diff --git a/Makefile b/Makefile index 87f5ccd..def86f1 100644 --- a/Makefile +++ b/Makefile @@ -1,4 +1,4 @@ -NAME=draft-iab-privsec-confidentiality-threat-00 +NAME=draft-iab-privsec-confidentiality-threat-07 MD=kramdown-rfc2629 X2R=xml2rfc CF=cupsfilter diff --git a/draft-iab-privsec-confidentiality-threat-01.md b/draft-iab-privsec-confidentiality-threat-01.md new file mode 100644 index 0000000..2eee21f --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-01.md @@ -0,0 +1,415 @@ +--- +title: "Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement" +abbrev: Confidentiality Threat Model +docname: draft-iab-privsec-confidentiality-threat-01 +date: 2014-12-12 +category: info +ipr: trust200902 + +author: + - + ins: R. Barnes + name: Richard Barnes + email: rlb@ipv.sx + - + ins: B. Schneier + name: Bruce Schneier + email: schneier@schneier.com + - + ins: C. Jennings + name: Cullen Jennings + email: fluffy@cisco.com + - + ins: T. Hardie + name: Ted Hardie + email: ted.ietf@gmail.com + - + ins: B. Trammell + name: Brian Trammell + email: ietf@trammell.ch + - + ins: C. Huitema + name: Christian Huitema + email: huitema@huitema.net + - + ins: D. Borkmann + name: Daniel Borkmann + email: dborkman@redhat.com + +normative: + RFC6973: + +informative: + pass1: + target: http://www.theguardian.com/world/2013/jun/27/nsa-online-metadata-collection + title: "How the NSA is still harvesting your online data" + author: + organization: The Guardian + date: 2013 + pass2: + target: http://www.theguardian.com/world/2013/jun/08/nsa-prism-server-collection-facebook-google + title: "NSA's Prism surveillance program: how it works and what it can do" + author: + organization: The Guardian + date: 2013 + pass3: + target: http://www.theguardian.com/world/2013/jul/31/nsa-top-secret-program-online-data + title: "XKeyscore: NSA tool collects 'nearly everything a user does on the internet'" + author: + organization: The Guardian + date: 2013 + pass4: + target: http://www.theguardian.com/uk/2013/jun/21/how-does-gchq-internet-surveillance-work + title: "How does GCHQ's internet surveillance work?" + author: + organization: The Guardian + dec1: + target: http://www.nytimes.com/2013/09/06/us/nsa-foils-much-internet-encryption.html + title: "N.S.A. Able to Foil Basic Safeguards of Privacy on Web" + author: + organization: The New York Times + date: 2013 + dec2: + target: http://www.theguardian.com/world/interactive/2013/sep/05/nsa-project-bullrun-classification-guide + title: "Project Bullrun – classification guide to the NSA's decryption program" + author: + organization: The Guardian + date: 2013 + dec3: + target: http://www.theguardian.com/world/2013/sep/05/nsa-gchq-encryption-codes-security + title: "Revealed: how US and UK spy agencies defeat internet privacy and security" + author: + organization: The Guardian + date: 2013 + TOR: + target: https://www.torproject.org/ + title: "Tor" + author: + organization: The Tor Project + date: 2013 + TOR1: + target: https://www.schneier.com/blog/archives/2013/10/how_the_nsa_att.html + title: "How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID" + author: + name: Bruce Schneier + ins: B. Schneier + date: 2013 + TOR2: + target: http://www.theguardian.com/world/interactive/2013/oct/04/tor-stinks-nsa-presentation-document + title: "'Tor Stinks' presentation – read the full document" + author: + organization: The Guardian + date: 2013 + dir1: + target: http://www.theguardian.com/world/2013/jun/06/nsa-phone-records-verizon-court-order + title: "NSA collecting phone records of millions of Verizon customers daily" + author: + organization: The Guardian + date: 2013 + dir2: + target: http://www.theguardian.com/world/2013/jun/06/us-tech-giants-nsa-data + title: "NSA Prism program taps in to user data of Apple, Google and others" + author: + organization: The Guardian + date: 2013 + dir3: + target: http://www.theguardian.com/world/interactive/2013/sep/05/sigint-nsa-collaborates-technology-companies + title: "Sigint – how the NSA collaborates with technology companies" + author: + organization: The Guardian + date: 2013 + secure: + target: http://www.theguardian.com/world/2013/sep/05/nsa-how-to-remain-secure-surveillance + title: "NSA surveillance: A guide to staying secure" + author: + name: Bruce Schneier + ins: B. Schneier + organization: The Guardian + date: 2013 + snowden: + target: http://www.technologyreview.com/news/519171/nsa-leak-leaves-crypto-math-intact-but-highlights-known-workarounds/ + title: NSA Leak Leaves Crypto-Math Intact but Highlights Known Workarounds + author: + organization: Technology Review + date: 2013 + key-recovery: + target: http://crypto.stanford.edu/~pgolle/papers/escrow.pdf + title: The Design and Implementation of Protocol-Based Hidden Key Recovery + author: + ins: E.-J. Goh + name: Eu-Jin Goh + author: + ins: D. Boneh + name: Dan Boneh + author: + ins: B. Pinkas + name: Benny Pinkas + author: + ins: P. Golle + name: Phillippe Golle + date: 2003 + RFC1035: + RFC1918: + RFC1939: + RFC2015: + RFC2821: + RFC3261: + RFC3365: + RFC3501: + RFC3851: + RFC4033: + RFC4301: + RFC4303: + RFC4306: + RFC4949: + RFC5246: + RFC5321: + RFC5655: + RFC5750: + RFC6120: + RFC6962: + RFC6698: + RFC7011: + RFC7258: + +--- abstract + +Documents published in 2013 revealed several classes of pervasive surveillance attack on Internet communications. In this document we develop a threat model that describes these pervasive attacks. We start by assuming a completely passive attacker with an interest in undetected, indiscriminate eavesdropping, then expand the threat model with a set of verified attacks that have been published. Based on this threat model, we discuss the techniques that can be employed in Internet protocol design to increase the protocols robustness to pervasive surveillance. + +--- middle + +# Introduction + +Starting in June 2013, documents released to the press by Edward Snowden have revealed several operations undertaken by intelligence agencies to exploit Internet communications for intelligence purposes. These attacks were largely based on protocol vulnerabilities that were already known to exist. The attacks were nonetheless striking in their pervasive nature, both in terms of the amount of Internet communications targeted, and in terms of the diversity of attack techniques employed. + +To ensure that the Internet can be trusted by users, it is necessary for the Internet technical community to address the vulnerabilities exploited in these attacks {{RFC7258}}. The goal of this document is to describe more precisely the threats posed by these pervasive attacks, and based on those threats, lay out the problems that need to be solved in order to secure the Internet in the face of those threats. + +The remainder of this document is structured as follows. In {{adversary}}, we describe an idealized passive attacket, one which could completely undetectably compromise communications at Internet scale. In {{reported}}, we provide a brief summary of some attacks that have been disclosed, and use these to expand the assumed capabilities of our idealized attacker. {{model}} describes a threat model based on these attacks, focusing on classes of attack that have not been a focus of Internet engineering to date. + +# Terminology {#terminology} + +This document makes extensive use of standard security and privacy terminology; see {{RFC4949}} and {{RFC6973}}. Terms used from {{RFC6973}} include Eavesdropper, Observer, Initiator, Intermediary, Recipient, Attack (in a privacy context), Correlation, Fingerprint, Traffic Analysis, and Identifiability (and related terms). In addition, we use a few terms that are specific to the attacks discussed here: + +Pervasive Attack: +: An attack on Internet communications that makes use of access at a large number of points in the network, or otherwise provides the attacker with access to a large amount of Internet traffic; see {{RFC7258}} + +Observation: +: Information collected directly from communications by an eavesdropper or observer. For example, the knowledge that <alice@example.com> sent a message to <bob@example.com> via SMTP taken from the headers of an observed SMTP message would be an observation. + +Inference: +: Information extracted from analysis of information collected directly from communications by an eavesdropper or observer. For example, the knowledge that a given web page was accessed by a given IP address, by comparing the size in octets of measured network flow records to fingerprints derived from known sizes of linked resources on the web servers involved, would be an +inference. + +Collaborator: +: An entity that is a legitimate participant in a communication, but who provides information about that interaction (keys or data) to an attacker. + +Unwitting Collaborator: +: A collaborator that provides information to the attacker not deliberately, but because the attacker has exploited some technology used by the collaborator. + +Key Exfiltration: +: The transmission of keying material for an encrypted communication from a collaborator to an attacker + +Content Exfiltration: +: The transmission of the content of a communication from a collaborator to an attacker + +# An Idealized Pervasive Passive Attacker {#adversary} + +To build a thread model, we first assume a pervasive passive attacker, an indiscriminate eavesdropper on an Internet-attached computer network that + +- can observe every packet of all communications at any or every hop in any network path between an initiator and a recipient; and +- can observe data at rest in intermediate systems between the endpoints controlled by the initiator and recipient; but +- takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.). + +This attacker is less capable than those which we know to have compromised the Internet from press reports, elaborated in {{reported}}, but represents the threat to communications privacy by a single eavesdropper interested in remaining undetectable. + +The techniques available to our ideal attacker are direct observation and inference. Direct observation involves taking information directly from eavesdropped communications - e.g., URLs identifying content or email addresses identifying individuals from application-layer headers. Inference, on the other hand, involves analyzing eavesdropped information to derive new information from it; e.g., searching for application or behavioral fingerprints in observed traffic to derive information about the observed individual from them, in absence of directly-observed sources of the same information. The use of encryption to protect confidentiality is generally enough to prevent direct observation, assuming uncompromised encryption implementations and key material, but provides less complete protection against inference, especially inference based only on unprotected portions of communications (e.g. IP and TCP headers for TLS {{RFC5246}}). + +## Information subject to direct observation + +Protocols which do not encrypt their payload make the entire content of the communication available to the idealized attacker along their path. Following the advice in {{RFC3365}}, most such protocols have a secure variant which encrypts payload for confidentiality, and these secure variants are seeing ever-wider deployment. A noteworthy exception is DNS {{RFC1035}}, as DNSSEC {{RFC4033}} does not have confidentiality as a requirement. This implies that all DNS queries and answers generated by the activities of any protocol are available to the attacker. + +Protocols which imply the storage of some data at rest in intermediaries (e.g. SMTP {{RFC5321}}) leave this data subject to observation by an attacker that has compromised these intermediaries, unless the data is encrypted end-to-end by the application layer protocol, or the implementation uses an encrypted store for this data. + +## Information useful for inference + +Inference is information extracted from later analysis of an observed or eavesdropped communication, and/or correlation of observed or eavesdropped information with information available from other sources. Indeed, most useful inference performed by the attacker falls under the rubric of correlation. The simplest example of this is the observation of DNS queries and answers from and to a source and correlating those with IP addresses with which that source communicates. This can give access to information otherwise not available from encrypted application payloads (e.g., the Host: HTTP/1.1 request header when HTTP is used with TLS). + +Protocols which encrypt their payload using an application- or transport-layer encryption scheme (e.g. TLS) still expose all the information in their network and transport layer headers to the attacker, including source and destination addresses and ports. IPsec ESP{{RFC4303}} further encrypts the transport-layer headers, but still leaves IP address information unencrypted; in tunnel mode, these addresses correspond to the tunnel endpoints. Features of the cryptographic protocols themselves, e.g. the TLS session identifier, may leak information that can be used for correlation and inference. While this information is much less semantically rich than the application payload, it can still be useful for the inferring an individual's activities. + +Inference can also leverage information obtained from sources other than direct traffic observation. Geolocation databases, for example, have been developed map IP addresses to a location, in order to provide location-aware services such as targeted advertising. This location information is often of sufficient resolution that it can be used to draw further inferences toward identifying or profiling an individual. + +Social media provide another source of more or less publicly accessible information. This information can be extremely semantically rich, including information about an individual's location, associations with other individuals and groups, and activities. Further, this information is generally contributed and curated voluntarily by the individuals themselves: it represents information which the individuals are not necessarily interested in protecting for privascy reasons. However, correlation of this social networking data with information available from direct observation of network traffic allows the creation of a much richer picture of an individual's activities than either alone. We note with some alarm that there is little that can be done at protocol design time to limit such correlation by the attacker, and that the existence of such data sources in many cases greatly complicates the problem of protecting privacy by hardening protocols alone. + +## An illustration of an ideal passive attack + +To illustrate how capable the attacker is even given its limitations, we explore the non-anonymity of even encrypted IP traffic by examining in detail some inference techniques for associating a set of addresses with an individual, in order to illustrate the difficulty of defending communications against our idealized attacker. Here, the basic problem is that information radiated even from protocols which have no obvious connection with personal data can be correlated with other information which can paint a very rich behavioral picture, that only takes one unprotected link in the chain to associate with an identity. + +### Analysis of IP headers + +Internet traffic can be monitored by tapping Internet links, or by installing monitoring tools in Internet routers. Of course, a single link or a single router only provides access to a fraction of the global Internet traffic. However, monitoring a number of high capacity links or a set of routers placed at strategic locations provides access to a good sampling of Internet traffic. + +Tools like IPFIX {{RFC7011}} allow administrators to acquire statistics about sequences of packets with some common properties that pass through a network device. The most common set of properties used in flow measurement is the "five-tuple"of source and destination addresses, protocol type, and source and destination ports. These statistics are commonly used for network engineering, but could certainly be used for other purposes. + +Let's assume for a moment that IP addresses can be correlated to specific services or specific users. Analysis of the sequences of packets will quickly reveal which users use what services, and also which users engage in peer-to-peer connections with other users. Analysis of traffic variations over time can be used to detect increased activity by particular users, or in the case of peer-to-peer connections increased activity within groups of users. + +### Correlation of IP addresses to user identities + +The correlation of IP addresses with specific users can be done in various ways. For example, tools like reverse DNS lookup can be used to retrieve the DNS names of servers. Since the addresses of servers tend to be quite stable and since servers are relatively less numerous than users, an attacker could easily maintain its own copy of the DNS for well-known or popular servers, to accelerate such lookups. + +On the other hand, the reverse lookup of IP addresses of users is generally less informative. For example, a lookup of the address currently used by one author's home network returns a name of the form "c-192-000-002-033.hsd1.wa.comcast.net". This particular type of reverse DNS lookup generally reveals only coarse-grained location or provider information. + +In many jurisdictions, Internet Service Providers (ISPs) are required to provide identification on a case by case basis of the "owner" of a specific IP address for law enforcement purposes. This is a reasonably expedient process for targeted investigations, but pervasive surveillance requires something more efficient. This provides an incentive for the attacker to secure the cooperation of the ISP in order to automate this correlation. + +### Monitoring messaging clients for IP address correlation + +Even if the ISP does not cooperate, user identity can often be obtained via inference. POP3 {{RFC1939}} and IMAP {{RFC3501}} are used to retrieve mail from mail servers, while a variant of SMTP is used to submit messages through mail servers. IMAP connections originate from the client, and typically start with an authentication exchange in which the client proves its identity by answering a password challenge. The same holds for the SIP protocol {{RFC3261}} and many instant messaging services operating over the Internet using proprietary protocols. + +The username is directly observable if any of these protocols operate in cleartext; the username can then be directly associated with the source address. + +### Retrieving IP addresses from mail headers + +SMTP {{RFC5321}} requires that each successive SMTP relay adds a "Received" header to the mail headers. The purpose of these headers is to enable audit of mail transmission, and perhaps to distinguish between regular mail and spam. Here is an extract from the headers of a message recently received from the "perpass" mailing list: + +``` + Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?) + (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA + (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100 + Message-ID: <526D7BD2.7070908@example.org> + Date: Sun, 27 Oct 2013 20:47:14 +0000 + From: Some One +``` + +This is the first "Received" header attached to the message by the first SMTP relay; for privacy reasons, the field values have been anonymized. We learn here that the message was submitted by "Some One" on October 27, from a host behind a NAT (192.168.1.100) {{RFC1918}} that used the IP address 192.0.2.44. The information remained in the message, and is accessible by all recipients of the "perpass" mailing list, or indeed by any attacker that sees at least one copy of the message. + +An attacker that can observe sufficient email traffic can regularly update the mapping between public IP addresses and individual email identities. Even if the SMTP traffic was encrypted on submission and relaying, the attacker can still receive a copy of public mailing lists like "perpass". + +### Tracking address usage with web cookies + +Many web sites only encrypt a small fraction of their transactions. A popular pattern is to use HTTPS for the login information, and then use a "cookie" to associate following clear-text transactions with the user's identity. Cookies are also used by various advertisement services to quickly identify the users and serve them with "personalized" advertisements. Such cookies are particularly useful if the advertisement services want to keep tracking the user across multiple sessions that may use different IP addresses. + +As cookies are sent in clear text, an attacker can build a database that associates cookies to IP addresses for non-HTTPS traffic. If the IP address is already identified, the cookie can be linked to the user identify. After that, if the same cookie appears on a new IP address, the new IP address can be immediately associated with the pre-determined identity. + +### Graph-based approaches to address correlation + +An attacker can track traffic from an IP address not yet associated with an individual to various public services (e.g. websites, mail servers, game servers), and exploit patterns in the observed traffic to correlate this address with other addresses that show similar patterns. For example, any two addresses that show connections to the same IMAP or webmail services, the same set of favorite websites, and game servers at similar times of day may be associated with the same individual. Correlated addresses can then be tied to an individual through one of the techniques above, walking the "network graph" to expand the set of attributable traffic. + +### Tracking of MAC Addresses + +Moving back down the stack, technologies like Ethernet or Wi-Fi use MAC Addresses to identify link-level destinations. MAC Addresses assigned according to IEEE-802 standards are unique to the device. If the link is publicly accessible, an attacker can track it. For example, the attacker can track the wireless traffic at public Wi-Fi networks. Simple devices can monitor the traffic, and reveal which MAC Addresses are present. If the network does not use some form of Wi-Fi encryption, or if the attacker can access the decrypted traffic, the analysis will also provide the correlation between MAC Addresses and IP addresses. Additional monitoring using techniques exposed in the previous sections will reveal the correlation between MAC Addresses, IP Addresses, and user identity. The attacker can conceivably build a database linking MAC Addresses and device or user identities, and use it to track the movement of devices and of their owners. + + +# Reported Instances of Large-Scale Attacks {#reported} + +The situation in reality is more bleak than that suggested by an analysis of our idealized attacker. Through revelations of sensitive documents in several media outlets, the Internet community has been made aware of several intelligence activities conducted by US and UK national intelligence agencies, particularly the US National Security Agency (NSA) and the UK Government Communications Headquarters (GCHQ). These documents have revealed methods that these agencies use to attack Internet applications and obtain sensitive user information. + +First, they have confirmed that these agencies have capabilities in line with those of our idealized attacker, thorugh the large-scale passive collection of Internet traffic {{pass1}}{{pass2}}{{pass3}}{{pass4}}. For example: + - The NSA XKEYSCORE system accesses data from multiple access points and searches for "selectors" such as email addresses, at the scale of tens of terabytes of data per day. + - The GCHQ Tempora system appears to have access to around 1,500 major cables passing through the UK. + - The NSA MUSCULAR program tapped cables between data centers belonging to major service providers. + - Several programs appear to perform wide-scale collection of cookies in web traffic and location data from location-aware portable devices such as smartphones. + +However, the capabilities described go beyond those available to our idealized attacker, including: + +* Decryption of TLS-protected Internet sessions {{dec1}}{{dec2}}{{dec3}}. For example, the NSA BULLRUN project appears to have had a budget of around $250M per year to undermine encryption through multiple approaches. + +* Insertion of NSA devices as a man-in-the-middle of Internet transactions {{TOR1}}{{TOR2}}. For example, the NSA QUANTUM system appears to use several different techniques to hijack HTTP connections, ranging from DNS response injection to HTTP 302 redirects. + +* Direct acquisition of bulk data and metadata from service providers {{dir1}}{{dir2}}{{dir3}}. For example, the NSA PRISM program provides the agency with access to many types of user data (e.g., email, chat, VoIP). + +* Use of implants (covert modifications or malware) to undermine security and anonymity features {{dec2}}{{TOR1}}{{TOR2}}. For example: + * NSA appears to use the QUANTUM man-in-the-middle system to direct users to a FOXACID server, which delivers an implant to compromise the browser of a user of the Tor anonymous communications network. + * The BULLRUN program mentioned above includes the addition of covert modifications to software as one means to undermine encryption. + * There is also some suspicion that NSA modifications to the DUAL\_EC\_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA. These suspicions have been reinforced by reports that RSA Security was paid roughly $10M to make DUAL\_EC\_DRBG the default in their products. + +We use the term "pervasive attack" {{RFC7258}} to collectively describe these operations. The term "pervasive" is used because the attacks are designed to indiscriminately gather as much data as possible and to apply selective analysis on targets after the fact. This means that all, or nearly all, Internet communications are targets for these attacks. To achieve this scale, the attacks are physically pervasive; they affect a large number of Internet communications. They are pervasive in content, consuming and exploiting any information revealed by the protocol. And they are pervasive in technology, exploiting many different vulnerabilities in many different protocols. + +It's important to note that although the attacks mentioned above were executed by NSA and GCHQ, there are many other organizations that can mount pervasive surveillance attacks. Because of the resources required to achieve pervasive scale, these attacks are most commonly undertaken by nation-state actors. For example, the Chinese Internet filtering system known as the "Great Firewall of China" uses several techniques that are similar to the QUANTUM program, and which have a high degree of pervasiveness with regard to the Internet in China. + +# Threat Model {#model} + +Given these disclosures, we must consider a broader threat model. + +Pervasive surveillance aims to collect information across a large number of Internet communications, analyzing the collected communications to identify information of interest within individual communications, or inferring information from correlated communications. his analysis sometimes benefits from decryption of encrypted communications and deanonymization of anonymized communications. As a result, these attackers desire both access to the bulk of Internet traffic and to the keying material required to decrypt any traffic that has been encrypted. Even if keys are not available, note that the presence of a communication and the fact that it is encrypted may both be inputs to an analysis, even if the attacker cannot decrypt the communication. + +The attacks listed above highlight new avenues both for access to traffic and for access to relevant encryption keys. They further indicate that the scale of surveillance is sufficient to provide a general capability to cross-correlate communications, a threat not previously thought to be relevant at the scale of the Internet. + +## Attacker Capabilities + +| Attack Class | Capability | +|:--------------------------|:------------------------------------------| +| Passive observation | Directly capture data in transit | +| Passive inference | Infer from reduced/encrypted data | +| Active | Manipulate / inject data in transit | +| Static key exfiltration | Obtain key material once / rarely | +| Dynamic key exfiltration | Obtain per-session key material | +| Content exfiltration | Access data at rest | + +Security analyses of Internet protocols commonly consider two classes of attacker: Passive attackers, who can simply listen in on communications as they transit the network, and active attackers, who can modify or delete packets in addition to simply collecting them. + +In the context of pervasive passive surveillance, these attacks take on an even greater significance. In the past, these attackers were often assumed to operate near the edge of the network, where attacks can be simpler. For example, in some LANs, it is simple for any node to engage in passive listening to other nodes' traffic or inject packets to accomplish active attacks. However, as we now know, both passive and active attacks are undertaken by pervasive attackers closer to the core of the network, greatly expanding the scope and capability of the attacker. + +Eavesdropping and observation at a larger scale make passive inference attacks easier to carry out: a passive attacker with access to a large portion of the Internet can analyze collected traffic to create a much more detailed view of individual behavior than an attacker that collects at a single point. Even the usual claim that encryption defeats passive attackers is weakened, since a pervasive passive attacker can infer relationships from correlations over large numbers of sessions, e.g., pairing encrypted sessions with unencrypted sessions from the same host, or performing traffic fingerprinting between known and unknown encrypted sessions. Reports on the NSA XKEYSCORE system would indicate it is an example of such an attacker. + +A pervasive active attacker likewise has capabilities beyond those of a localized active attacker. Active attacks are often limited by network topology, for example by a requirement that the attacker be able to see a targeted session as well as inject packets into it. A pervasive active attacker with access at multiple points within the core of the Internet is able to overcome these topological limitations and perform attacks over a much broader scope. Being positioned in the core of the network rather than the edge can also enable a pervasive active attacker to reroute targeted traffic, amplifying the ability to perform both eavesdropping and traffic injection. Pervasive active attackers can also benefit from pervasive passive collection to identify vulnerable hosts. + +While not directly related to pervasiveness, attackers that are in a position to mount a pervasive active attack are also often in a position to subvert authentication, a traditional protection against such attacks. Authentication in the Internet is often achieved via trusted third party authorities such as the Certificate Authorities (CAs) that provide web sites with authentication credentials. An attacker with sufficient resources may also be able to induce an authority to grant credentials for an identity of the attacker’s choosing. If the parties to a communication will trust multiple authorities to certify a specific identity, this attack may be mounted by suborning any one of the authorities (the proverbial "weakest link"). Subversion of authorities in this way can allow an active attack to succeed in spite of an authentication check. + +Beyond these three classes (observation, inference, and active), reports on the BULLRUN effort to defeat encryption and the PRISM effort to obtain data from service providers suggest three more classes of attack: + +* Static key exfiltration +* Dynamic key exfiltration +* Content exfiltration + +These attacks all rely on a collaborator providing the attacker with some information, either keys or data. These attacks have not traditionally been considered in security analyses of protocols, since they happen outside of the protocol. + +The term "key exfiltration" refers to the transfer of keying material for an encrypted communication from the collaborator to the attacker. By "static", we mean that the transfer of keys happens once, or rarely, typically of a long-lived key. For example, this case would cover a web site operator that provides the private key corresponding to its HTTPS certificate to an intelligence agency. + +"Dynamic" key exfiltration, by contrast, refers to attacks in which the collaborator delivers keying material to the attacker frequently, e.g., on a per-session basis. This does not necessarily imply frequent communications with the attacker; the transfer of keying material may be virtual. For example, if an endpoint were modified in such a way that the attacker could predict the state of its psuedorandom number generator, then the attacker would be able to derive per-session keys even without per-session communications. + +Finally, content exfiltration is the attack in which the collaborator simply provides the attacker with the desired data or metadata. Unlike the key exfiltration cases, this attack does not require the attacker to capture the desired data as it flows through the network. The risk is to data at rest as opposed to data in transit. This increases the scope of data that the attacker can obtain, since the attacker can access historical data -- the attacker does not have to be listening at the time the communication happens. + +Exfiltration attacks can be accomplished via attacks against one of the parties to a communication, i.e., by the attacker stealing the keys or content rather than the party providing them willingly. In these cases, the party may not be aware that they are collaborating, at least at a human level. Rather, the subverted technical assets are "collaborating" with the attacker (by providing keys/content) without their owner's knowledge or consent. + +Any party that has access to encryption keys or unencrypted data can be a collaborator. While collaborators are typically the endpoints of a communication (with encryption securing the links), intermediaries in an unencrypted communication can also facilitate content exfiltration attacks as collaborators by providing the attacker access to those communications. For example, documents describing the NSA PRISM program claim that NSA is able to access user data directly from servers, where it is stored unencrypted. In these cases, the operator of the server would be a collaborator, if an unwitting one. By contrast, in the NSA MUSCULAR program, a set of collaborators enabled attackers to access the cables connecting data centers used by service providers such as Google and Yahoo. Because communications among these data centers were not encrypted, the collaboration by an intermediate entity allowed NSA to collect unencrypted user data. + +## Attacker Costs + +| Attack Class | Cost / Risk to Attacker | +|:--------------------------|:----------------------------------| +| Passive observation | Passive data access | +| Passive inference | Passive data access + processing | +| Active | Active data access + processing | +| Static key exfiltration | One-time interaction | +| Dynamic key exfiltration | Ongoing interaction / code change | +| Content exfiltration | Ongoing, bulk interaction | + +Each of the attack types discussed in the previous section entails certain costs and risks. These costs differ by attack, and can be helpful in guiding response to pervasive attack. + +Depending on the attack, the attacker may be exposed to several types of risk, ranging from simply losing access to arrest or prosecution. In order for any of these negative consequences to occur, however, the attacker must first be discovered and identified. So the primary risk we focus on here is the risk of discovery and attribution. + +A passive attack is the simplest to mount in some ways. The base requirement is that the attacker obtain physical access to a communications medium and extract communications from it. For example, the attacker might tap a fiber-optic cable, acquire a mirror port on a switch, or listen to a wireless signal. The need for these taps to have physical access or proximity to a link exposes the attacker to the risk that the taps will be discovered. For example, a fiber tap or mirror port might be discovered by network operators noticing increased attenuation in the fiber or a change in switch configuration. Of course, passive attacks may be accomplished with the cooperation of the network operator, in which case there is a risk that the attacker's interactions with the network operator will be exposed. + +In many ways, the costs and risks for an active attack are similar to those for a passive attack, with a few additions. An active attacker requires more robust network access than a passive attacker, since for example they will often need to transmit data as well as receiving it. In the wireless example above, the attacker would need to act as an transmitter as well as receiver, greatly increasing the probability the attacker will be discovered (e.g., using direction-finding technology). Active attacks are also much more observable at higher layers of the network. For example, an active attacker that attempts to use a mis-issued certificate could be detected via Certificate Transparency {{RFC6962}}. + +In terms of raw implementation complexity, passive attacks require only enough processing to extract information from the network and store it. Active attacks, by contrast, often depend on winning race conditions to inject pakets into active connections. So active attacks in the core of the network require processing hardware to that can operate at line speed (roughly 100Gbps to 1Tbps in the core) to identify opportunities for attack and insert attack traffic in a high-volume traffic. +Key exfiltration attacks rely on passive attack for access to encrypted data, with the collaborator providing keys to decrypt the data. So the attacker undertakes the cost and risk of a passive attack, as well as additional risk of discovery via the interactions that the attacker has with the collaborator. + +In this sense, static exfiltration has a lower risk profile than dynamic. In the static case, the attacker need only interact with the collaborator a small number of times, possibly only once, say to exchange a private key. In the dynamic case, the attacker must have continuing interactions with the collaborator. As noted above these interactions may real, such as in-person meetings, or virtual, such as software modifications that render keys available to the attacker. Both of these types of interactions introduce a risk that they will be discovered, e.g., by employees of the collaborator organization noticing suspicious meetings or suspicious code changes. + +Content exfiltration has a similar risk profile to dynamic key exfiltration. In a content exfiltration attack, the attacker saves the cost and risk of conducting a passive attack. The risk of discovery through interactions with the collaborator, however, is still present, and may be higher. The content of a communication is obviously larger than the key used to encrypt it, often by several orders of magnitude. So in the content exfiltration case, the interactions between the collaborator and the attacker need to be much higher-bandwidth than in the key exfiltration cases, with a corresponding increase in the risk that this high-bandwidth channel will be discovered. + +It should also be noted that in these latter three exfiltration cases, the collaborator also undertakes a risk that his collaboration with the attacker will be discovered. Thus the attacker may have to incur additional cost in order to convince the collaborator to participate in the attack. Likewise, the scope of these attacks is limited to case where the attacker can convince a collaborator to participate. If the attacker is a national government, for example, it may be able to compel participation within its borders, but have a much more difficult time recruiting foreign collaborators. + +As noted above, the collaborator in an exfiltration attack can be unwitting; the attacker can steal keys or data to enable the attack. In some ways, the risks of this approach are similar to the case of an active collaborator. In the static case, the attacker needs to steal information from the collaborator once; in the dynamic case, the attacker needs to continued presence inside the collaborators systems. The main difference is that the risk in this case is of automated discovery (e.g., by intrusion detection systems) rather than discovery by humans. + +# Security Considerations + +This document describes a threat model for pervasive surveillance attacks. Mitigations are to be given in a future document. + +# IANA Considerations + +This document has no actions for IANA. + +# Acknowledgements + +Thanks to Dave Thaler for the list of attacks and taxonomy; to Security Area Directors Stephen Farrell, Sean Turner, and Kathleen Moriarty for starting and managing the IETF's discussion on pervasive attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, and Evangelos Halepilidis, and to the membership of the IAB Privacy and Security Program for their input. diff --git a/draft-iab-privsec-confidentiality-threat-01.txt b/draft-iab-privsec-confidentiality-threat-01.txt new file mode 100644 index 0000000..107d052 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-01.txt @@ -0,0 +1,1176 @@ + + + + +Network Working Group R. Barnes +Internet-Draft +Intended status: Informational B. Schneier +Expires: June 15, 2015 + C. Jennings + + T. Hardie + + B. Trammell + + C. Huitema + + D. Borkmann + + December 12, 2014 + + + Confidentiality in the Face of Pervasive Surveillance: A Threat Model + and Problem Statement + draft-iab-privsec-confidentiality-threat-01 + +Abstract + + Documents published in 2013 revealed several classes of pervasive + surveillance attack on Internet communications. In this document we + develop a threat model that describes these pervasive attacks. We + start by assuming a completely passive attacker with an interest in + undetected, indiscriminate eavesdropping, then expand the threat + model with a set of verified attacks that have been published. Based + on this threat model, we discuss the techniques that can be employed + in Internet protocol design to increase the protocols robustness to + pervasive surveillance. + +Status of This Memo + + This Internet-Draft is submitted in full conformance with the + provisions of BCP 78 and BCP 79. + + Internet-Drafts are working documents of the Internet Engineering + Task Force (IETF). Note that other groups may also distribute + working documents as Internet-Drafts. The list of current Internet- + Drafts is at http://datatracker.ietf.org/drafts/current/. + + Internet-Drafts are draft documents valid for a maximum of six months + and may be updated, replaced, or obsoleted by other documents at any + time. It is inappropriate to use Internet-Drafts as reference + material or to cite them other than as "work in progress." + + + + +Barnes, et al. Expires June 15, 2015 [Page 1] + +Internet-Draft Confidentiality Threat Model December 2014 + + + This Internet-Draft will expire on June 15, 2015. + +Copyright Notice + + Copyright (c) 2014 IETF Trust and the persons identified as the + document authors. All rights reserved. + + This document is subject to BCP 78 and the IETF Trust's Legal + Provisions Relating to IETF Documents + (http://trustee.ietf.org/license-info) in effect on the date of + publication of this document. Please review these documents + carefully, as they describe your rights and restrictions with respect + to this document. Code Components extracted from this document must + include Simplified BSD License text as described in Section 4.e of + the Trust Legal Provisions and are provided without warranty as + described in the Simplified BSD License. + +1. Introduction + + Starting in June 2013, documents released to the press by Edward + Snowden have revealed several operations undertaken by intelligence + agencies to exploit Internet communications for intelligence + purposes. These attacks were largely based on protocol + vulnerabilities that were already known to exist. The attacks were + nonetheless striking in their pervasive nature, both in terms of the + amount of Internet communications targeted, and in terms of the + diversity of attack techniques employed. + + To ensure that the Internet can be trusted by users, it is necessary + for the Internet technical community to address the vulnerabilities + exploited in these attacks [RFC7258]. The goal of this document is + to describe more precisely the threats posed by these pervasive + attacks, and based on those threats, lay out the problems that need + to be solved in order to secure the Internet in the face of those + threats. + + The remainder of this document is structured as follows. In + Section 3, we describe an idealized passive attacket, one which could + completely undetectably compromise communications at Internet scale. + In Section 4, we provide a brief summary of some attacks that have + been disclosed, and use these to expand the assumed capabilities of + our idealized attacker. Section 5 describes a threat model based on + these attacks, focusing on classes of attack that have not been a + focus of Internet engineering to date. + + + + + + + +Barnes, et al. Expires June 15, 2015 [Page 2] + +Internet-Draft Confidentiality Threat Model December 2014 + + +2. Terminology + + This document makes extensive use of standard security and privacy + terminology; see [RFC4949] and [RFC6973]. Terms used from [RFC6973] + include Eavesdropper, Observer, Initiator, Intermediary, Recipient, + Attack (in a privacy context), Correlation, Fingerprint, Traffic + Analysis, and Identifiability (and related terms). In addition, we + use a few terms that are specific to the attacks discussed here: + + Pervasive Attack: An attack on Internet communications that makes + use of access at a large number of points in the network, or + otherwise provides the attacker with access to a large amount of + Internet traffic; see [RFC7258] + + Observation: Information collected directly from communications by + an eavesdropper or observer. For example, the knowledge that + sent a message to via SMTP + taken from the headers of an observed SMTP message would be an + observation. + + Inference: Information extracted from analysis of information + collected directly from communications by an eavesdropper or + observer. For example, the knowledge that a given web page was + accessed by a given IP address, by comparing the size in octets of + measured network flow records to fingerprints derived from known + sizes of linked resources on the web servers involved, would be an + inference. + + Collaborator: An entity that is a legitimate participant in a + communication, but who provides information about that interaction + (keys or data) to an attacker. + + Unwitting Collaborator: A collaborator that provides information to + the attacker not deliberately, but because the attacker has + exploited some technology used by the collaborator. + + Key Exfiltration: The transmission of keying material for an + encrypted communication from a collaborator to an attacker + + Content Exfiltration: The transmission of the content of a + communication from a collaborator to an attacker + +3. An Idealized Pervasive Passive Attacker + + To build a thread model, we first assume a pervasive passive + attacker, an indiscriminate eavesdropper on an Internet-attached + computer network that + + + + +Barnes, et al. Expires June 15, 2015 [Page 3] + +Internet-Draft Confidentiality Threat Model December 2014 + + + o can observe every packet of all communications at any or every hop + in any network path between an initiator and a recipient; and + + o can observe data at rest in intermediate systems between the + endpoints controlled by the initiator and recipient; but + + o takes no other action with respect to these communications (i.e., + blocking, modification, injection, etc.). + + This attacker is less capable than those which we know to have + compromised the Internet from press reports, elaborated in Section 4, + but represents the threat to communications privacy by a single + eavesdropper interested in remaining undetectable. + + The techniques available to our ideal attacker are direct observation + and inference. Direct observation involves taking information + directly from eavesdropped communications - e.g., URLs identifying + content or email addresses identifying individuals from application- + layer headers. Inference, on the other hand, involves analyzing + eavesdropped information to derive new information from it; e.g., + searching for application or behavioral fingerprints in observed + traffic to derive information about the observed individual from + them, in absence of directly-observed sources of the same + information. The use of encryption to protect confidentiality is + generally enough to prevent direct observation, assuming + uncompromised encryption implementations and key material, but + provides less complete protection against inference, especially + inference based only on unprotected portions of communications (e.g. + IP and TCP headers for TLS [RFC5246]). + +3.1. Information subject to direct observation + + Protocols which do not encrypt their payload make the entire content + of the communication available to the idealized attacker along their + path. Following the advice in [RFC3365], most such protocols have a + secure variant which encrypts payload for confidentiality, and these + secure variants are seeing ever-wider deployment. A noteworthy + exception is DNS [RFC1035], as DNSSEC [RFC4033] does not have + confidentiality as a requirement. This implies that all DNS queries + and answers generated by the activities of any protocol are available + to the attacker. + + Protocols which imply the storage of some data at rest in + intermediaries (e.g. SMTP [RFC5321]) leave this data subject to + observation by an attacker that has compromised these intermediaries, + unless the data is encrypted end-to-end by the application layer + protocol, or the implementation uses an encrypted store for this + data. + + + +Barnes, et al. Expires June 15, 2015 [Page 4] + +Internet-Draft Confidentiality Threat Model December 2014 + + +3.2. Information useful for inference + + Inference is information extracted from later analysis of an observed + or eavesdropped communication, and/or correlation of observed or + eavesdropped information with information available from other + sources. Indeed, most useful inference performed by the attacker + falls under the rubric of correlation. The simplest example of this + is the observation of DNS queries and answers from and to a source + and correlating those with IP addresses with which that source + communicates. This can give access to information otherwise not + available from encrypted application payloads (e.g., the Host: + HTTP/1.1 request header when HTTP is used with TLS). + + Protocols which encrypt their payload using an application- or + transport-layer encryption scheme (e.g. TLS) still expose all the + information in their network and transport layer headers to the + attacker, including source and destination addresses and ports. + IPsec ESP[RFC4303] further encrypts the transport-layer headers, but + still leaves IP address information unencrypted; in tunnel mode, + these addresses correspond to the tunnel endpoints. Features of the + cryptographic protocols themselves, e.g. the TLS session identifier, + may leak information that can be used for correlation and inference. + While this information is much less semantically rich than the + application payload, it can still be useful for the inferring an + individual's activities. + + Inference can also leverage information obtained from sources other + than direct traffic observation. Geolocation databases, for example, + have been developed map IP addresses to a location, in order to + provide location-aware services such as targeted advertising. This + location information is often of sufficient resolution that it can be + used to draw further inferences toward identifying or profiling an + individual. + + Social media provide another source of more or less publicly + accessible information. This information can be extremely + semantically rich, including information about an individual's + location, associations with other individuals and groups, and + activities. Further, this information is generally contributed and + curated voluntarily by the individuals themselves: it represents + information which the individuals are not necessarily interested in + protecting for privascy reasons. However, correlation of this social + networking data with information available from direct observation of + network traffic allows the creation of a much richer picture of an + individual's activities than either alone. We note with some alarm + that there is little that can be done at protocol design time to + limit such correlation by the attacker, and that the existence of + + + + +Barnes, et al. Expires June 15, 2015 [Page 5] + +Internet-Draft Confidentiality Threat Model December 2014 + + + such data sources in many cases greatly complicates the problem of + protecting privacy by hardening protocols alone. + +3.3. An illustration of an ideal passive attack + + To illustrate how capable the attacker is even given its limitations, + we explore the non-anonymity of even encrypted IP traffic by + examining in detail some inference techniques for associating a set + of addresses with an individual, in order to illustrate the + difficulty of defending communications against our idealized + attacker. Here, the basic problem is that information radiated even + from protocols which have no obvious connection with personal data + can be correlated with other information which can paint a very rich + behavioral picture, that only takes one unprotected link in the chain + to associate with an identity. + +3.3.1. Analysis of IP headers + + Internet traffic can be monitored by tapping Internet links, or by + installing monitoring tools in Internet routers. Of course, a single + link or a single router only provides access to a fraction of the + global Internet traffic. However, monitoring a number of high + capacity links or a set of routers placed at strategic locations + provides access to a good sampling of Internet traffic. + + Tools like IPFIX [RFC7011] allow administrators to acquire statistics + about sequences of packets with some common properties that pass + through a network device. The most common set of properties used in + flow measurement is the "five-tuple"of source and destination + addresses, protocol type, and source and destination ports. These + statistics are commonly used for network engineering, but could + certainly be used for other purposes. + + Let's assume for a moment that IP addresses can be correlated to + specific services or specific users. Analysis of the sequences of + packets will quickly reveal which users use what services, and also + which users engage in peer-to-peer connections with other users. + Analysis of traffic variations over time can be used to detect + increased activity by particular users, or in the case of peer-to- + peer connections increased activity within groups of users. + +3.3.2. Correlation of IP addresses to user identities + + The correlation of IP addresses with specific users can be done in + various ways. For example, tools like reverse DNS lookup can be used + to retrieve the DNS names of servers. Since the addresses of servers + tend to be quite stable and since servers are relatively less + numerous than users, an attacker could easily maintain its own copy + + + +Barnes, et al. Expires June 15, 2015 [Page 6] + +Internet-Draft Confidentiality Threat Model December 2014 + + + of the DNS for well-known or popular servers, to accelerate such + lookups. + + On the other hand, the reverse lookup of IP addresses of users is + generally less informative. For example, a lookup of the address + currently used by one author's home network returns a name of the + form "c-192-000-002-033.hsd1.wa.comcast.net". This particular type + of reverse DNS lookup generally reveals only coarse-grained location + or provider information. + + In many jurisdictions, Internet Service Providers (ISPs) are required + to provide identification on a case by case basis of the "owner" of a + specific IP address for law enforcement purposes. This is a + reasonably expedient process for targeted investigations, but + pervasive surveillance requires something more efficient. This + provides an incentive for the attacker to secure the cooperation of + the ISP in order to automate this correlation. + +3.3.3. Monitoring messaging clients for IP address correlation + + Even if the ISP does not cooperate, user identity can often be + obtained via inference. POP3 [RFC1939] and IMAP [RFC3501] are used + to retrieve mail from mail servers, while a variant of SMTP is used + to submit messages through mail servers. IMAP connections originate + from the client, and typically start with an authentication exchange + in which the client proves its identity by answering a password + challenge. The same holds for the SIP protocol [RFC3261] and many + instant messaging services operating over the Internet using + proprietary protocols. + + The username is directly observable if any of these protocols operate + in cleartext; the username can then be directly associated with the + source address. + +3.3.4. Retrieving IP addresses from mail headers + + SMTP [RFC5321] requires that each successive SMTP relay adds a + "Received" header to the mail headers. The purpose of these headers + is to enable audit of mail transmission, and perhaps to distinguish + between regular mail and spam. Here is an extract from the headers + of a message recently received from the "perpass" mailing list: + + "Received: from 192-000-002-044.zone13.example.org (HELO + ?192.168.1.100?) (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net + with ESMTPSA (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct + 2013 21:47:14 +0100 Message-ID: <526D7BD2.7070908@example.org> Date: + Sun, 27 Oct 2013 20:47:14 +0000 From: Some One + " + + + +Barnes, et al. Expires June 15, 2015 [Page 7] + +Internet-Draft Confidentiality Threat Model December 2014 + + + This is the first "Received" header attached to the message by the + first SMTP relay; for privacy reasons, the field values have been + anonymized. We learn here that the message was submitted by "Some + One" on October 27, from a host behind a NAT (192.168.1.100) + [RFC1918] that used the IP address 192.0.2.44. The information + remained in the message, and is accessible by all recipients of the + "perpass" mailing list, or indeed by any attacker that sees at least + one copy of the message. + + An attacker that can observe sufficient email traffic can regularly + update the mapping between public IP addresses and individual email + identities. Even if the SMTP traffic was encrypted on submission and + relaying, the attacker can still receive a copy of public mailing + lists like "perpass". + +3.3.5. Tracking address usage with web cookies + + Many web sites only encrypt a small fraction of their transactions. + A popular pattern is to use HTTPS for the login information, and then + use a "cookie" to associate following clear-text transactions with + the user's identity. Cookies are also used by various advertisement + services to quickly identify the users and serve them with + "personalized" advertisements. Such cookies are particularly useful + if the advertisement services want to keep tracking the user across + multiple sessions that may use different IP addresses. + + As cookies are sent in clear text, an attacker can build a database + that associates cookies to IP addresses for non-HTTPS traffic. If + the IP address is already identified, the cookie can be linked to the + user identify. After that, if the same cookie appears on a new IP + address, the new IP address can be immediately associated with the + pre-determined identity. + +3.3.6. Graph-based approaches to address correlation + + An attacker can track traffic from an IP address not yet associated + with an individual to various public services (e.g. websites, mail + servers, game servers), and exploit patterns in the observed traffic + to correlate this address with other addresses that show similar + patterns. For example, any two addresses that show connections to + the same IMAP or webmail services, the same set of favorite websites, + and game servers at similar times of day may be associated with the + same individual. Correlated addresses can then be tied to an + individual through one of the techniques above, walking the "network + graph" to expand the set of attributable traffic. + + + + + + +Barnes, et al. Expires June 15, 2015 [Page 8] + +Internet-Draft Confidentiality Threat Model December 2014 + + +3.3.7. Tracking of MAC Addresses + + Moving back down the stack, technologies like Ethernet or Wi-Fi use + MAC Addresses to identify link-level destinations. MAC Addresses + assigned according to IEEE-802 standards are unique to the device. + If the link is publicly accessible, an attacker can track it. For + example, the attacker can track the wireless traffic at public Wi-Fi + networks. Simple devices can monitor the traffic, and reveal which + MAC Addresses are present. If the network does not use some form of + Wi-Fi encryption, or if the attacker can access the decrypted + traffic, the analysis will also provide the correlation between MAC + Addresses and IP addresses. Additional monitoring using techniques + exposed in the previous sections will reveal the correlation between + MAC Addresses, IP Addresses, and user identity. The attacker can + conceivably build a database linking MAC Addresses and device or user + identities, and use it to track the movement of devices and of their + owners. + +4. Reported Instances of Large-Scale Attacks + + The situation in reality is more bleak than that suggested by an + analysis of our idealized attacker. Through revelations of sensitive + documents in several media outlets, the Internet community has been + made aware of several intelligence activities conducted by US and UK + national intelligence agencies, particularly the US National Security + Agency (NSA) and the UK Government Communications Headquarters + (GCHQ). These documents have revealed methods that these agencies + use to attack Internet applications and obtain sensitive user + information. + + First, they have confirmed that these agencies have capabilities in + line with those of our idealized attacker, thorugh the large-scale + passive collection of Internet traffic [pass1][pass2][pass3][pass4]. + For example: - The NSA XKEYSCORE system accesses data from multiple + access points and searches for "selectors" such as email addresses, + at the scale of tens of terabytes of data per day. - The GCHQ + Tempora system appears to have access to around 1,500 major cables + passing through the UK. - The NSA MUSCULAR program tapped cables + between data centers belonging to major service providers. - Several + programs appear to perform wide-scale collection of cookies in web + traffic and location data from location-aware portable devices such + as smartphones. + + However, the capabilities described go beyond those available to our + idealized attacker, including: + + o Decryption of TLS-protected Internet sessions [dec1][dec2][dec3]. + For example, the NSA BULLRUN project appears to have had a budget + + + +Barnes, et al. Expires June 15, 2015 [Page 9] + +Internet-Draft Confidentiality Threat Model December 2014 + + + of around $250M per year to undermine encryption through multiple + approaches. + + o Insertion of NSA devices as a man-in-the-middle of Internet + transactions [TOR1][TOR2]. For example, the NSA QUANTUM system + appears to use several different techniques to hijack HTTP + connections, ranging from DNS response injection to HTTP 302 + redirects. + + o Direct acquisition of bulk data and metadata from service + providers [dir1][dir2][dir3]. For example, the NSA PRISM program + provides the agency with access to many types of user data (e.g., + email, chat, VoIP). + + o Use of implants (covert modifications or malware) to undermine + security and anonymity features [dec2][TOR1][TOR2]. For example: + + * NSA appears to use the QUANTUM man-in-the-middle system to + direct users to a FOXACID server, which delivers an implant to + compromise the browser of a user of the Tor anonymous + communications network. + + * The BULLRUN program mentioned above includes the addition of + covert modifications to software as one means to undermine + encryption. + + * There is also some suspicion that NSA modifications to the + DUAL_EC_DRBG random number generator were made to ensure that + keys generated using that generator could be predicted by NSA. + These suspicions have been reinforced by reports that RSA + Security was paid roughly $10M to make DUAL_EC_DRBG the default + in their products. + + We use the term "pervasive attack" [RFC7258] to collectively describe + these operations. The term "pervasive" is used because the attacks + are designed to indiscriminately gather as much data as possible and + to apply selective analysis on targets after the fact. This means + that all, or nearly all, Internet communications are targets for + these attacks. To achieve this scale, the attacks are physically + pervasive; they affect a large number of Internet communications. + They are pervasive in content, consuming and exploiting any + information revealed by the protocol. And they are pervasive in + technology, exploiting many different vulnerabilities in many + different protocols. + + It's important to note that although the attacks mentioned above were + executed by NSA and GCHQ, there are many other organizations that can + mount pervasive surveillance attacks. Because of the resources + + + +Barnes, et al. Expires June 15, 2015 [Page 10] + +Internet-Draft Confidentiality Threat Model December 2014 + + + required to achieve pervasive scale, these attacks are most commonly + undertaken by nation-state actors. For example, the Chinese Internet + filtering system known as the "Great Firewall of China" uses several + techniques that are similar to the QUANTUM program, and which have a + high degree of pervasiveness with regard to the Internet in China. + +5. Threat Model + + Given these disclosures, we must consider a broader threat model. + + Pervasive surveillance aims to collect information across a large + number of Internet communications, analyzing the collected + communications to identify information of interest within individual + communications, or inferring information from correlated + communications. his analysis sometimes benefits from decryption of + encrypted communications and deanonymization of anonymized + communications. As a result, these attackers desire both access to + the bulk of Internet traffic and to the keying material required to + decrypt any traffic that has been encrypted. Even if keys are not + available, note that the presence of a communication and the fact + that it is encrypted may both be inputs to an analysis, even if the + attacker cannot decrypt the communication. + + The attacks listed above highlight new avenues both for access to + traffic and for access to relevant encryption keys. They further + indicate that the scale of surveillance is sufficient to provide a + general capability to cross-correlate communications, a threat not + previously thought to be relevant at the scale of the Internet. + +5.1. Attacker Capabilities + + +--------------------------+-------------------------------------+ + | Attack Class | Capability | + +--------------------------+-------------------------------------+ + | Passive observation | Directly capture data in transit | + | | | + | Passive inference | Infer from reduced/encrypted data | + | | | + | Active | Manipulate / inject data in transit | + | | | + | Static key exfiltration | Obtain key material once / rarely | + | | | + | Dynamic key exfiltration | Obtain per-session key material | + | | | + | Content exfiltration | Access data at rest | + +--------------------------+-------------------------------------+ + + + + + +Barnes, et al. Expires June 15, 2015 [Page 11] + +Internet-Draft Confidentiality Threat Model December 2014 + + + Security analyses of Internet protocols commonly consider two classes + of attacker: Passive attackers, who can simply listen in on + communications as they transit the network, and active attackers, who + can modify or delete packets in addition to simply collecting them. + + In the context of pervasive passive surveillance, these attacks take + on an even greater significance. In the past, these attackers were + often assumed to operate near the edge of the network, where attacks + can be simpler. For example, in some LANs, it is simple for any node + to engage in passive listening to other nodes' traffic or inject + packets to accomplish active attacks. However, as we now know, both + passive and active attacks are undertaken by pervasive attackers + closer to the core of the network, greatly expanding the scope and + capability of the attacker. + + Eavesdropping and observation at a larger scale make passive + inference attacks easier to carry out: a passive attacker with access + to a large portion of the Internet can analyze collected traffic to + create a much more detailed view of individual behavior than an + attacker that collects at a single point. Even the usual claim that + encryption defeats passive attackers is weakened, since a pervasive + passive attacker can infer relationships from correlations over large + numbers of sessions, e.g., pairing encrypted sessions with + unencrypted sessions from the same host, or performing traffic + fingerprinting between known and unknown encrypted sessions. Reports + on the NSA XKEYSCORE system would indicate it is an example of such + an attacker. + + A pervasive active attacker likewise has capabilities beyond those of + a localized active attacker. Active attacks are often limited by + network topology, for example by a requirement that the attacker be + able to see a targeted session as well as inject packets into it. A + pervasive active attacker with access at multiple points within the + core of the Internet is able to overcome these topological + limitations and perform attacks over a much broader scope. Being + positioned in the core of the network rather than the edge can also + enable a pervasive active attacker to reroute targeted traffic, + amplifying the ability to perform both eavesdropping and traffic + injection. Pervasive active attackers can also benefit from + pervasive passive collection to identify vulnerable hosts. + + While not directly related to pervasiveness, attackers that are in a + position to mount a pervasive active attack are also often in a + position to subvert authentication, a traditional protection against + such attacks. Authentication in the Internet is often achieved via + trusted third party authorities such as the Certificate Authorities + (CAs) that provide web sites with authentication credentials. An + attacker with sufficient resources may also be able to induce an + + + +Barnes, et al. Expires June 15, 2015 [Page 12] + +Internet-Draft Confidentiality Threat Model December 2014 + + + authority to grant credentials for an identity of the attacker's + choosing. If the parties to a communication will trust multiple + authorities to certify a specific identity, this attack may be + mounted by suborning any one of the authorities (the proverbial + "weakest link"). Subversion of authorities in this way can allow an + active attack to succeed in spite of an authentication check. + + Beyond these three classes (observation, inference, and active), + reports on the BULLRUN effort to defeat encryption and the PRISM + effort to obtain data from service providers suggest three more + classes of attack: + + o Static key exfiltration + + o Dynamic key exfiltration + + o Content exfiltration + + These attacks all rely on a collaborator providing the attacker with + some information, either keys or data. These attacks have not + traditionally been considered in security analyses of protocols, + since they happen outside of the protocol. + + The term "key exfiltration" refers to the transfer of keying material + for an encrypted communication from the collaborator to the attacker. + By "static", we mean that the transfer of keys happens once, or + rarely, typically of a long-lived key. For example, this case would + cover a web site operator that provides the private key corresponding + to its HTTPS certificate to an intelligence agency. + + "Dynamic" key exfiltration, by contrast, refers to attacks in which + the collaborator delivers keying material to the attacker frequently, + e.g., on a per-session basis. This does not necessarily imply + frequent communications with the attacker; the transfer of keying + material may be virtual. For example, if an endpoint were modified + in such a way that the attacker could predict the state of its + psuedorandom number generator, then the attacker would be able to + derive per-session keys even without per-session communications. + + Finally, content exfiltration is the attack in which the collaborator + simply provides the attacker with the desired data or metadata. + Unlike the key exfiltration cases, this attack does not require the + attacker to capture the desired data as it flows through the network. + The risk is to data at rest as opposed to data in transit. This + increases the scope of data that the attacker can obtain, since the + attacker can access historical data - the attacker does not have to + be listening at the time the communication happens. + + + + +Barnes, et al. Expires June 15, 2015 [Page 13] + +Internet-Draft Confidentiality Threat Model December 2014 + + + Exfiltration attacks can be accomplished via attacks against one of + the parties to a communication, i.e., by the attacker stealing the + keys or content rather than the party providing them willingly. In + these cases, the party may not be aware that they are collaborating, + at least at a human level. Rather, the subverted technical assets + are "collaborating" with the attacker (by providing keys/content) + without their owner's knowledge or consent. + + Any party that has access to encryption keys or unencrypted data can + be a collaborator. While collaborators are typically the endpoints + of a communication (with encryption securing the links), + intermediaries in an unencrypted communication can also facilitate + content exfiltration attacks as collaborators by providing the + attacker access to those communications. For example, documents + describing the NSA PRISM program claim that NSA is able to access + user data directly from servers, where it is stored unencrypted. In + these cases, the operator of the server would be a collaborator, if + an unwitting one. By contrast, in the NSA MUSCULAR program, a set of + collaborators enabled attackers to access the cables connecting data + centers used by service providers such as Google and Yahoo. Because + communications among these data centers were not encrypted, the + collaboration by an intermediate entity allowed NSA to collect + unencrypted user data. + +5.2. Attacker Costs + + +--------------------------+-----------------------------------+ + | Attack Class | Cost / Risk to Attacker | + +--------------------------+-----------------------------------+ + | Passive observation | Passive data access | + | | | + | Passive inference | Passive data access + processing | + | | | + | Active | Active data access + processing | + | | | + | Static key exfiltration | One-time interaction | + | | | + | Dynamic key exfiltration | Ongoing interaction / code change | + | | | + | Content exfiltration | Ongoing, bulk interaction | + +--------------------------+-----------------------------------+ + + Each of the attack types discussed in the previous section entails + certain costs and risks. These costs differ by attack, and can be + helpful in guiding response to pervasive attack. + + Depending on the attack, the attacker may be exposed to several types + of risk, ranging from simply losing access to arrest or prosecution. + + + +Barnes, et al. Expires June 15, 2015 [Page 14] + +Internet-Draft Confidentiality Threat Model December 2014 + + + In order for any of these negative consequences to occur, however, + the attacker must first be discovered and identified. So the primary + risk we focus on here is the risk of discovery and attribution. + + A passive attack is the simplest to mount in some ways. The base + requirement is that the attacker obtain physical access to a + communications medium and extract communications from it. For + example, the attacker might tap a fiber-optic cable, acquire a mirror + port on a switch, or listen to a wireless signal. The need for these + taps to have physical access or proximity to a link exposes the + attacker to the risk that the taps will be discovered. For example, + a fiber tap or mirror port might be discovered by network operators + noticing increased attenuation in the fiber or a change in switch + configuration. Of course, passive attacks may be accomplished with + the cooperation of the network operator, in which case there is a + risk that the attacker's interactions with the network operator will + be exposed. + + In many ways, the costs and risks for an active attack are similar to + those for a passive attack, with a few additions. An active attacker + requires more robust network access than a passive attacker, since + for example they will often need to transmit data as well as + receiving it. In the wireless example above, the attacker would need + to act as an transmitter as well as receiver, greatly increasing the + probability the attacker will be discovered (e.g., using direction- + finding technology). Active attacks are also much more observable at + higher layers of the network. For example, an active attacker that + attempts to use a mis-issued certificate could be detected via + Certificate Transparency [RFC6962]. + + In terms of raw implementation complexity, passive attacks require + only enough processing to extract information from the network and + store it. Active attacks, by contrast, often depend on winning race + conditions to inject pakets into active connections. So active + attacks in the core of the network require processing hardware to + that can operate at line speed (roughly 100Gbps to 1Tbps in the core) + to identify opportunities for attack and insert attack traffic in a + high-volume traffic. + Key exfiltration attacks rely on passive attack for access to + encrypted data, with the collaborator providing keys to decrypt the + data. So the attacker undertakes the cost and risk of a passive + attack, as well as additional risk of discovery via the interactions + that the attacker has with the collaborator. + + In this sense, static exfiltration has a lower risk profile than + dynamic. In the static case, the attacker need only interact with + the collaborator a small number of times, possibly only once, say to + exchange a private key. In the dynamic case, the attacker must have + + + +Barnes, et al. Expires June 15, 2015 [Page 15] + +Internet-Draft Confidentiality Threat Model December 2014 + + + continuing interactions with the collaborator. As noted above these + interactions may real, such as in-person meetings, or virtual, such + as software modifications that render keys available to the attacker. + Both of these types of interactions introduce a risk that they will + be discovered, e.g., by employees of the collaborator organization + noticing suspicious meetings or suspicious code changes. + + Content exfiltration has a similar risk profile to dynamic key + exfiltration. In a content exfiltration attack, the attacker saves + the cost and risk of conducting a passive attack. The risk of + discovery through interactions with the collaborator, however, is + still present, and may be higher. The content of a communication is + obviously larger than the key used to encrypt it, often by several + orders of magnitude. So in the content exfiltration case, the + interactions between the collaborator and the attacker need to be + much higher-bandwidth than in the key exfiltration cases, with a + corresponding increase in the risk that this high-bandwidth channel + will be discovered. + + It should also be noted that in these latter three exfiltration + cases, the collaborator also undertakes a risk that his collaboration + with the attacker will be discovered. Thus the attacker may have to + incur additional cost in order to convince the collaborator to + participate in the attack. Likewise, the scope of these attacks is + limited to case where the attacker can convince a collaborator to + participate. If the attacker is a national government, for example, + it may be able to compel participation within its borders, but have a + much more difficult time recruiting foreign collaborators. + + As noted above, the collaborator in an exfiltration attack can be + unwitting; the attacker can steal keys or data to enable the attack. + In some ways, the risks of this approach are similar to the case of + an active collaborator. In the static case, the attacker needs to + steal information from the collaborator once; in the dynamic case, + the attacker needs to continued presence inside the collaborators + systems. The main difference is that the risk in this case is of + automated discovery (e.g., by intrusion detection systems) rather + than discovery by humans. + +6. Security Considerations + + This document describes a threat model for pervasive surveillance + attacks. Mitigations are to be given in a future document. + + + + + + + + +Barnes, et al. Expires June 15, 2015 [Page 16] + +Internet-Draft Confidentiality Threat Model December 2014 + + +7. IANA Considerations + + This document has no actions for IANA. + +8. Acknowledgements + + Thanks to Dave Thaler for the list of attacks and taxonomy; to + Security Area Directors Stephen Farrell, Sean Turner, and Kathleen + Moriarty for starting and managing the IETF's discussion on pervasive + attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, and + Evangelos Halepilidis, and to the membership of the IAB Privacy and + Security Program for their input. + +9. References + +9.1. Normative References + + [RFC6973] Cooper, A., Tschofenig, H., Aboba, B., Peterson, J., + Morris, J., Hansen, M., and R. Smith, "Privacy + Considerations for Internet Protocols", RFC 6973, July + 2013. + +9.2. Informative References + + [pass1] The Guardian, "How the NSA is still harvesting your online + data", 2013, + . + + [pass2] The Guardian, "NSA's Prism surveillance program: how it + works and what it can do", 2013, + . + + [pass3] The Guardian, "XKeyscore: NSA tool collects 'nearly + everything a user does on the internet'", 2013, + . + + [pass4] The Guardian, "How does GCHQ's internet surveillance + work?", n.d., . + + [dec1] The New York Times, "N.S.A. Able to Foil Basic Safeguards + of Privacy on Web", 2013, + . + + + + +Barnes, et al. Expires June 15, 2015 [Page 17] + +Internet-Draft Confidentiality Threat Model December 2014 + + + [dec2] The Guardian, "Project Bullrun - classification guide to + the NSA's decryption program", 2013, + . + + [dec3] The Guardian, "Revealed: how US and UK spy agencies defeat + internet privacy and security", 2013, + . + + [TOR] The Tor Project, "Tor", 2013, + . + + [TOR1] Schneier, B., "How the NSA Attacks Tor/Firefox Users With + QUANTUM and FOXACID", 2013, + . + + [TOR2] The Guardian, "'Tor Stinks' presentation - read the full + document", 2013, + . + + [dir1] The Guardian, "NSA collecting phone records of millions of + Verizon customers daily", 2013, + . + + [dir2] The Guardian, "NSA Prism program taps in to user data of + Apple, Google and others", 2013, + . + + [dir3] The Guardian, "Sigint - how the NSA collaborates with + technology companies", 2013, + . + + [secure] Schneier, B., "NSA surveillance: A guide to staying + secure", 2013, + . + + [snowden] Technology Review, "NSA Leak Leaves Crypto-Math Intact but + Highlights Known Workarounds", 2013, + . + + + +Barnes, et al. Expires June 15, 2015 [Page 18] + +Internet-Draft Confidentiality Threat Model December 2014 + + + [key-recovery] + Golle, P., "The Design and Implementation of Protocol- + Based Hidden Key Recovery", 2003, + . + + [RFC1035] Mockapetris, P., "Domain names - implementation and + specification", STD 13, RFC 1035, November 1987. + + [RFC1918] Rekhter, Y., Moskowitz, R., Karrenberg, D., Groot, G., and + E. Lear, "Address Allocation for Private Internets", BCP + 5, RFC 1918, February 1996. + + [RFC1939] Myers, J. and M. Rose, "Post Office Protocol - Version 3", + STD 53, RFC 1939, May 1996. + + [RFC2015] Elkins, M., "MIME Security with Pretty Good Privacy + (PGP)", RFC 2015, October 1996. + + [RFC2821] Klensin, J., "Simple Mail Transfer Protocol", RFC 2821, + April 2001. + + [RFC3261] Rosenberg, J., Schulzrinne, H., Camarillo, G., Johnston, + A., Peterson, J., Sparks, R., Handley, M., and E. + Schooler, "SIP: Session Initiation Protocol", RFC 3261, + June 2002. + + [RFC3365] Schiller, J., "Strong Security Requirements for Internet + Engineering Task Force Standard Protocols", BCP 61, RFC + 3365, August 2002. + + [RFC3501] Crispin, M., "INTERNET MESSAGE ACCESS PROTOCOL - VERSION + 4rev1", RFC 3501, March 2003. + + [RFC3851] Ramsdell, B., "Secure/Multipurpose Internet Mail + Extensions (S/MIME) Version 3.1 Message Specification", + RFC 3851, July 2004. + + [RFC4033] Arends, R., Austein, R., Larson, M., Massey, D., and S. + Rose, "DNS Security Introduction and Requirements", RFC + 4033, March 2005. + + [RFC4301] Kent, S. and K. Seo, "Security Architecture for the + Internet Protocol", RFC 4301, December 2005. + + [RFC4303] Kent, S., "IP Encapsulating Security Payload (ESP)", RFC + 4303, December 2005. + + + + + +Barnes, et al. Expires June 15, 2015 [Page 19] + +Internet-Draft Confidentiality Threat Model December 2014 + + + [RFC4306] Kaufman, C., "Internet Key Exchange (IKEv2) Protocol", RFC + 4306, December 2005. + + [RFC4949] Shirey, R., "Internet Security Glossary, Version 2", RFC + 4949, August 2007. + + [RFC5246] Dierks, T. and E. Rescorla, "The Transport Layer Security + (TLS) Protocol Version 1.2", RFC 5246, August 2008. + + [RFC5321] Klensin, J., "Simple Mail Transfer Protocol", RFC 5321, + October 2008. + + [RFC5655] Trammell, B., Boschi, E., Mark, L., Zseby, T., and A. + Wagner, "Specification of the IP Flow Information Export + (IPFIX) File Format", RFC 5655, October 2009. + + [RFC5750] Ramsdell, B. and S. Turner, "Secure/Multipurpose Internet + Mail Extensions (S/MIME) Version 3.2 Certificate + Handling", RFC 5750, January 2010. + + [RFC6120] Saint-Andre, P., "Extensible Messaging and Presence + Protocol (XMPP): Core", RFC 6120, March 2011. + + [RFC6962] Laurie, B., Langley, A., and E. Kasper, "Certificate + Transparency", RFC 6962, June 2013. + + [RFC6698] Hoffman, P. and J. Schlyter, "The DNS-Based Authentication + of Named Entities (DANE) Transport Layer Security (TLS) + Protocol: TLSA", RFC 6698, August 2012. + + [RFC7011] Claise, B., Trammell, B., and P. Aitken, "Specification of + the IP Flow Information Export (IPFIX) Protocol for the + Exchange of Flow Information", STD 77, RFC 7011, September + 2013. + + [RFC7258] Farrell, S. and H. Tschofenig, "Pervasive Monitoring Is an + Attack", BCP 188, RFC 7258, May 2014. + +Authors' Addresses + + Richard Barnes + + Email: rlb@ipv.sx + + + Bruce Schneier + + Email: schneier@schneier.com + + + +Barnes, et al. Expires June 15, 2015 [Page 20] + +Internet-Draft Confidentiality Threat Model December 2014 + + + Cullen Jennings + + Email: fluffy@cisco.com + + + Ted Hardie + + Email: ted.ietf@gmail.com + + + Brian Trammell + + Email: ietf@trammell.ch + + + Christian Huitema + + Email: huitema@huitema.net + + + Daniel Borkmann + + Email: dborkman@redhat.com + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Barnes, et al. Expires June 15, 2015 [Page 21] diff --git a/draft-iab-privsec-confidentiality-threat-01.xml b/draft-iab-privsec-confidentiality-threat-01.xml new file mode 100644 index 0000000..7210d78 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-01.xml @@ -0,0 +1,563 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +]> + + + + + + Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement + + + +
+ rlb@ipv.sx +
+ + + +
+ schneier@schneier.com +
+ + + +
+ fluffy@cisco.com +
+ + + +
+ ted.ietf@gmail.com +
+ + + +
+ ietf@trammell.ch +
+ + + +
+ huitema@huitema.net +
+ + + +
+ dborkman@redhat.com +
+ + + + + + + + + + + +Documents published in 2013 revealed several classes of pervasive surveillance attack on Internet communications. In this document we develop a threat model that describes these pervasive attacks. We start by assuming a completely passive attacker with an interest in undetected, indiscriminate eavesdropping, then expand the threat model with a set of verified attacks that have been published. Based on this threat model, we discuss the techniques that can be employed in Internet protocol design to increase the protocols robustness to pervasive surveillance. + + + + + + + + + + + +
+ +Starting in June 2013, documents released to the press by Edward Snowden have revealed several operations undertaken by intelligence agencies to exploit Internet communications for intelligence purposes. These attacks were largely based on protocol vulnerabilities that were already known to exist. The attacks were nonetheless striking in their pervasive nature, both in terms of the amount of Internet communications targeted, and in terms of the diversity of attack techniques employed. + +To ensure that the Internet can be trusted by users, it is necessary for the Internet technical community to address the vulnerabilities exploited in these attacks . The goal of this document is to describe more precisely the threats posed by these pervasive attacks, and based on those threats, lay out the problems that need to be solved in order to secure the Internet in the face of those threats. + +The remainder of this document is structured as follows. In , we describe an idealized passive attacket, one which could completely undetectably compromise communications at Internet scale. In , we provide a brief summary of some attacks that have been disclosed, and use these to expand the assumed capabilities of our idealized attacker. describes a threat model based on these attacks, focusing on classes of attack that have not been a focus of Internet engineering to date. + +
+
+ +This document makes extensive use of standard security and privacy terminology; see and . Terms used from include Eavesdropper, Observer, Initiator, Intermediary, Recipient, Attack (in a privacy context), Correlation, Fingerprint, Traffic Analysis, and Identifiability (and related terms). In addition, we use a few terms that are specific to the attacks discussed here: + + + + An attack on Internet communications that makes use of access at a large number of points in the network, or otherwise provides the attacker with access to a large amount of Internet traffic; see + + Information collected directly from communications by an eavesdropper or observer. For example, the knowledge that <alice@example.com> sent a message to <bob@example.com> via SMTP taken from the headers of an observed SMTP message would be an observation. + + Information extracted from analysis of information collected directly from communications by an eavesdropper or observer. For example, the knowledge that a given web page was accessed by a given IP address, by comparing the size in octets of measured network flow records to fingerprints derived from known sizes of linked resources on the web servers involved, would be an +inference. + + An entity that is a legitimate participant in a communication, but who provides information about that interaction (keys or data) to an attacker. + + A collaborator that provides information to the attacker not deliberately, but because the attacker has exploited some technology used by the collaborator. + + The transmission of keying material for an encrypted communication from a collaborator to an attacker + + The transmission of the content of a communication from a collaborator to an attacker + + +
+
+ +To build a thread model, we first assume a pervasive passive attacker, an indiscriminate eavesdropper on an Internet-attached computer network that + + + can observe every packet of all communications at any or every hop in any network path between an initiator and a recipient; and + can observe data at rest in intermediate systems between the endpoints controlled by the initiator and recipient; but + takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.). + + +This attacker is less capable than those which we know to have compromised the Internet from press reports, elaborated in , but represents the threat to communications privacy by a single eavesdropper interested in remaining undetectable. + +The techniques available to our ideal attacker are direct observation and inference. Direct observation involves taking information directly from eavesdropped communications - e.g., URLs identifying content or email addresses identifying individuals from application-layer headers. Inference, on the other hand, involves analyzing eavesdropped information to derive new information from it; e.g., searching for application or behavioral fingerprints in observed traffic to derive information about the observed individual from them, in absence of directly-observed sources of the same information. The use of encryption to protect confidentiality is generally enough to prevent direct observation, assuming uncompromised encryption implementations and key material, but provides less complete protection against inference, especially inference based only on unprotected portions of communications (e.g. IP and TCP headers for TLS ). + +
+ +Protocols which do not encrypt their payload make the entire content of the communication available to the idealized attacker along their path. Following the advice in , most such protocols have a secure variant which encrypts payload for confidentiality, and these secure variants are seeing ever-wider deployment. A noteworthy exception is DNS , as DNSSEC does not have confidentiality as a requirement. This implies that all DNS queries and answers generated by the activities of any protocol are available to the attacker. + +Protocols which imply the storage of some data at rest in intermediaries (e.g. SMTP ) leave this data subject to observation by an attacker that has compromised these intermediaries, unless the data is encrypted end-to-end by the application layer protocol, or the implementation uses an encrypted store for this data. + +
+
+ +Inference is information extracted from later analysis of an observed or eavesdropped communication, and/or correlation of observed or eavesdropped information with information available from other sources. Indeed, most useful inference performed by the attacker falls under the rubric of correlation. The simplest example of this is the observation of DNS queries and answers from and to a source and correlating those with IP addresses with which that source communicates. This can give access to information otherwise not available from encrypted application payloads (e.g., the Host: HTTP/1.1 request header when HTTP is used with TLS). + +Protocols which encrypt their payload using an application- or transport-layer encryption scheme (e.g. TLS) still expose all the information in their network and transport layer headers to the attacker, including source and destination addresses and ports. IPsec ESP further encrypts the transport-layer headers, but still leaves IP address information unencrypted; in tunnel mode, these addresses correspond to the tunnel endpoints. Features of the cryptographic protocols themselves, e.g. the TLS session identifier, may leak information that can be used for correlation and inference. While this information is much less semantically rich than the application payload, it can still be useful for the inferring an individual’s activities. + +Inference can also leverage information obtained from sources other than direct traffic observation. Geolocation databases, for example, have been developed map IP addresses to a location, in order to provide location-aware services such as targeted advertising. This location information is often of sufficient resolution that it can be used to draw further inferences toward identifying or profiling an individual. + +Social media provide another source of more or less publicly accessible information. This information can be extremely semantically rich, including information about an individual’s location, associations with other individuals and groups, and activities. Further, this information is generally contributed and curated voluntarily by the individuals themselves: it represents information which the individuals are not necessarily interested in protecting for privascy reasons. However, correlation of this social networking data with information available from direct observation of network traffic allows the creation of a much richer picture of an individual’s activities than either alone. We note with some alarm that there is little that can be done at protocol design time to limit such correlation by the attacker, and that the existence of such data sources in many cases greatly complicates the problem of protecting privacy by hardening protocols alone. + +
+
+ +To illustrate how capable the attacker is even given its limitations, we explore the non-anonymity of even encrypted IP traffic by examining in detail some inference techniques for associating a set of addresses with an individual, in order to illustrate the difficulty of defending communications against our idealized attacker. Here, the basic problem is that information radiated even from protocols which have no obvious connection with personal data can be correlated with other information which can paint a very rich behavioral picture, that only takes one unprotected link in the chain to associate with an identity. + +
+ +Internet traffic can be monitored by tapping Internet links, or by installing monitoring tools in Internet routers. Of course, a single link or a single router only provides access to a fraction of the global Internet traffic. However, monitoring a number of high capacity links or a set of routers placed at strategic locations provides access to a good sampling of Internet traffic. + +Tools like IPFIX allow administrators to acquire statistics about sequences of packets with some common properties that pass through a network device. The most common set of properties used in flow measurement is the “five-tuple”of source and destination addresses, protocol type, and source and destination ports. These statistics are commonly used for network engineering, but could certainly be used for other purposes. + +Let’s assume for a moment that IP addresses can be correlated to specific services or specific users. Analysis of the sequences of packets will quickly reveal which users use what services, and also which users engage in peer-to-peer connections with other users. Analysis of traffic variations over time can be used to detect increased activity by particular users, or in the case of peer-to-peer connections increased activity within groups of users. + +
+
+ +The correlation of IP addresses with specific users can be done in various ways. For example, tools like reverse DNS lookup can be used to retrieve the DNS names of servers. Since the addresses of servers tend to be quite stable and since servers are relatively less numerous than users, an attacker could easily maintain its own copy of the DNS for well-known or popular servers, to accelerate such lookups. + +On the other hand, the reverse lookup of IP addresses of users is generally less informative. For example, a lookup of the address currently used by one author’s home network returns a name of the form “c-192-000-002-033.hsd1.wa.comcast.net”. This particular type of reverse DNS lookup generally reveals only coarse-grained location or provider information. + +In many jurisdictions, Internet Service Providers (ISPs) are required to provide identification on a case by case basis of the “owner” of a specific IP address for law enforcement purposes. This is a reasonably expedient process for targeted investigations, but pervasive surveillance requires something more efficient. This provides an incentive for the attacker to secure the cooperation of the ISP in order to automate this correlation. + +
+
+ +Even if the ISP does not cooperate, user identity can often be obtained via inference. POP3 and IMAP are used to retrieve mail from mail servers, while a variant of SMTP is used to submit messages through mail servers. IMAP connections originate from the client, and typically start with an authentication exchange in which the client proves its identity by answering a password challenge. The same holds for the SIP protocol and many instant messaging services operating over the Internet using proprietary protocols. + +The username is directly observable if any of these protocols operate in cleartext; the username can then be directly associated with the source address. + +
+
+ +SMTP requires that each successive SMTP relay adds a “Received” header to the mail headers. The purpose of these headers is to enable audit of mail transmission, and perhaps to distinguish between regular mail and spam. Here is an extract from the headers of a message recently received from the “perpass” mailing list: + + + Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?) + (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA + (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100 + Message-ID: <526D7BD2.7070908@example.org> + Date: Sun, 27 Oct 2013 20:47:14 +0000 + From: Some One <some.one@example.org> + + +This is the first “Received” header attached to the message by the first SMTP relay; for privacy reasons, the field values have been anonymized. We learn here that the message was submitted by “Some One” on October 27, from a host behind a NAT (192.168.1.100) that used the IP address 192.0.2.44. The information remained in the message, and is accessible by all recipients of the “perpass” mailing list, or indeed by any attacker that sees at least one copy of the message. + +An attacker that can observe sufficient email traffic can regularly update the mapping between public IP addresses and individual email identities. Even if the SMTP traffic was encrypted on submission and relaying, the attacker can still receive a copy of public mailing lists like “perpass”. + +
+
+ +Many web sites only encrypt a small fraction of their transactions. A popular pattern is to use HTTPS for the login information, and then use a “cookie” to associate following clear-text transactions with the user’s identity. Cookies are also used by various advertisement services to quickly identify the users and serve them with “personalized” advertisements. Such cookies are particularly useful if the advertisement services want to keep tracking the user across multiple sessions that may use different IP addresses. + +As cookies are sent in clear text, an attacker can build a database that associates cookies to IP addresses for non-HTTPS traffic. If the IP address is already identified, the cookie can be linked to the user identify. After that, if the same cookie appears on a new IP address, the new IP address can be immediately associated with the pre-determined identity. + +
+
+ +An attacker can track traffic from an IP address not yet associated with an individual to various public services (e.g. websites, mail servers, game servers), and exploit patterns in the observed traffic to correlate this address with other addresses that show similar patterns. For example, any two addresses that show connections to the same IMAP or webmail services, the same set of favorite websites, and game servers at similar times of day may be associated with the same individual. Correlated addresses can then be tied to an individual through one of the techniques above, walking the “network graph” to expand the set of attributable traffic. + +
+
+ +Moving back down the stack, technologies like Ethernet or Wi-Fi use MAC Addresses to identify link-level destinations. MAC Addresses assigned according to IEEE-802 standards are unique to the device. If the link is publicly accessible, an attacker can track it. For example, the attacker can track the wireless traffic at public Wi-Fi networks. Simple devices can monitor the traffic, and reveal which MAC Addresses are present. If the network does not use some form of Wi-Fi encryption, or if the attacker can access the decrypted traffic, the analysis will also provide the correlation between MAC Addresses and IP addresses. Additional monitoring using techniques exposed in the previous sections will reveal the correlation between MAC Addresses, IP Addresses, and user identity. The attacker can conceivably build a database linking MAC Addresses and device or user identities, and use it to track the movement of devices and of their owners. + +
+
+
+
+ +The situation in reality is more bleak than that suggested by an analysis of our idealized attacker. Through revelations of sensitive documents in several media outlets, the Internet community has been made aware of several intelligence activities conducted by US and UK national intelligence agencies, particularly the US National Security Agency (NSA) and the UK Government Communications Headquarters (GCHQ). These documents have revealed methods that these agencies use to attack Internet applications and obtain sensitive user information. + +First, they have confirmed that these agencies have capabilities in line with those of our idealized attacker, thorugh the large-scale passive collection of Internet traffic . For example: + - The NSA XKEYSCORE system accesses data from multiple access points and searches for “selectors” such as email addresses, at the scale of tens of terabytes of data per day. + - The GCHQ Tempora system appears to have access to around 1,500 major cables passing through the UK. + - The NSA MUSCULAR program tapped cables between data centers belonging to major service providers. + - Several programs appear to perform wide-scale collection of cookies in web traffic and location data from location-aware portable devices such as smartphones. + +However, the capabilities described go beyond those available to our idealized attacker, including: + + + Decryption of TLS-protected Internet sessions . For example, the NSA BULLRUN project appears to have had a budget of around $250M per year to undermine encryption through multiple approaches. + Insertion of NSA devices as a man-in-the-middle of Internet transactions . For example, the NSA QUANTUM system appears to use several different techniques to hijack HTTP connections, ranging from DNS response injection to HTTP 302 redirects. + Direct acquisition of bulk data and metadata from service providers . For example, the NSA PRISM program provides the agency with access to many types of user data (e.g., email, chat, VoIP). + Use of implants (covert modifications or malware) to undermine security and anonymity features . For example: + NSA appears to use the QUANTUM man-in-the-middle system to direct users to a FOXACID server, which delivers an implant to compromise the browser of a user of the Tor anonymous communications network. + The BULLRUN program mentioned above includes the addition of covert modifications to software as one means to undermine encryption. + There is also some suspicion that NSA modifications to the DUAL_EC_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA. These suspicions have been reinforced by reports that RSA Security was paid roughly $10M to make DUAL_EC_DRBG the default in their products. + + + +We use the term “pervasive attack” to collectively describe these operations. The term “pervasive” is used because the attacks are designed to indiscriminately gather as much data as possible and to apply selective analysis on targets after the fact. This means that all, or nearly all, Internet communications are targets for these attacks. To achieve this scale, the attacks are physically pervasive; they affect a large number of Internet communications. They are pervasive in content, consuming and exploiting any information revealed by the protocol. And they are pervasive in technology, exploiting many different vulnerabilities in many different protocols. + +It’s important to note that although the attacks mentioned above were executed by NSA and GCHQ, there are many other organizations that can mount pervasive surveillance attacks. Because of the resources required to achieve pervasive scale, these attacks are most commonly undertaken by nation-state actors. For example, the Chinese Internet filtering system known as the “Great Firewall of China” uses several techniques that are similar to the QUANTUM program, and which have a high degree of pervasiveness with regard to the Internet in China. + +
+
+ +Given these disclosures, we must consider a broader threat model. + +Pervasive surveillance aims to collect information across a large number of Internet communications, analyzing the collected communications to identify information of interest within individual communications, or inferring information from correlated communications. his analysis sometimes benefits from decryption of encrypted communications and deanonymization of anonymized communications. As a result, these attackers desire both access to the bulk of Internet traffic and to the keying material required to decrypt any traffic that has been encrypted. Even if keys are not available, note that the presence of a communication and the fact that it is encrypted may both be inputs to an analysis, even if the attacker cannot decrypt the communication. + +The attacks listed above highlight new avenues both for access to traffic and for access to relevant encryption keys. They further indicate that the scale of surveillance is sufficient to provide a general capability to cross-correlate communications, a threat not previously thought to be relevant at the scale of the Internet. + +
+ + + Attack Class + Capability + Passive observation + Directly capture data in transit + Passive inference + Infer from reduced/encrypted data + Active + Manipulate / inject data in transit + Static key exfiltration + Obtain key material once / rarely + Dynamic key exfiltration + Obtain per-session key material + Content exfiltration + Access data at rest + + +Security analyses of Internet protocols commonly consider two classes of attacker: Passive attackers, who can simply listen in on communications as they transit the network, and active attackers, who can modify or delete packets in addition to simply collecting them. + +In the context of pervasive passive surveillance, these attacks take on an even greater significance. In the past, these attackers were often assumed to operate near the edge of the network, where attacks can be simpler. For example, in some LANs, it is simple for any node to engage in passive listening to other nodes’ traffic or inject packets to accomplish active attacks. However, as we now know, both passive and active attacks are undertaken by pervasive attackers closer to the core of the network, greatly expanding the scope and capability of the attacker. + +Eavesdropping and observation at a larger scale make passive inference attacks easier to carry out: a passive attacker with access to a large portion of the Internet can analyze collected traffic to create a much more detailed view of individual behavior than an attacker that collects at a single point. Even the usual claim that encryption defeats passive attackers is weakened, since a pervasive passive attacker can infer relationships from correlations over large numbers of sessions, e.g., pairing encrypted sessions with unencrypted sessions from the same host, or performing traffic fingerprinting between known and unknown encrypted sessions. Reports on the NSA XKEYSCORE system would indicate it is an example of such an attacker. + +A pervasive active attacker likewise has capabilities beyond those of a localized active attacker. Active attacks are often limited by network topology, for example by a requirement that the attacker be able to see a targeted session as well as inject packets into it. A pervasive active attacker with access at multiple points within the core of the Internet is able to overcome these topological limitations and perform attacks over a much broader scope. Being positioned in the core of the network rather than the edge can also enable a pervasive active attacker to reroute targeted traffic, amplifying the ability to perform both eavesdropping and traffic injection. Pervasive active attackers can also benefit from pervasive passive collection to identify vulnerable hosts. + +While not directly related to pervasiveness, attackers that are in a position to mount a pervasive active attack are also often in a position to subvert authentication, a traditional protection against such attacks. Authentication in the Internet is often achieved via trusted third party authorities such as the Certificate Authorities (CAs) that provide web sites with authentication credentials. An attacker with sufficient resources may also be able to induce an authority to grant credentials for an identity of the attacker’s choosing. If the parties to a communication will trust multiple authorities to certify a specific identity, this attack may be mounted by suborning any one of the authorities (the proverbial “weakest link”). Subversion of authorities in this way can allow an active attack to succeed in spite of an authentication check. + +Beyond these three classes (observation, inference, and active), reports on the BULLRUN effort to defeat encryption and the PRISM effort to obtain data from service providers suggest three more classes of attack: + + + Static key exfiltration + Dynamic key exfiltration + Content exfiltration + + +These attacks all rely on a collaborator providing the attacker with some information, either keys or data. These attacks have not traditionally been considered in security analyses of protocols, since they happen outside of the protocol. + +The term “key exfiltration” refers to the transfer of keying material for an encrypted communication from the collaborator to the attacker. By “static”, we mean that the transfer of keys happens once, or rarely, typically of a long-lived key. For example, this case would cover a web site operator that provides the private key corresponding to its HTTPS certificate to an intelligence agency. + +“Dynamic” key exfiltration, by contrast, refers to attacks in which the collaborator delivers keying material to the attacker frequently, e.g., on a per-session basis. This does not necessarily imply frequent communications with the attacker; the transfer of keying material may be virtual. For example, if an endpoint were modified in such a way that the attacker could predict the state of its psuedorandom number generator, then the attacker would be able to derive per-session keys even without per-session communications. + +Finally, content exfiltration is the attack in which the collaborator simply provides the attacker with the desired data or metadata. Unlike the key exfiltration cases, this attack does not require the attacker to capture the desired data as it flows through the network. The risk is to data at rest as opposed to data in transit. This increases the scope of data that the attacker can obtain, since the attacker can access historical data – the attacker does not have to be listening at the time the communication happens. + +Exfiltration attacks can be accomplished via attacks against one of the parties to a communication, i.e., by the attacker stealing the keys or content rather than the party providing them willingly. In these cases, the party may not be aware that they are collaborating, at least at a human level. Rather, the subverted technical assets are “collaborating” with the attacker (by providing keys/content) without their owner’s knowledge or consent. + +Any party that has access to encryption keys or unencrypted data can be a collaborator. While collaborators are typically the endpoints of a communication (with encryption securing the links), intermediaries in an unencrypted communication can also facilitate content exfiltration attacks as collaborators by providing the attacker access to those communications. For example, documents describing the NSA PRISM program claim that NSA is able to access user data directly from servers, where it is stored unencrypted. In these cases, the operator of the server would be a collaborator, if an unwitting one. By contrast, in the NSA MUSCULAR program, a set of collaborators enabled attackers to access the cables connecting data centers used by service providers such as Google and Yahoo. Because communications among these data centers were not encrypted, the collaboration by an intermediate entity allowed NSA to collect unencrypted user data. + +
+
+ + + Attack Class + Cost / Risk to Attacker + Passive observation + Passive data access + Passive inference + Passive data access + processing + Active + Active data access + processing + Static key exfiltration + One-time interaction + Dynamic key exfiltration + Ongoing interaction / code change + Content exfiltration + Ongoing, bulk interaction + + +Each of the attack types discussed in the previous section entails certain costs and risks. These costs differ by attack, and can be helpful in guiding response to pervasive attack. + +Depending on the attack, the attacker may be exposed to several types of risk, ranging from simply losing access to arrest or prosecution. In order for any of these negative consequences to occur, however, the attacker must first be discovered and identified. So the primary risk we focus on here is the risk of discovery and attribution. + +A passive attack is the simplest to mount in some ways. The base requirement is that the attacker obtain physical access to a communications medium and extract communications from it. For example, the attacker might tap a fiber-optic cable, acquire a mirror port on a switch, or listen to a wireless signal. The need for these taps to have physical access or proximity to a link exposes the attacker to the risk that the taps will be discovered. For example, a fiber tap or mirror port might be discovered by network operators noticing increased attenuation in the fiber or a change in switch configuration. Of course, passive attacks may be accomplished with the cooperation of the network operator, in which case there is a risk that the attacker’s interactions with the network operator will be exposed. + +In many ways, the costs and risks for an active attack are similar to those for a passive attack, with a few additions. An active attacker requires more robust network access than a passive attacker, since for example they will often need to transmit data as well as receiving it. In the wireless example above, the attacker would need to act as an transmitter as well as receiver, greatly increasing the probability the attacker will be discovered (e.g., using direction-finding technology). Active attacks are also much more observable at higher layers of the network. For example, an active attacker that attempts to use a mis-issued certificate could be detected via Certificate Transparency . + +In terms of raw implementation complexity, passive attacks require only enough processing to extract information from the network and store it. Active attacks, by contrast, often depend on winning race conditions to inject pakets into active connections. So active attacks in the core of the network require processing hardware to that can operate at line speed (roughly 100Gbps to 1Tbps in the core) to identify opportunities for attack and insert attack traffic in a high-volume traffic. +Key exfiltration attacks rely on passive attack for access to encrypted data, with the collaborator providing keys to decrypt the data. So the attacker undertakes the cost and risk of a passive attack, as well as additional risk of discovery via the interactions that the attacker has with the collaborator. + +In this sense, static exfiltration has a lower risk profile than dynamic. In the static case, the attacker need only interact with the collaborator a small number of times, possibly only once, say to exchange a private key. In the dynamic case, the attacker must have continuing interactions with the collaborator. As noted above these interactions may real, such as in-person meetings, or virtual, such as software modifications that render keys available to the attacker. Both of these types of interactions introduce a risk that they will be discovered, e.g., by employees of the collaborator organization noticing suspicious meetings or suspicious code changes. + +Content exfiltration has a similar risk profile to dynamic key exfiltration. In a content exfiltration attack, the attacker saves the cost and risk of conducting a passive attack. The risk of discovery through interactions with the collaborator, however, is still present, and may be higher. The content of a communication is obviously larger than the key used to encrypt it, often by several orders of magnitude. So in the content exfiltration case, the interactions between the collaborator and the attacker need to be much higher-bandwidth than in the key exfiltration cases, with a corresponding increase in the risk that this high-bandwidth channel will be discovered. + +It should also be noted that in these latter three exfiltration cases, the collaborator also undertakes a risk that his collaboration with the attacker will be discovered. Thus the attacker may have to incur additional cost in order to convince the collaborator to participate in the attack. Likewise, the scope of these attacks is limited to case where the attacker can convince a collaborator to participate. If the attacker is a national government, for example, it may be able to compel participation within its borders, but have a much more difficult time recruiting foreign collaborators. + +As noted above, the collaborator in an exfiltration attack can be unwitting; the attacker can steal keys or data to enable the attack. In some ways, the risks of this approach are similar to the case of an active collaborator. In the static case, the attacker needs to steal information from the collaborator once; in the dynamic case, the attacker needs to continued presence inside the collaborators systems. The main difference is that the risk in this case is of automated discovery (e.g., by intrusion detection systems) rather than discovery by humans. + +
+
+
+ +This document describes a threat model for pervasive surveillance attacks. Mitigations are to be given in a future document. + +
+
+ +This document has no actions for IANA. + +
+
+ +Thanks to Dave Thaler for the list of attacks and taxonomy; to Security Area Directors Stephen Farrell, Sean Turner, and Kathleen Moriarty for starting and managing the IETF’s discussion on pervasive attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, and Evangelos Halepilidis, and to the membership of the IAB Privacy and Security Program for their input. + +
+ + + + + + + + +&RFC6973; + + + + + + + + + How the NSA is still harvesting your online data + + The Guardian + + + + + + + NSA's Prism surveillance program: how it works and what it can do + + The Guardian + + + + + + + XKeyscore: NSA tool collects 'nearly everything a user does on the internet' + + The Guardian + + + + + + + How does GCHQ's internet surveillance work? + + The Guardian + + + + + + + N.S.A. Able to Foil Basic Safeguards of Privacy on Web + + The New York Times + + + + + + + Project Bullrun – classification guide to the NSA's decryption program + + The Guardian + + + + + + + Revealed: how US and UK spy agencies defeat internet privacy and security + + The Guardian + + + + + + + Tor + + The Tor Project + + + + + + + How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID + + + + + + + + + 'Tor Stinks' presentation – read the full document + + The Guardian + + + + + + + NSA collecting phone records of millions of Verizon customers daily + + The Guardian + + + + + + + NSA Prism program taps in to user data of Apple, Google and others + + The Guardian + + + + + + + Sigint – how the NSA collaborates with technology companies + + The Guardian + + + + + + + NSA surveillance: A guide to staying secure + + The Guardian + + + + + + + NSA Leak Leaves Crypto-Math Intact but Highlights Known Workarounds + + Technology Review + + + + + + + The Design and Implementation of Protocol-Based Hidden Key Recovery + + + + + + +&RFC1035; +&RFC1918; +&RFC1939; +&RFC2015; +&RFC2821; +&RFC3261; +&RFC3365; +&RFC3501; +&RFC3851; +&RFC4033; +&RFC4301; +&RFC4303; +&RFC4306; +&RFC4949; +&RFC5246; +&RFC5321; +&RFC5655; +&RFC5750; +&RFC6120; +&RFC6962; +&RFC6698; +&RFC7011; +&RFC7258; + + + + + + + + + diff --git a/draft-iab-privsec-confidentiality-threat-02.md b/draft-iab-privsec-confidentiality-threat-02.md new file mode 100644 index 0000000..c9885e3 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-02.md @@ -0,0 +1,425 @@ +--- +title: "Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement" +abbrev: Confidentiality Threat Model +docname: draft-iab-privsec-confidentiality-threat-02 +date: 2015-02-06 +category: info +ipr: trust200902 + +author: + - + ins: R. Barnes + name: Richard Barnes + email: rlb@ipv.sx + - + ins: B. Schneier + name: Bruce Schneier + email: schneier@schneier.com + - + ins: C. Jennings + name: Cullen Jennings + email: fluffy@cisco.com + - + ins: T. Hardie + name: Ted Hardie + email: ted.ietf@gmail.com + - + ins: B. Trammell + name: Brian Trammell + email: ietf@trammell.ch + - + ins: C. Huitema + name: Christian Huitema + email: huitema@huitema.net + - + ins: D. Borkmann + name: Daniel Borkmann + email: dborkman@redhat.com + +normative: + RFC6973: + +informative: + pass1: + target: http://www.theguardian.com/world/2013/jun/27/nsa-online-metadata-collection + title: "How the NSA is still harvesting your online data" + author: + organization: The Guardian + date: 2013 + pass2: + target: http://www.theguardian.com/world/2013/jun/08/nsa-prism-server-collection-facebook-google + title: "NSA's Prism surveillance program: how it works and what it can do" + author: + organization: The Guardian + date: 2013 + pass3: + target: http://www.theguardian.com/world/2013/jul/31/nsa-top-secret-program-online-data + title: "XKeyscore: NSA tool collects 'nearly everything a user does on the internet'" + author: + organization: The Guardian + date: 2013 + pass4: + target: http://www.theguardian.com/uk/2013/jun/21/how-does-gchq-internet-surveillance-work + title: "How does GCHQ's internet surveillance work?" + author: + organization: The Guardian + dec1: + target: http://www.nytimes.com/2013/09/06/us/nsa-foils-much-internet-encryption.html + title: "N.S.A. Able to Foil Basic Safeguards of Privacy on Web" + author: + organization: The New York Times + date: 2013 + dec2: + target: http://www.theguardian.com/world/interactive/2013/sep/05/nsa-project-bullrun-classification-guide + title: "Project Bullrun – classification guide to the NSA's decryption program" + author: + organization: The Guardian + date: 2013 + dec3: + target: http://www.theguardian.com/world/2013/sep/05/nsa-gchq-encryption-codes-security + title: "Revealed: how US and UK spy agencies defeat internet privacy and security" + author: + organization: The Guardian + date: 2013 + TOR: + target: https://www.torproject.org/ + title: "Tor" + author: + organization: The Tor Project + date: 2013 + TOR1: + target: https://www.schneier.com/blog/archives/2013/10/how_the_nsa_att.html + title: "How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID" + author: + name: Bruce Schneier + ins: B. Schneier + date: 2013 + TOR2: + target: http://www.theguardian.com/world/interactive/2013/oct/04/tor-stinks-nsa-presentation-document + title: "'Tor Stinks' presentation – read the full document" + author: + organization: The Guardian + date: 2013 + dir1: + target: http://www.theguardian.com/world/2013/jun/06/nsa-phone-records-verizon-court-order + title: "NSA collecting phone records of millions of Verizon customers daily" + author: + organization: The Guardian + date: 2013 + dir2: + target: http://www.theguardian.com/world/2013/jun/06/us-tech-giants-nsa-data + title: "NSA Prism program taps in to user data of Apple, Google and others" + author: + organization: The Guardian + date: 2013 + dir3: + target: http://www.theguardian.com/world/interactive/2013/sep/05/sigint-nsa-collaborates-technology-companies + title: "Sigint – how the NSA collaborates with technology companies" + author: + organization: The Guardian + date: 2013 + secure: + target: http://www.theguardian.com/world/2013/sep/05/nsa-how-to-remain-secure-surveillance + title: "NSA surveillance: A guide to staying secure" + author: + name: Bruce Schneier + ins: B. Schneier + organization: The Guardian + date: 2013 + snowden: + target: http://www.technologyreview.com/news/519171/nsa-leak-leaves-crypto-math-intact-but-highlights-known-workarounds/ + title: NSA Leak Leaves Crypto-Math Intact but Highlights Known Workarounds + author: + organization: Technology Review + date: 2013 + key-recovery: + target: http://crypto.stanford.edu/~pgolle/papers/escrow.pdf + title: The Design and Implementation of Protocol-Based Hidden Key Recovery + author: + ins: E.-J. Goh + name: Eu-Jin Goh + author: + ins: D. Boneh + name: Dan Boneh + author: + ins: B. Pinkas + name: Benny Pinkas + author: + ins: P. Golle + name: Phillippe Golle + date: 2003 + RFC1035: + RFC1918: + RFC1939: + RFC2015: + RFC2821: + RFC3261: + RFC3365: + RFC3501: + RFC3851: + RFC4033: + RFC4301: + RFC4303: + RFC4306: + RFC4949: + RFC5246: + RFC5321: + RFC5655: + RFC5750: + RFC6120: + RFC6962: + RFC6698: + RFC7011: + RFC7258: + +--- abstract + +Documents published in 2013 revealed several classes of pervasive surveillance attack on Internet communications. In this document we develop a threat model that describes these pervasive attacks. We start by assuming a completely passive attacker with an interest in undetected, indiscriminate eavesdropping, then expand the threat model with a set of verified attacks that have been published. + +--- middle + +# Introduction + +Starting in June 2013, documents released to the press by Edward Snowden have revealed several operations undertaken by intelligence agencies to exploit Internet communications for intelligence purposes. These attacks were largely based on protocol vulnerabilities that were already known to exist. The attacks were nonetheless striking in their pervasive nature, both in terms of the amount of Internet communications targeted, and in terms of the diversity of attack techniques employed. + +To ensure that the Internet can be trusted by users, it is necessary for the Internet technical community to address the vulnerabilities exploited in these attacks {{RFC7258}}. The goal of this document is to describe more precisely the threats posed by these pervasive attacks, and based on those threats, lay out the problems that need to be solved in order to secure the Internet in the face of those threats. + +The remainder of this document is structured as follows. In {{adversary}}, we describe an idealized passive attacker, one which could completely undetectably compromise communications at Internet scale. In {{reported}}, we provide a brief summary of some attacks that have been disclosed, and use these to expand the assumed capabilities of our idealized attacker. {{model}} describes a threat model based on these attacks, focusing on classes of attack that have not been a focus of Internet engineering to date. + +# Terminology {#terminology} + +This document makes extensive use of standard security and privacy terminology; see {{RFC4949}} and {{RFC6973}}. Terms used from {{RFC6973}} include Eavesdropper, Observer, Initiator, Intermediary, Recipient, Attack (in a privacy context), Correlation, Fingerprint, Traffic Analysis, and Identifiability (and related terms). In addition, we use a few terms that are specific to the attacks discussed here: + +Passive Attack: +: In this document, the term passive attack is used with respect to the traffic stream: a passive attack does not modify the packets in the traffic stream between two endpoints, modify the treatment of packets in the traffic stream (e.g. delay, routing), or add or remove packets in the traffic stream. Passive attacks are undetectable from the endpoints. + +Active Attack: +: In constrast to a passive attack, and active attack may modify a traffic stream, at the cost of possible detection at the endpoints. + +Pervasive Attack: +: An attack on Internet communications that makes use of access at a large number of points in the network, or otherwise provides the attacker with access to a large amount of Internet traffic; see {{RFC7258}} + +Observation: +: Information collected directly from communications by an eavesdropper or observer. For example, the knowledge that <alice@example.com> sent a message to <bob@example.com> via SMTP taken from the headers of an observed SMTP message would be an observation. + +Inference: +: Information extracted from analysis of information collected directly from communications by an eavesdropper or observer. For example, the knowledge that a given web page was accessed by a given IP address, by comparing the size in octets of measured network flow records to fingerprints derived from known sizes of linked resources on the web servers involved, would be an +inference. + +Collaborator: +: An entity that is a legitimate participant in a communication, but who deliberately provides information about that interaction to an attacker. + +Unwitting Collaborator: +: An entity that is a legitimate participant in a communication, and who is the source of information obtained by the attacker without the entity's consent or intention, because the attacker has exploited some technology used by the entity. + +Key Exfiltration: +: The transmission of keying material for an encrypted communication from a collaborator, deliberately or unwittingly, to an attacker + +Content Exfiltration: +: The transmission of the content of a communication from a collaborator, deliberately or unwittingly, to an attacker + +# An Idealized Pervasive Passive Attacker {#adversary} + +In considering the threat posed by pervasive surveillance, we begin by defining an idealized pervasive passive attacker. While this attacker is less capable than those which we now know to have compromised the Internet from press reports, as elaborated in {{reported}}, it does set a lower bound on the capabilities of an attacker interested in indiscriminate passive surveillance while interested in remaining undetectable. We note that, prior to the Snowden revelations in 2013, the assumptions of attacker capability presented here would be considered on the border of paranoia outside the network security community. + +Our idealized attacker is an indiscriminate eavesdropper on an Internet-attached computer network that: + +- can observe every packet of all communications at any hop in any network path between an initiator and a recipient; +- can observe data at rest in any intermediate system between the endpoints controlled by the initiator and recipient; and +- can share information with other such attackers; but +- takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.). + +The techniques available to our ideal attacker are direct observation and inference. Direct observation involves taking information directly from eavesdropped communications - e.g., URLs identifying content or email addresses identifying individuals from application-layer headers. Inference, on the other hand, involves analyzing eavesdropped information to derive new information from it; e.g., searching for application or behavioral fingerprints in observed traffic to derive information about the observed individual from them, in absence of directly-observed sources of the same information. The use of encryption to protect confidentiality is generally enough to prevent direct observation of unencrypted content, assuming uncompromised encryption implementations and key material. However, it provides less complete protection against inference, especially inference based only on unprotected portions of communications (e.g. IP and TCP headers for TLS {{RFC5246}}). + +## Information subject to direct observation + +Protocols which do not encrypt their payload make the entire content of the communication available to the idealized attacker along their path. Following the advice in {{RFC3365}}, most such protocols have a secure variant which encrypts payload for confidentiality, and these secure variants are seeing ever-wider deployment. A noteworthy exception is DNS {{RFC1035}}, as DNSSEC {{RFC4033}} does not have confidentiality as a requirement. This implies that, in the absence of changes to the protocol as presently under development in the DPRIVE working group, all DNS queries and answers generated by the activities of any protocol are available to the attacker. + +Protocols which imply the storage of some data at rest in intermediaries (e.g. SMTP {{RFC5321}}) leave this data subject to observation by an attacker that has compromised these intermediaries, unless the data is encrypted end-to-end by the application layer protocol, or the implementation uses an encrypted store for this data. + +## Information useful for inference + +Inference is information extracted from later analysis of an observed or eavesdropped communication, and/or correlation of observed or eavesdropped information with information available from other sources. Indeed, most useful inference performed by the attacker falls under the rubric of correlation. The simplest example of this is the observation of DNS queries and answers from and to a source and correlating those with IP addresses with which that source communicates. This can give access to information otherwise not available from encrypted application payloads (e.g., the Host: HTTP/1.1 request header when HTTP is used with TLS). + +Protocols which encrypt their payload using an application- or transport-layer encryption scheme (e.g. TLS) still expose all the information in their network and transport layer headers to the attacker, including source and destination addresses and ports. IPsec ESP{{RFC4303}} further encrypts the transport-layer headers, but still leaves IP address information unencrypted; in tunnel mode, these addresses correspond to the tunnel endpoints. Features of the cryptographic protocols themselves, e.g. the TLS session identifier, may leak information that can be used for correlation and inference. While this information is much less semantically rich than the application payload, it can still be useful for the inferring an individual's activities. + +Inference can also leverage information obtained from sources other than direct traffic observation. Geolocation databases, for example, have been developed map IP addresses to a location, in order to provide location-aware services such as targeted advertising. This location information is often of sufficient resolution that it can be used to draw further inferences toward identifying or profiling an individual. + +Social media provide another source of more or less publicly accessible information. This information can be extremely semantically rich, including information about an individual's location, associations with other individuals and groups, and activities. Further, this information is generally contributed and curated voluntarily by the individuals themselves: it represents information which the individuals are not necessarily interested in protecting for privacy reasons. However, correlation of this social networking data with information available from direct observation of network traffic allows the creation of a much richer picture of an individual's activities than either alone. + +We note with some alarm that there is little that can be done at protocol design time to limit such correlation by the attacker, and that the existence of such data sources in many cases greatly complicates the problem of protecting privacy by hardening protocols alone. + +## An illustration of an ideal passive attack + +To illustrate how capable the idealized attacker is even given its limitations, we explore the non-anonymity of encrypted IP traffic in this section. Here we examine in detail some inference techniques for associating a set of addresses with an individual, in order to illustrate the difficulty of defending communications against our idealized attacker. Here, the basic problem is that information radiated even from protocols which have no obvious connection with personal data can be correlated with other information which can paint a very rich behavioral picture, that only takes one unprotected link in the chain to associate with an identity. + +### Analysis of IP headers + +Internet traffic can be monitored by tapping Internet links, or by installing monitoring tools in Internet routers. Of course, a single link or a single router only provides access to a fraction of the global Internet traffic. However, monitoring a number of high capacity links or a set of routers placed at strategic locations provides access to a good sampling of Internet traffic. + +Tools like IPFIX {{RFC7011}} allow administrators to acquire statistics about sequences of packets with some common properties that pass through a network device. The most common set of properties used in flow measurement is the "five-tuple"of source and destination addresses, protocol type, and source and destination ports. These statistics are commonly used for network engineering, but could certainly be used for other purposes. + +Let's assume for a moment that IP addresses can be correlated to specific services or specific users. Analysis of the sequences of packets will quickly reveal which users use what services, and also which users engage in peer-to-peer connections with other users. Analysis of traffic variations over time can be used to detect increased activity by particular users, or in the case of peer-to-peer connections increased activity within groups of users. + +### Correlation of IP addresses to user identities + +The correlation of IP addresses with specific users can be done in various ways. For example, tools like reverse DNS lookup can be used to retrieve the DNS names of servers. Since the addresses of servers tend to be quite stable and since servers are relatively less numerous than users, an attacker could easily maintain its own copy of the DNS for well-known or popular servers, to accelerate such lookups. + +On the other hand, the reverse lookup of IP addresses of users is generally less informative. For example, a lookup of the address currently used by one author's home network returns a name of the form "c-192-000-002-033.hsd1.wa.comcast.net". This particular type of reverse DNS lookup generally reveals only coarse-grained location or provider information, equivalent to that available from geolocation databases. + +In many jurisdictions, Internet Service Providers (ISPs) are required to provide identification on a case by case basis of the "owner" of a specific IP address for law enforcement purposes. This is a reasonably expedient process for targeted investigations, but pervasive surveillance requires something more efficient. This provides an incentive for the attacker to secure the cooperation of the ISP in order to automate this correlation. + +### Monitoring messaging clients for IP address correlation + +Even if the ISP does not cooperate, user identity can often be obtained via inference. POP3 {{RFC1939}} and IMAP {{RFC3501}} are used to retrieve mail from mail servers, while a variant of SMTP is used to submit messages through mail servers. IMAP connections originate from the client, and typically start with an authentication exchange in which the client proves its identity by answering a password challenge. The same holds for the SIP protocol {{RFC3261}} and many instant messaging services operating over the Internet using proprietary protocols. + +The username is directly observable if any of these protocols operate in cleartext; the username can then be directly associated with the source address. + +### Retrieving IP addresses from mail headers + +SMTP {{RFC5321}} requires that each successive SMTP relay adds a "Received" header to the mail headers. The purpose of these headers is to enable audit of mail transmission, and perhaps to distinguish between regular mail and spam. Here is an extract from the headers of a message recently received from the "perpass" mailing list: + +``` + Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?) + (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA + (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100 + Message-ID: <526D7BD2.7070908@example.org> + Date: Sun, 27 Oct 2013 20:47:14 +0000 + From: Some One +``` + +This is the first "Received" header attached to the message by the first SMTP relay; for privacy reasons, the field values have been anonymized. We learn here that the message was submitted by "Some One" on October 27, from a host behind a NAT (192.168.1.100) {{RFC1918}} that used the IP address 192.0.2.44. The information remained in the message, and is accessible by all recipients of the "perpass" mailing list, or indeed by any attacker that sees at least one copy of the message. + +An attacker that can observe sufficient email traffic can regularly update the mapping between public IP addresses and individual email identities. Even if the SMTP traffic was encrypted on submission and relaying, the attacker can still receive a copy of public mailing lists like "perpass". + +### Tracking address usage with web cookies + +Many web sites only encrypt a small fraction of their transactions. A popular pattern is to use HTTPS for the login information, and then use a "cookie" to associate following clear-text transactions with the user's identity. Cookies are also used by various advertisement services to quickly identify the users and serve them with "personalized" advertisements. Such cookies are particularly useful if the advertisement services want to keep tracking the user across multiple sessions that may use different IP addresses. + +As cookies are sent in clear text, an attacker can build a database that associates cookies to IP addresses for non-HTTPS traffic. If the IP address is already identified, the cookie can be linked to the user identify. After that, if the same cookie appears on a new IP address, the new IP address can be immediately associated with the pre-determined identity. + +### Graph-based approaches to address correlation + +An attacker can track traffic from an IP address not yet associated with an individual to various public services (e.g. websites, mail servers, game servers), and exploit patterns in the observed traffic to correlate this address with other addresses that show similar patterns. For example, any two addresses that show connections to the same IMAP or webmail services, the same set of favorite websites, and game servers at similar times of day may be associated with the same individual. Correlated addresses can then be tied to an individual through one of the techniques above, walking the "network graph" to expand the set of attributable traffic. + +### Tracking of MAC Addresses + +Moving back down the stack, technologies like Ethernet or Wi-Fi use MAC Addresses to identify link-level destinations. MAC Addresses assigned according to IEEE-802 standards are unique to the device. If the link is publicly accessible, an attacker can track it. For example, the attacker can track the wireless traffic at public Wi-Fi networks. Simple devices can monitor the traffic, and reveal which MAC Addresses are present. If the network does not use some form of Wi-Fi encryption, or if the attacker can access the decrypted traffic, the analysis will also provide the correlation between MAC Addresses and IP addresses. Additional monitoring using techniques exposed in the previous sections will reveal the correlation between MAC Addresses, IP Addresses, and user identity. + +Given that large-scale databases of the MAC addresses of wireless access points for geolocation purposes have been known to exist for some time, the attacker could easily build a database linking MAC Addresses and device or user identities, and use it to track the movement of devices and of their owners. + +# Reported Instances of Large-Scale Attacks {#reported} + +The situation in reality is more bleak than that suggested by an analysis of our idealized attacker. Through revelations of sensitive documents in several media outlets, the Internet community has been made aware of several intelligence activities conducted by US and UK national intelligence agencies, particularly the US National Security Agency (NSA) and the UK Government Communications Headquarters (GCHQ). These documents have revealed methods that these agencies use to attack Internet applications and obtain sensitive user information. + +First, they have confirmed that these agencies have capabilities in line with those of our idealized attacker, thorugh the large-scale passive collection of Internet traffic {{pass1}}{{pass2}}{{pass3}}{{pass4}}. For example: + - The NSA XKEYSCORE system accesses data from multiple access points and searches for "selectors" such as email addresses, at the scale of tens of terabytes of data per day. + - The GCHQ Tempora system appears to have access to around 1,500 major cables passing through the UK. + - The NSA MUSCULAR program tapped cables between data centers belonging to major service providers. + - Several programs appear to perform wide-scale collection of cookies in web traffic and location data from location-aware portable devices such as smartphones. + +However, the capabilities described go beyond those available to our idealized attacker, including: + +* Decryption of TLS-protected Internet sessions {{dec1}}{{dec2}}{{dec3}}. For example, the NSA BULLRUN project appears to have had a budget of around $250M per year to undermine encryption through multiple approaches. + +* Insertion of NSA devices as a man-in-the-middle of Internet transactions {{TOR1}}{{TOR2}}. For example, the NSA QUANTUM system appears to use several different techniques to hijack HTTP connections, ranging from DNS response injection to HTTP 302 redirects. + +* Direct acquisition of bulk data and metadata from service providers {{dir1}}{{dir2}}{{dir3}}. For example, the NSA PRISM program provides the agency with access to many types of user data (e.g., email, chat, VoIP). + +* Use of implants (covert modifications or malware) to undermine security and anonymity features {{dec2}}{{TOR1}}{{TOR2}}. For example: + * NSA appears to use the QUANTUM man-in-the-middle system to direct users to a FOXACID server, which delivers an implant to compromise the browser of a user of the Tor anonymous communications network. + * The BULLRUN program mentioned above includes the addition of covert modifications to software as one means to undermine encryption. + * There is also some suspicion that NSA modifications to the DUAL\_EC\_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA. These suspicions have been reinforced by reports that RSA Security was paid roughly $10M to make DUAL\_EC\_DRBG the default in their products. + +We use the term "pervasive attack" {{RFC7258}} to collectively describe these operations. The term "pervasive" is used because the attacks are designed to indiscriminately gather as much data as possible and to apply selective analysis on targets after the fact. This means that all, or nearly all, Internet communications are targets for these attacks. To achieve this scale, the attacks are physically pervasive; they affect a large number of Internet communications. They are pervasive in content, consuming and exploiting any information revealed by the protocol. And they are pervasive in technology, exploiting many different vulnerabilities in many different protocols. + +It's important to note that although the attacks mentioned above were executed by NSA and GCHQ, there are many other organizations that can mount pervasive surveillance attacks. Because of the resources required to achieve pervasive scale, these attacks are most commonly undertaken by nation-state actors. For example, the Chinese Internet filtering system known as the "Great Firewall of China" uses several techniques that are similar to the QUANTUM program, and which have a high degree of pervasiveness with regard to the Internet in China. + +# Threat Model {#model} + +Given these disclosures, we must consider a broader threat model. + +Pervasive surveillance aims to collect information across a large number of Internet communications, analyzing the collected communications to identify information of interest within individual communications, or inferring information from correlated communications. his analysis sometimes benefits from decryption of encrypted communications and deanonymization of anonymized communications. As a result, these attackers desire both access to the bulk of Internet traffic and to the keying material required to decrypt any traffic that has been encrypted. Even if keys are not available, note that the presence of a communication and the fact that it is encrypted may both be inputs to an analysis, even if the attacker cannot decrypt the communication. + +The attacks listed above highlight new avenues both for access to traffic and for access to relevant encryption keys. They further indicate that the scale of surveillance is sufficient to provide a general capability to cross-correlate communications, a threat not previously thought to be relevant at the scale of the Internet. + +## Attacker Capabilities + +| Attack Class | Capability | +|:--------------------------|:------------------------------------------| +| Passive observation | Directly capture data in transit | +| Passive inference | Infer from reduced/encrypted data | +| Active | Manipulate / inject data in transit | +| Static key exfiltration | Obtain key material once / rarely | +| Dynamic key exfiltration | Obtain per-session key material | +| Content exfiltration | Access data at rest | + +Security analyses of Internet protocols commonly consider two classes of attacker: Passive attackers, who can simply listen in on communications as they transit the network, and active attackers, who can modify or delete packets in addition to simply collecting them. + +In the context of pervasive passive surveillance, these attacks take on an even greater significance. In the past, these attackers were often assumed to operate near the edge of the network, where attacks can be simpler. For example, in some LANs, it is simple for any node to engage in passive listening to other nodes' traffic or inject packets to accomplish active attacks. However, as we now know, both passive and active attacks are undertaken by pervasive attackers closer to the core of the network, greatly expanding the scope and capability of the attacker. + +Eavesdropping and observation at a larger scale make passive inference attacks easier to carry out: a passive attacker with access to a large portion of the Internet can analyze collected traffic to create a much more detailed view of individual behavior than an attacker that collects at a single point. Even the usual claim that encryption defeats passive attackers is weakened, since a pervasive passive attacker can infer relationships from correlations over large numbers of sessions, e.g., pairing encrypted sessions with unencrypted sessions from the same host, or performing traffic fingerprinting between known and unknown encrypted sessions. Reports on the NSA XKEYSCORE system would indicate it is an example of such an attacker. + +A pervasive active attacker likewise has capabilities beyond those of a localized active attacker. Active attacks are often limited by network topology, for example by a requirement that the attacker be able to see a targeted session as well as inject packets into it. A pervasive active attacker with access at multiple points within the core of the Internet is able to overcome these topological limitations and perform attacks over a much broader scope. Being positioned in the core of the network rather than the edge can also enable a pervasive active attacker to reroute targeted traffic, amplifying the ability to perform both eavesdropping and traffic injection. Pervasive active attackers can also benefit from pervasive passive collection to identify vulnerable hosts. + +While not directly related to pervasiveness, attackers that are in a position to mount a pervasive active attack are also often in a position to subvert authentication, a traditional protection against such attacks. Authentication in the Internet is often achieved via trusted third party authorities such as the Certificate Authorities (CAs) that provide web sites with authentication credentials. An attacker with sufficient resources may also be able to induce an authority to grant credentials for an identity of the attacker’s choosing. If the parties to a communication will trust multiple authorities to certify a specific identity, this attack may be mounted by suborning any one of the authorities (the proverbial "weakest link"). Subversion of authorities in this way can allow an active attack to succeed in spite of an authentication check. + +Beyond these three classes (observation, inference, and active), reports on the BULLRUN effort to defeat encryption and the PRISM effort to obtain data from service providers suggest three more classes of attack: + +* Static key exfiltration +* Dynamic key exfiltration +* Content exfiltration + +These attacks all rely on a collaborator providing the attacker with some information, either keys or data. These attacks have not traditionally been considered in scope for the Security Considerations sections of IETF protocols, as they occur outside the protocol. + +The term "key exfiltration" refers to the transfer of keying material for an encrypted communication from the collaborator to the attacker. By "static", we mean that the transfer of keys happens once, or rarely, typically of a long-lived key. For example, this case would cover a web site operator that provides the private key corresponding to its HTTPS certificate to an intelligence agency. + +"Dynamic" key exfiltration, by contrast, refers to attacks in which the collaborator delivers keying material to the attacker frequently, e.g., on a per-session basis. This does not necessarily imply frequent communications with the attacker; the transfer of keying material may be virtual. For example, if an endpoint were modified in such a way that the attacker could predict the state of its psuedorandom number generator, then the attacker would be able to derive per-session keys even without per-session communications. + +Finally, content exfiltration is the attack in which the collaborator simply provides the attacker with the desired data or metadata. Unlike the key exfiltration cases, this attack does not require the attacker to capture the desired data as it flows through the network. The risk is to data at rest as opposed to data in transit. This increases the scope of data that the attacker can obtain, since the attacker can access historical data -- the attacker does not have to be listening at the time the communication happens. + +Exfiltration attacks can be accomplished via attacks against one of the parties to a communication, i.e., by the attacker stealing the keys or content rather than the party providing them willingly. In these cases, the party may not be aware that they are collaborating, at least at a human level. Rather, the subverted technical assets are "collaborating" with the attacker (by providing keys/content) without their owner's knowledge or consent. + +Any party that has access to encryption keys or unencrypted data can be a collaborator. While collaborators are typically the endpoints of a communication (with encryption securing the links), intermediaries in an unencrypted communication can also facilitate content exfiltration attacks as collaborators by providing the attacker access to those communications. For example, documents describing the NSA PRISM program claim that NSA is able to access user data directly from servers, where it is stored unencrypted. In these cases, the operator of the server would be a collaborator, if an unwitting one. By contrast, in the NSA MUSCULAR program, a set of collaborators enabled attackers to access the cables connecting data centers used by service providers such as Google and Yahoo. Because communications among these data centers were not encrypted, the collaboration by an intermediate entity allowed NSA to collect unencrypted user data. + +## Attacker Costs + +| Attack Class | Cost / Risk to Attacker | +|:--------------------------|:----------------------------------| +| Passive observation | Passive data access | +| Passive inference | Passive data access + processing | +| Active | Active data access + processing | +| Static key exfiltration | One-time interaction | +| Dynamic key exfiltration | Ongoing interaction / code change | +| Content exfiltration | Ongoing, bulk interaction | + +Each of the attack types discussed in the previous section entails certain costs and risks. These costs differ by attack, and can be helpful in guiding response to pervasive attack. + +Depending on the attack, the attacker may be exposed to several types of risk, ranging from simply losing access to arrest or prosecution. In order for any of these negative consequences to occur, however, the attacker must first be discovered and identified. So the primary risk we focus on here is the risk of discovery and attribution. + +A passive attack is the simplest to mount in some ways. The base requirement is that the attacker obtain physical access to a communications medium and extract communications from it. For example, the attacker might tap a fiber-optic cable, acquire a mirror port on a switch, or listen to a wireless signal. The need for these taps to have physical access or proximity to a link exposes the attacker to the risk that the taps will be discovered. For example, a fiber tap or mirror port might be discovered by network operators noticing increased attenuation in the fiber or a change in switch configuration. Of course, passive attacks may be accomplished with the cooperation of the network operator, in which case there is a risk that the attacker's interactions with the network operator will be exposed. + +In many ways, the costs and risks for an active attack are similar to those for a passive attack, with a few additions. An active attacker requires more robust network access than a passive attacker, since for example they will often need to transmit data as well as receiving it. In the wireless example above, the attacker would need to act as an transmitter as well as receiver, greatly increasing the probability the attacker will be discovered (e.g., using direction-finding technology). Active attacks are also much more observable at higher layers of the network. For example, an active attacker that attempts to use a mis-issued certificate could be detected via Certificate Transparency {{RFC6962}}. + +In terms of raw implementation complexity, passive attacks require only enough processing to extract information from the network and store it. Active attacks, by contrast, often depend on winning race conditions to inject pakets into active connections. So active attacks in the core of the network require processing hardware to that can operate at line speed (roughly 100Gbps to 1Tbps in the core) to identify opportunities for attack and insert attack traffic in a high-volume traffic. +Key exfiltration attacks rely on passive attack for access to encrypted data, with the collaborator providing keys to decrypt the data. So the attacker undertakes the cost and risk of a passive attack, as well as additional risk of discovery via the interactions that the attacker has with the collaborator. + +In this sense, static exfiltration has a lower risk profile than dynamic. In the static case, the attacker need only interact with the collaborator a small number of times, possibly only once, say to exchange a private key. In the dynamic case, the attacker must have continuing interactions with the collaborator. As noted above these interactions may real, such as in-person meetings, or virtual, such as software modifications that render keys available to the attacker. Both of these types of interactions introduce a risk that they will be discovered, e.g., by employees of the collaborator organization noticing suspicious meetings or suspicious code changes. + +Content exfiltration has a similar risk profile to dynamic key exfiltration. In a content exfiltration attack, the attacker saves the cost and risk of conducting a passive attack. The risk of discovery through interactions with the collaborator, however, is still present, and may be higher. The content of a communication is obviously larger than the key used to encrypt it, often by several orders of magnitude. So in the content exfiltration case, the interactions between the collaborator and the attacker need to be much higher-bandwidth than in the key exfiltration cases, with a corresponding increase in the risk that this high-bandwidth channel will be discovered. + +It should also be noted that in these latter three exfiltration cases, the collaborator also undertakes a risk that his collaboration with the attacker will be discovered. Thus the attacker may have to incur additional cost in order to convince the collaborator to participate in the attack. Likewise, the scope of these attacks is limited to case where the attacker can convince a collaborator to participate. If the attacker is a national government, for example, it may be able to compel participation within its borders, but have a much more difficult time recruiting foreign collaborators. + +As noted above, the collaborator in an exfiltration attack can be unwitting; the attacker can steal keys or data to enable the attack. In some ways, the risks of this approach are similar to the case of an active collaborator. In the static case, the attacker needs to steal information from the collaborator once; in the dynamic case, the attacker needs to continued presence inside the collaborators systems. The main difference is that the risk in this case is of automated discovery (e.g., by intrusion detection systems) rather than discovery by humans. + +# Security Considerations + +This document describes a threat model for pervasive surveillance attacks. Mitigations are to be given in a future document. + +# IANA Considerations + +This document has no actions for IANA. + +# Acknowledgements + +Thanks to Dave Thaler for the list of attacks and taxonomy; to Security Area Directors Stephen Farrell, Sean Turner, and Kathleen Moriarty for starting and managing the IETF's discussion on pervasive attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, Evangelos Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, as well as the IAB Privacy and Security Program, for their input. diff --git a/draft-iab-privsec-confidentiality-threat-02.pdf b/draft-iab-privsec-confidentiality-threat-02.pdf new file mode 100644 index 0000000..8116133 Binary files /dev/null and b/draft-iab-privsec-confidentiality-threat-02.pdf differ diff --git a/draft-iab-privsec-confidentiality-threat-02.txt b/draft-iab-privsec-confidentiality-threat-02.txt new file mode 100644 index 0000000..a0ce9f1 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-02.txt @@ -0,0 +1,1176 @@ + + + + +Network Working Group R. Barnes +Internet-Draft +Intended status: Informational B. Schneier +Expires: August 10, 2015 + C. Jennings + + T. Hardie + + B. Trammell + + C. Huitema + + D. Borkmann + + February 06, 2015 + + + Confidentiality in the Face of Pervasive Surveillance: A Threat Model + and Problem Statement + draft-iab-privsec-confidentiality-threat-02 + +Abstract + + Documents published in 2013 revealed several classes of pervasive + surveillance attack on Internet communications. In this document we + develop a threat model that describes these pervasive attacks. We + start by assuming a completely passive attacker with an interest in + undetected, indiscriminate eavesdropping, then expand the threat + model with a set of verified attacks that have been published. + +Status of This Memo + + This Internet-Draft is submitted in full conformance with the + provisions of BCP 78 and BCP 79. + + Internet-Drafts are working documents of the Internet Engineering + Task Force (IETF). Note that other groups may also distribute + working documents as Internet-Drafts. The list of current Internet- + Drafts is at http://datatracker.ietf.org/drafts/current/. + + Internet-Drafts are draft documents valid for a maximum of six months + and may be updated, replaced, or obsoleted by other documents at any + time. It is inappropriate to use Internet-Drafts as reference + material or to cite them other than as "work in progress." + + This Internet-Draft will expire on August 10, 2015. + + + + + +Barnes, et al. Expires August 10, 2015 [Page 1] + +Internet-Draft Confidentiality Threat Model February 2015 + + +Copyright Notice + + Copyright (c) 2015 IETF Trust and the persons identified as the + document authors. All rights reserved. + + This document is subject to BCP 78 and the IETF Trust's Legal + Provisions Relating to IETF Documents + (http://trustee.ietf.org/license-info) in effect on the date of + publication of this document. Please review these documents + carefully, as they describe your rights and restrictions with respect + to this document. Code Components extracted from this document must + include Simplified BSD License text as described in Section 4.e of + the Trust Legal Provisions and are provided without warranty as + described in the Simplified BSD License. + +1. Introduction + + Starting in June 2013, documents released to the press by Edward + Snowden have revealed several operations undertaken by intelligence + agencies to exploit Internet communications for intelligence + purposes. These attacks were largely based on protocol + vulnerabilities that were already known to exist. The attacks were + nonetheless striking in their pervasive nature, both in terms of the + amount of Internet communications targeted, and in terms of the + diversity of attack techniques employed. + + To ensure that the Internet can be trusted by users, it is necessary + for the Internet technical community to address the vulnerabilities + exploited in these attacks [RFC7258]. The goal of this document is + to describe more precisely the threats posed by these pervasive + attacks, and based on those threats, lay out the problems that need + to be solved in order to secure the Internet in the face of those + threats. + + The remainder of this document is structured as follows. In + Section 3, we describe an idealized passive attacker, one which could + completely undetectably compromise communications at Internet scale. + In Section 4, we provide a brief summary of some attacks that have + been disclosed, and use these to expand the assumed capabilities of + our idealized attacker. Section 5 describes a threat model based on + these attacks, focusing on classes of attack that have not been a + focus of Internet engineering to date. + +2. Terminology + + This document makes extensive use of standard security and privacy + terminology; see [RFC4949] and [RFC6973]. Terms used from [RFC6973] + include Eavesdropper, Observer, Initiator, Intermediary, Recipient, + + + +Barnes, et al. Expires August 10, 2015 [Page 2] + +Internet-Draft Confidentiality Threat Model February 2015 + + + Attack (in a privacy context), Correlation, Fingerprint, Traffic + Analysis, and Identifiability (and related terms). In addition, we + use a few terms that are specific to the attacks discussed here: + + Passive Attack: In this document, the term passive attack is used + with respect to the traffic stream: a passive attack does not + modify the packets in the traffic stream between two endpoints, + modify the treatment of packets in the traffic stream (e.g. delay, + routing), or add or remove packets in the traffic stream. Passive + attacks are undetectable from the endpoints. + + Active Attack: In constrast to a passive attack, and active attack + may modify a traffic stream, at the cost of possible detection at + the endpoints. + + Pervasive Attack: An attack on Internet communications that makes + use of access at a large number of points in the network, or + otherwise provides the attacker with access to a large amount of + Internet traffic; see [RFC7258] + + Observation: Information collected directly from communications by + an eavesdropper or observer. For example, the knowledge that + sent a message to via SMTP + taken from the headers of an observed SMTP message would be an + observation. + + Inference: Information extracted from analysis of information + collected directly from communications by an eavesdropper or + observer. For example, the knowledge that a given web page was + accessed by a given IP address, by comparing the size in octets of + measured network flow records to fingerprints derived from known + sizes of linked resources on the web servers involved, would be an + inference. + + Collaborator: An entity that is a legitimate participant in a + communication, but who deliberately provides information about + that interaction to an attacker. + + Unwitting Collaborator: An entity that is a legitimate participant + in a communication, and who is the source of information obtained + by the attacker without the entity's consent or intention, because + the attacker has exploited some technology used by the entity. + + Key Exfiltration: The transmission of keying material for an + encrypted communication from a collaborator, deliberately or + unwittingly, to an attacker + + + + + +Barnes, et al. Expires August 10, 2015 [Page 3] + +Internet-Draft Confidentiality Threat Model February 2015 + + + Content Exfiltration: The transmission of the content of a + communication from a collaborator, deliberately or unwittingly, to + an attacker + +3. An Idealized Pervasive Passive Attacker + + In considering the threat posed by pervasive surveillance, we begin + by defining an idealized pervasive passive attacker. While this + attacker is less capable than those which we now know to have + compromised the Internet from press reports, as elaborated in + Section 4, it does set a lower bound on the capabilities of an + attacker interested in indiscriminate passive surveillance while + interested in remaining undetectable. We note that, prior to the + Snowden revelations in 2013, the assumptions of attacker capability + presented here would be considered on the border of paranoia outside + the network security community. + + Our idealized attacker is an indiscriminate eavesdropper on an + Internet-attached computer network that: + + o can observe every packet of all communications at any hop in any + network path between an initiator and a recipient; + + o can observe data at rest in any intermediate system between the + endpoints controlled by the initiator and recipient; and + + o can share information with other such attackers; but + + o takes no other action with respect to these communications (i.e., + blocking, modification, injection, etc.). + + The techniques available to our ideal attacker are direct observation + and inference. Direct observation involves taking information + directly from eavesdropped communications - e.g., URLs identifying + content or email addresses identifying individuals from application- + layer headers. Inference, on the other hand, involves analyzing + eavesdropped information to derive new information from it; e.g., + searching for application or behavioral fingerprints in observed + traffic to derive information about the observed individual from + them, in absence of directly-observed sources of the same + information. The use of encryption to protect confidentiality is + generally enough to prevent direct observation of unencrypted + content, assuming uncompromised encryption implementations and key + material. However, it provides less complete protection against + inference, especially inference based only on unprotected portions of + communications (e.g. IP and TCP headers for TLS [RFC5246]). + + + + + +Barnes, et al. Expires August 10, 2015 [Page 4] + +Internet-Draft Confidentiality Threat Model February 2015 + + +3.1. Information subject to direct observation + + Protocols which do not encrypt their payload make the entire content + of the communication available to the idealized attacker along their + path. Following the advice in [RFC3365], most such protocols have a + secure variant which encrypts payload for confidentiality, and these + secure variants are seeing ever-wider deployment. A noteworthy + exception is DNS [RFC1035], as DNSSEC [RFC4033] does not have + confidentiality as a requirement. This implies that, in the absence + of changes to the protocol as presently under development in the + DPRIVE working group, all DNS queries and answers generated by the + activities of any protocol are available to the attacker. + + Protocols which imply the storage of some data at rest in + intermediaries (e.g. SMTP [RFC5321]) leave this data subject to + observation by an attacker that has compromised these intermediaries, + unless the data is encrypted end-to-end by the application layer + protocol, or the implementation uses an encrypted store for this + data. + +3.2. Information useful for inference + + Inference is information extracted from later analysis of an observed + or eavesdropped communication, and/or correlation of observed or + eavesdropped information with information available from other + sources. Indeed, most useful inference performed by the attacker + falls under the rubric of correlation. The simplest example of this + is the observation of DNS queries and answers from and to a source + and correlating those with IP addresses with which that source + communicates. This can give access to information otherwise not + available from encrypted application payloads (e.g., the Host: + HTTP/1.1 request header when HTTP is used with TLS). + + Protocols which encrypt their payload using an application- or + transport-layer encryption scheme (e.g. TLS) still expose all the + information in their network and transport layer headers to the + attacker, including source and destination addresses and ports. + IPsec ESP[RFC4303] further encrypts the transport-layer headers, but + still leaves IP address information unencrypted; in tunnel mode, + these addresses correspond to the tunnel endpoints. Features of the + cryptographic protocols themselves, e.g. the TLS session identifier, + may leak information that can be used for correlation and inference. + While this information is much less semantically rich than the + application payload, it can still be useful for the inferring an + individual's activities. + + Inference can also leverage information obtained from sources other + than direct traffic observation. Geolocation databases, for example, + + + +Barnes, et al. Expires August 10, 2015 [Page 5] + +Internet-Draft Confidentiality Threat Model February 2015 + + + have been developed map IP addresses to a location, in order to + provide location-aware services such as targeted advertising. This + location information is often of sufficient resolution that it can be + used to draw further inferences toward identifying or profiling an + individual. + + Social media provide another source of more or less publicly + accessible information. This information can be extremely + semantically rich, including information about an individual's + location, associations with other individuals and groups, and + activities. Further, this information is generally contributed and + curated voluntarily by the individuals themselves: it represents + information which the individuals are not necessarily interested in + protecting for privacy reasons. However, correlation of this social + networking data with information available from direct observation of + network traffic allows the creation of a much richer picture of an + individual's activities than either alone. + + We note with some alarm that there is little that can be done at + protocol design time to limit such correlation by the attacker, and + that the existence of such data sources in many cases greatly + complicates the problem of protecting privacy by hardening protocols + alone. + +3.3. An illustration of an ideal passive attack + + To illustrate how capable the idealized attacker is even given its + limitations, we explore the non-anonymity of encrypted IP traffic in + this section. Here we examine in detail some inference techniques + for associating a set of addresses with an individual, in order to + illustrate the difficulty of defending communications against our + idealized attacker. Here, the basic problem is that information + radiated even from protocols which have no obvious connection with + personal data can be correlated with other information which can + paint a very rich behavioral picture, that only takes one unprotected + link in the chain to associate with an identity. + +3.3.1. Analysis of IP headers + + Internet traffic can be monitored by tapping Internet links, or by + installing monitoring tools in Internet routers. Of course, a single + link or a single router only provides access to a fraction of the + global Internet traffic. However, monitoring a number of high + capacity links or a set of routers placed at strategic locations + provides access to a good sampling of Internet traffic. + + Tools like IPFIX [RFC7011] allow administrators to acquire statistics + about sequences of packets with some common properties that pass + + + +Barnes, et al. Expires August 10, 2015 [Page 6] + +Internet-Draft Confidentiality Threat Model February 2015 + + + through a network device. The most common set of properties used in + flow measurement is the "five-tuple"of source and destination + addresses, protocol type, and source and destination ports. These + statistics are commonly used for network engineering, but could + certainly be used for other purposes. + + Let's assume for a moment that IP addresses can be correlated to + specific services or specific users. Analysis of the sequences of + packets will quickly reveal which users use what services, and also + which users engage in peer-to-peer connections with other users. + Analysis of traffic variations over time can be used to detect + increased activity by particular users, or in the case of peer-to- + peer connections increased activity within groups of users. + +3.3.2. Correlation of IP addresses to user identities + + The correlation of IP addresses with specific users can be done in + various ways. For example, tools like reverse DNS lookup can be used + to retrieve the DNS names of servers. Since the addresses of servers + tend to be quite stable and since servers are relatively less + numerous than users, an attacker could easily maintain its own copy + of the DNS for well-known or popular servers, to accelerate such + lookups. + + On the other hand, the reverse lookup of IP addresses of users is + generally less informative. For example, a lookup of the address + currently used by one author's home network returns a name of the + form "c-192-000-002-033.hsd1.wa.comcast.net". This particular type + of reverse DNS lookup generally reveals only coarse-grained location + or provider information, equivalent to that available from + geolocation databases. + + In many jurisdictions, Internet Service Providers (ISPs) are required + to provide identification on a case by case basis of the "owner" of a + specific IP address for law enforcement purposes. This is a + reasonably expedient process for targeted investigations, but + pervasive surveillance requires something more efficient. This + provides an incentive for the attacker to secure the cooperation of + the ISP in order to automate this correlation. + +3.3.3. Monitoring messaging clients for IP address correlation + + Even if the ISP does not cooperate, user identity can often be + obtained via inference. POP3 [RFC1939] and IMAP [RFC3501] are used + to retrieve mail from mail servers, while a variant of SMTP is used + to submit messages through mail servers. IMAP connections originate + from the client, and typically start with an authentication exchange + in which the client proves its identity by answering a password + + + +Barnes, et al. Expires August 10, 2015 [Page 7] + +Internet-Draft Confidentiality Threat Model February 2015 + + + challenge. The same holds for the SIP protocol [RFC3261] and many + instant messaging services operating over the Internet using + proprietary protocols. + + The username is directly observable if any of these protocols operate + in cleartext; the username can then be directly associated with the + source address. + +3.3.4. Retrieving IP addresses from mail headers + + SMTP [RFC5321] requires that each successive SMTP relay adds a + "Received" header to the mail headers. The purpose of these headers + is to enable audit of mail transmission, and perhaps to distinguish + between regular mail and spam. Here is an extract from the headers + of a message recently received from the "perpass" mailing list: + + "Received: from 192-000-002-044.zone13.example.org (HELO + ?192.168.1.100?) (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net + with ESMTPSA (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct + 2013 21:47:14 +0100 Message-ID: <526D7BD2.7070908@example.org> Date: + Sun, 27 Oct 2013 20:47:14 +0000 From: Some One + " + + This is the first "Received" header attached to the message by the + first SMTP relay; for privacy reasons, the field values have been + anonymized. We learn here that the message was submitted by "Some + One" on October 27, from a host behind a NAT (192.168.1.100) + [RFC1918] that used the IP address 192.0.2.44. The information + remained in the message, and is accessible by all recipients of the + "perpass" mailing list, or indeed by any attacker that sees at least + one copy of the message. + + An attacker that can observe sufficient email traffic can regularly + update the mapping between public IP addresses and individual email + identities. Even if the SMTP traffic was encrypted on submission and + relaying, the attacker can still receive a copy of public mailing + lists like "perpass". + +3.3.5. Tracking address usage with web cookies + + Many web sites only encrypt a small fraction of their transactions. + A popular pattern is to use HTTPS for the login information, and then + use a "cookie" to associate following clear-text transactions with + the user's identity. Cookies are also used by various advertisement + services to quickly identify the users and serve them with + "personalized" advertisements. Such cookies are particularly useful + if the advertisement services want to keep tracking the user across + multiple sessions that may use different IP addresses. + + + +Barnes, et al. Expires August 10, 2015 [Page 8] + +Internet-Draft Confidentiality Threat Model February 2015 + + + As cookies are sent in clear text, an attacker can build a database + that associates cookies to IP addresses for non-HTTPS traffic. If + the IP address is already identified, the cookie can be linked to the + user identify. After that, if the same cookie appears on a new IP + address, the new IP address can be immediately associated with the + pre-determined identity. + +3.3.6. Graph-based approaches to address correlation + + An attacker can track traffic from an IP address not yet associated + with an individual to various public services (e.g. websites, mail + servers, game servers), and exploit patterns in the observed traffic + to correlate this address with other addresses that show similar + patterns. For example, any two addresses that show connections to + the same IMAP or webmail services, the same set of favorite websites, + and game servers at similar times of day may be associated with the + same individual. Correlated addresses can then be tied to an + individual through one of the techniques above, walking the "network + graph" to expand the set of attributable traffic. + +3.3.7. Tracking of MAC Addresses + + Moving back down the stack, technologies like Ethernet or Wi-Fi use + MAC Addresses to identify link-level destinations. MAC Addresses + assigned according to IEEE-802 standards are unique to the device. + If the link is publicly accessible, an attacker can track it. For + example, the attacker can track the wireless traffic at public Wi-Fi + networks. Simple devices can monitor the traffic, and reveal which + MAC Addresses are present. If the network does not use some form of + Wi-Fi encryption, or if the attacker can access the decrypted + traffic, the analysis will also provide the correlation between MAC + Addresses and IP addresses. Additional monitoring using techniques + exposed in the previous sections will reveal the correlation between + MAC Addresses, IP Addresses, and user identity. + + Given that large-scale databases of the MAC addresses of wireless + access points for geolocation purposes have been known to exist for + some time, the attacker could easily build a database linking MAC + Addresses and device or user identities, and use it to track the + movement of devices and of their owners. + +4. Reported Instances of Large-Scale Attacks + + The situation in reality is more bleak than that suggested by an + analysis of our idealized attacker. Through revelations of sensitive + documents in several media outlets, the Internet community has been + made aware of several intelligence activities conducted by US and UK + national intelligence agencies, particularly the US National Security + + + +Barnes, et al. Expires August 10, 2015 [Page 9] + +Internet-Draft Confidentiality Threat Model February 2015 + + + Agency (NSA) and the UK Government Communications Headquarters + (GCHQ). These documents have revealed methods that these agencies + use to attack Internet applications and obtain sensitive user + information. + + First, they have confirmed that these agencies have capabilities in + line with those of our idealized attacker, thorugh the large-scale + passive collection of Internet traffic [pass1][pass2][pass3][pass4]. + For example: - The NSA XKEYSCORE system accesses data from multiple + access points and searches for "selectors" such as email addresses, + at the scale of tens of terabytes of data per day. - The GCHQ + Tempora system appears to have access to around 1,500 major cables + passing through the UK. - The NSA MUSCULAR program tapped cables + between data centers belonging to major service providers. - Several + programs appear to perform wide-scale collection of cookies in web + traffic and location data from location-aware portable devices such + as smartphones. + + However, the capabilities described go beyond those available to our + idealized attacker, including: + + o Decryption of TLS-protected Internet sessions [dec1][dec2][dec3]. + For example, the NSA BULLRUN project appears to have had a budget + of around $250M per year to undermine encryption through multiple + approaches. + + o Insertion of NSA devices as a man-in-the-middle of Internet + transactions [TOR1][TOR2]. For example, the NSA QUANTUM system + appears to use several different techniques to hijack HTTP + connections, ranging from DNS response injection to HTTP 302 + redirects. + + o Direct acquisition of bulk data and metadata from service + providers [dir1][dir2][dir3]. For example, the NSA PRISM program + provides the agency with access to many types of user data (e.g., + email, chat, VoIP). + + o Use of implants (covert modifications or malware) to undermine + security and anonymity features [dec2][TOR1][TOR2]. For example: + + * NSA appears to use the QUANTUM man-in-the-middle system to + direct users to a FOXACID server, which delivers an implant to + compromise the browser of a user of the Tor anonymous + communications network. + + * The BULLRUN program mentioned above includes the addition of + covert modifications to software as one means to undermine + encryption. + + + +Barnes, et al. Expires August 10, 2015 [Page 10] + +Internet-Draft Confidentiality Threat Model February 2015 + + + * There is also some suspicion that NSA modifications to the + DUAL_EC_DRBG random number generator were made to ensure that + keys generated using that generator could be predicted by NSA. + These suspicions have been reinforced by reports that RSA + Security was paid roughly $10M to make DUAL_EC_DRBG the default + in their products. + + We use the term "pervasive attack" [RFC7258] to collectively describe + these operations. The term "pervasive" is used because the attacks + are designed to indiscriminately gather as much data as possible and + to apply selective analysis on targets after the fact. This means + that all, or nearly all, Internet communications are targets for + these attacks. To achieve this scale, the attacks are physically + pervasive; they affect a large number of Internet communications. + They are pervasive in content, consuming and exploiting any + information revealed by the protocol. And they are pervasive in + technology, exploiting many different vulnerabilities in many + different protocols. + + It's important to note that although the attacks mentioned above were + executed by NSA and GCHQ, there are many other organizations that can + mount pervasive surveillance attacks. Because of the resources + required to achieve pervasive scale, these attacks are most commonly + undertaken by nation-state actors. For example, the Chinese Internet + filtering system known as the "Great Firewall of China" uses several + techniques that are similar to the QUANTUM program, and which have a + high degree of pervasiveness with regard to the Internet in China. + +5. Threat Model + + Given these disclosures, we must consider a broader threat model. + + Pervasive surveillance aims to collect information across a large + number of Internet communications, analyzing the collected + communications to identify information of interest within individual + communications, or inferring information from correlated + communications. his analysis sometimes benefits from decryption of + encrypted communications and deanonymization of anonymized + communications. As a result, these attackers desire both access to + the bulk of Internet traffic and to the keying material required to + decrypt any traffic that has been encrypted. Even if keys are not + available, note that the presence of a communication and the fact + that it is encrypted may both be inputs to an analysis, even if the + attacker cannot decrypt the communication. + + The attacks listed above highlight new avenues both for access to + traffic and for access to relevant encryption keys. They further + indicate that the scale of surveillance is sufficient to provide a + + + +Barnes, et al. Expires August 10, 2015 [Page 11] + +Internet-Draft Confidentiality Threat Model February 2015 + + + general capability to cross-correlate communications, a threat not + previously thought to be relevant at the scale of the Internet. + +5.1. Attacker Capabilities + + +--------------------------+-------------------------------------+ + | Attack Class | Capability | + +--------------------------+-------------------------------------+ + | Passive observation | Directly capture data in transit | + | | | + | Passive inference | Infer from reduced/encrypted data | + | | | + | Active | Manipulate / inject data in transit | + | | | + | Static key exfiltration | Obtain key material once / rarely | + | | | + | Dynamic key exfiltration | Obtain per-session key material | + | | | + | Content exfiltration | Access data at rest | + +--------------------------+-------------------------------------+ + + Security analyses of Internet protocols commonly consider two classes + of attacker: Passive attackers, who can simply listen in on + communications as they transit the network, and active attackers, who + can modify or delete packets in addition to simply collecting them. + + In the context of pervasive passive surveillance, these attacks take + on an even greater significance. In the past, these attackers were + often assumed to operate near the edge of the network, where attacks + can be simpler. For example, in some LANs, it is simple for any node + to engage in passive listening to other nodes' traffic or inject + packets to accomplish active attacks. However, as we now know, both + passive and active attacks are undertaken by pervasive attackers + closer to the core of the network, greatly expanding the scope and + capability of the attacker. + + Eavesdropping and observation at a larger scale make passive + inference attacks easier to carry out: a passive attacker with access + to a large portion of the Internet can analyze collected traffic to + create a much more detailed view of individual behavior than an + attacker that collects at a single point. Even the usual claim that + encryption defeats passive attackers is weakened, since a pervasive + passive attacker can infer relationships from correlations over large + numbers of sessions, e.g., pairing encrypted sessions with + unencrypted sessions from the same host, or performing traffic + fingerprinting between known and unknown encrypted sessions. Reports + on the NSA XKEYSCORE system would indicate it is an example of such + an attacker. + + + +Barnes, et al. Expires August 10, 2015 [Page 12] + +Internet-Draft Confidentiality Threat Model February 2015 + + + A pervasive active attacker likewise has capabilities beyond those of + a localized active attacker. Active attacks are often limited by + network topology, for example by a requirement that the attacker be + able to see a targeted session as well as inject packets into it. A + pervasive active attacker with access at multiple points within the + core of the Internet is able to overcome these topological + limitations and perform attacks over a much broader scope. Being + positioned in the core of the network rather than the edge can also + enable a pervasive active attacker to reroute targeted traffic, + amplifying the ability to perform both eavesdropping and traffic + injection. Pervasive active attackers can also benefit from + pervasive passive collection to identify vulnerable hosts. + + While not directly related to pervasiveness, attackers that are in a + position to mount a pervasive active attack are also often in a + position to subvert authentication, a traditional protection against + such attacks. Authentication in the Internet is often achieved via + trusted third party authorities such as the Certificate Authorities + (CAs) that provide web sites with authentication credentials. An + attacker with sufficient resources may also be able to induce an + authority to grant credentials for an identity of the attacker's + choosing. If the parties to a communication will trust multiple + authorities to certify a specific identity, this attack may be + mounted by suborning any one of the authorities (the proverbial + "weakest link"). Subversion of authorities in this way can allow an + active attack to succeed in spite of an authentication check. + + Beyond these three classes (observation, inference, and active), + reports on the BULLRUN effort to defeat encryption and the PRISM + effort to obtain data from service providers suggest three more + classes of attack: + + o Static key exfiltration + + o Dynamic key exfiltration + + o Content exfiltration + + These attacks all rely on a collaborator providing the attacker with + some information, either keys or data. These attacks have not + traditionally been considered in scope for the Security + Considerations sections of IETF protocols, as they occur outside the + protocol. + + The term "key exfiltration" refers to the transfer of keying material + for an encrypted communication from the collaborator to the attacker. + By "static", we mean that the transfer of keys happens once, or + rarely, typically of a long-lived key. For example, this case would + + + +Barnes, et al. Expires August 10, 2015 [Page 13] + +Internet-Draft Confidentiality Threat Model February 2015 + + + cover a web site operator that provides the private key corresponding + to its HTTPS certificate to an intelligence agency. + + "Dynamic" key exfiltration, by contrast, refers to attacks in which + the collaborator delivers keying material to the attacker frequently, + e.g., on a per-session basis. This does not necessarily imply + frequent communications with the attacker; the transfer of keying + material may be virtual. For example, if an endpoint were modified + in such a way that the attacker could predict the state of its + psuedorandom number generator, then the attacker would be able to + derive per-session keys even without per-session communications. + + Finally, content exfiltration is the attack in which the collaborator + simply provides the attacker with the desired data or metadata. + Unlike the key exfiltration cases, this attack does not require the + attacker to capture the desired data as it flows through the network. + The risk is to data at rest as opposed to data in transit. This + increases the scope of data that the attacker can obtain, since the + attacker can access historical data - the attacker does not have to + be listening at the time the communication happens. + + Exfiltration attacks can be accomplished via attacks against one of + the parties to a communication, i.e., by the attacker stealing the + keys or content rather than the party providing them willingly. In + these cases, the party may not be aware that they are collaborating, + at least at a human level. Rather, the subverted technical assets + are "collaborating" with the attacker (by providing keys/content) + without their owner's knowledge or consent. + + Any party that has access to encryption keys or unencrypted data can + be a collaborator. While collaborators are typically the endpoints + of a communication (with encryption securing the links), + intermediaries in an unencrypted communication can also facilitate + content exfiltration attacks as collaborators by providing the + attacker access to those communications. For example, documents + describing the NSA PRISM program claim that NSA is able to access + user data directly from servers, where it is stored unencrypted. In + these cases, the operator of the server would be a collaborator, if + an unwitting one. By contrast, in the NSA MUSCULAR program, a set of + collaborators enabled attackers to access the cables connecting data + centers used by service providers such as Google and Yahoo. Because + communications among these data centers were not encrypted, the + collaboration by an intermediate entity allowed NSA to collect + unencrypted user data. + + + + + + + +Barnes, et al. Expires August 10, 2015 [Page 14] + +Internet-Draft Confidentiality Threat Model February 2015 + + +5.2. Attacker Costs + + +--------------------------+-----------------------------------+ + | Attack Class | Cost / Risk to Attacker | + +--------------------------+-----------------------------------+ + | Passive observation | Passive data access | + | | | + | Passive inference | Passive data access + processing | + | | | + | Active | Active data access + processing | + | | | + | Static key exfiltration | One-time interaction | + | | | + | Dynamic key exfiltration | Ongoing interaction / code change | + | | | + | Content exfiltration | Ongoing, bulk interaction | + +--------------------------+-----------------------------------+ + + Each of the attack types discussed in the previous section entails + certain costs and risks. These costs differ by attack, and can be + helpful in guiding response to pervasive attack. + + Depending on the attack, the attacker may be exposed to several types + of risk, ranging from simply losing access to arrest or prosecution. + In order for any of these negative consequences to occur, however, + the attacker must first be discovered and identified. So the primary + risk we focus on here is the risk of discovery and attribution. + + A passive attack is the simplest to mount in some ways. The base + requirement is that the attacker obtain physical access to a + communications medium and extract communications from it. For + example, the attacker might tap a fiber-optic cable, acquire a mirror + port on a switch, or listen to a wireless signal. The need for these + taps to have physical access or proximity to a link exposes the + attacker to the risk that the taps will be discovered. For example, + a fiber tap or mirror port might be discovered by network operators + noticing increased attenuation in the fiber or a change in switch + configuration. Of course, passive attacks may be accomplished with + the cooperation of the network operator, in which case there is a + risk that the attacker's interactions with the network operator will + be exposed. + + In many ways, the costs and risks for an active attack are similar to + those for a passive attack, with a few additions. An active attacker + requires more robust network access than a passive attacker, since + for example they will often need to transmit data as well as + receiving it. In the wireless example above, the attacker would need + to act as an transmitter as well as receiver, greatly increasing the + + + +Barnes, et al. Expires August 10, 2015 [Page 15] + +Internet-Draft Confidentiality Threat Model February 2015 + + + probability the attacker will be discovered (e.g., using direction- + finding technology). Active attacks are also much more observable at + higher layers of the network. For example, an active attacker that + attempts to use a mis-issued certificate could be detected via + Certificate Transparency [RFC6962]. + + In terms of raw implementation complexity, passive attacks require + only enough processing to extract information from the network and + store it. Active attacks, by contrast, often depend on winning race + conditions to inject pakets into active connections. So active + attacks in the core of the network require processing hardware to + that can operate at line speed (roughly 100Gbps to 1Tbps in the core) + to identify opportunities for attack and insert attack traffic in a + high-volume traffic. + Key exfiltration attacks rely on passive attack for access to + encrypted data, with the collaborator providing keys to decrypt the + data. So the attacker undertakes the cost and risk of a passive + attack, as well as additional risk of discovery via the interactions + that the attacker has with the collaborator. + + In this sense, static exfiltration has a lower risk profile than + dynamic. In the static case, the attacker need only interact with + the collaborator a small number of times, possibly only once, say to + exchange a private key. In the dynamic case, the attacker must have + continuing interactions with the collaborator. As noted above these + interactions may real, such as in-person meetings, or virtual, such + as software modifications that render keys available to the attacker. + Both of these types of interactions introduce a risk that they will + be discovered, e.g., by employees of the collaborator organization + noticing suspicious meetings or suspicious code changes. + + Content exfiltration has a similar risk profile to dynamic key + exfiltration. In a content exfiltration attack, the attacker saves + the cost and risk of conducting a passive attack. The risk of + discovery through interactions with the collaborator, however, is + still present, and may be higher. The content of a communication is + obviously larger than the key used to encrypt it, often by several + orders of magnitude. So in the content exfiltration case, the + interactions between the collaborator and the attacker need to be + much higher-bandwidth than in the key exfiltration cases, with a + corresponding increase in the risk that this high-bandwidth channel + will be discovered. + + It should also be noted that in these latter three exfiltration + cases, the collaborator also undertakes a risk that his collaboration + with the attacker will be discovered. Thus the attacker may have to + incur additional cost in order to convince the collaborator to + participate in the attack. Likewise, the scope of these attacks is + + + +Barnes, et al. Expires August 10, 2015 [Page 16] + +Internet-Draft Confidentiality Threat Model February 2015 + + + limited to case where the attacker can convince a collaborator to + participate. If the attacker is a national government, for example, + it may be able to compel participation within its borders, but have a + much more difficult time recruiting foreign collaborators. + + As noted above, the collaborator in an exfiltration attack can be + unwitting; the attacker can steal keys or data to enable the attack. + In some ways, the risks of this approach are similar to the case of + an active collaborator. In the static case, the attacker needs to + steal information from the collaborator once; in the dynamic case, + the attacker needs to continued presence inside the collaborators + systems. The main difference is that the risk in this case is of + automated discovery (e.g., by intrusion detection systems) rather + than discovery by humans. + +6. Security Considerations + + This document describes a threat model for pervasive surveillance + attacks. Mitigations are to be given in a future document. + +7. IANA Considerations + + This document has no actions for IANA. + +8. Acknowledgements + + Thanks to Dave Thaler for the list of attacks and taxonomy; to + Security Area Directors Stephen Farrell, Sean Turner, and Kathleen + Moriarty for starting and managing the IETF's discussion on pervasive + attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, + Evangelos Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, as well as + the IAB Privacy and Security Program, for their input. + +9. References + +9.1. Normative References + + [RFC6973] Cooper, A., Tschofenig, H., Aboba, B., Peterson, J., + Morris, J., Hansen, M., and R. Smith, "Privacy + Considerations for Internet Protocols", RFC 6973, July + 2013. + +9.2. Informative References + + [pass1] The Guardian, "How the NSA is still harvesting your online + data", 2013, + . + + + +Barnes, et al. Expires August 10, 2015 [Page 17] + +Internet-Draft Confidentiality Threat Model February 2015 + + + [pass2] The Guardian, "NSA's Prism surveillance program: how it + works and what it can do", 2013, + . + + [pass3] The Guardian, "XKeyscore: NSA tool collects 'nearly + everything a user does on the internet'", 2013, + . + + [pass4] The Guardian, "How does GCHQ's internet surveillance + work?", n.d., . + + [dec1] The New York Times, "N.S.A. Able to Foil Basic Safeguards + of Privacy on Web", 2013, + . + + [dec2] The Guardian, "Project Bullrun - classification guide to + the NSA's decryption program", 2013, + . + + [dec3] The Guardian, "Revealed: how US and UK spy agencies defeat + internet privacy and security", 2013, + . + + [TOR] The Tor Project, "Tor", 2013, + . + + [TOR1] Schneier, B., "How the NSA Attacks Tor/Firefox Users With + QUANTUM and FOXACID", 2013, + . + + [TOR2] The Guardian, "'Tor Stinks' presentation - read the full + document", 2013, + . + + [dir1] The Guardian, "NSA collecting phone records of millions of + Verizon customers daily", 2013, + . + + + + + +Barnes, et al. Expires August 10, 2015 [Page 18] + +Internet-Draft Confidentiality Threat Model February 2015 + + + [dir2] The Guardian, "NSA Prism program taps in to user data of + Apple, Google and others", 2013, + . + + [dir3] The Guardian, "Sigint - how the NSA collaborates with + technology companies", 2013, + . + + [secure] Schneier, B., "NSA surveillance: A guide to staying + secure", 2013, + . + + [snowden] Technology Review, "NSA Leak Leaves Crypto-Math Intact but + Highlights Known Workarounds", 2013, + . + + [key-recovery] + Golle, P., "The Design and Implementation of Protocol- + Based Hidden Key Recovery", 2003, + . + + [RFC1035] Mockapetris, P., "Domain names - implementation and + specification", STD 13, RFC 1035, November 1987. + + [RFC1918] Rekhter, Y., Moskowitz, R., Karrenberg, D., Groot, G., and + E. Lear, "Address Allocation for Private Internets", BCP + 5, RFC 1918, February 1996. + + [RFC1939] Myers, J. and M. Rose, "Post Office Protocol - Version 3", + STD 53, RFC 1939, May 1996. + + [RFC2015] Elkins, M., "MIME Security with Pretty Good Privacy + (PGP)", RFC 2015, October 1996. + + [RFC2821] Klensin, J., "Simple Mail Transfer Protocol", RFC 2821, + April 2001. + + [RFC3261] Rosenberg, J., Schulzrinne, H., Camarillo, G., Johnston, + A., Peterson, J., Sparks, R., Handley, M., and E. + Schooler, "SIP: Session Initiation Protocol", RFC 3261, + June 2002. + + + + + +Barnes, et al. Expires August 10, 2015 [Page 19] + +Internet-Draft Confidentiality Threat Model February 2015 + + + [RFC3365] Schiller, J., "Strong Security Requirements for Internet + Engineering Task Force Standard Protocols", BCP 61, RFC + 3365, August 2002. + + [RFC3501] Crispin, M., "INTERNET MESSAGE ACCESS PROTOCOL - VERSION + 4rev1", RFC 3501, March 2003. + + [RFC3851] Ramsdell, B., "Secure/Multipurpose Internet Mail + Extensions (S/MIME) Version 3.1 Message Specification", + RFC 3851, July 2004. + + [RFC4033] Arends, R., Austein, R., Larson, M., Massey, D., and S. + Rose, "DNS Security Introduction and Requirements", RFC + 4033, March 2005. + + [RFC4301] Kent, S. and K. Seo, "Security Architecture for the + Internet Protocol", RFC 4301, December 2005. + + [RFC4303] Kent, S., "IP Encapsulating Security Payload (ESP)", RFC + 4303, December 2005. + + [RFC4306] Kaufman, C., "Internet Key Exchange (IKEv2) Protocol", RFC + 4306, December 2005. + + [RFC4949] Shirey, R., "Internet Security Glossary, Version 2", RFC + 4949, August 2007. + + [RFC5246] Dierks, T. and E. Rescorla, "The Transport Layer Security + (TLS) Protocol Version 1.2", RFC 5246, August 2008. + + [RFC5321] Klensin, J., "Simple Mail Transfer Protocol", RFC 5321, + October 2008. + + [RFC5655] Trammell, B., Boschi, E., Mark, L., Zseby, T., and A. + Wagner, "Specification of the IP Flow Information Export + (IPFIX) File Format", RFC 5655, October 2009. + + [RFC5750] Ramsdell, B. and S. Turner, "Secure/Multipurpose Internet + Mail Extensions (S/MIME) Version 3.2 Certificate + Handling", RFC 5750, January 2010. + + [RFC6120] Saint-Andre, P., "Extensible Messaging and Presence + Protocol (XMPP): Core", RFC 6120, March 2011. + + [RFC6962] Laurie, B., Langley, A., and E. Kasper, "Certificate + Transparency", RFC 6962, June 2013. + + + + + +Barnes, et al. Expires August 10, 2015 [Page 20] + +Internet-Draft Confidentiality Threat Model February 2015 + + + [RFC6698] Hoffman, P. and J. Schlyter, "The DNS-Based Authentication + of Named Entities (DANE) Transport Layer Security (TLS) + Protocol: TLSA", RFC 6698, August 2012. + + [RFC7011] Claise, B., Trammell, B., and P. Aitken, "Specification of + the IP Flow Information Export (IPFIX) Protocol for the + Exchange of Flow Information", STD 77, RFC 7011, September + 2013. + + [RFC7258] Farrell, S. and H. Tschofenig, "Pervasive Monitoring Is an + Attack", BCP 188, RFC 7258, May 2014. + +Authors' Addresses + + Richard Barnes + + Email: rlb@ipv.sx + + + Bruce Schneier + + Email: schneier@schneier.com + + + Cullen Jennings + + Email: fluffy@cisco.com + + + Ted Hardie + + Email: ted.ietf@gmail.com + + + Brian Trammell + + Email: ietf@trammell.ch + + + Christian Huitema + + Email: huitema@huitema.net + + + Daniel Borkmann + + Email: dborkman@redhat.com + + + + +Barnes, et al. Expires August 10, 2015 [Page 21] diff --git a/draft-iab-privsec-confidentiality-threat-02.xml b/draft-iab-privsec-confidentiality-threat-02.xml new file mode 100644 index 0000000..02fa46e --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-02.xml @@ -0,0 +1,572 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +]> + + + + + + Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement + + + +
+ rlb@ipv.sx +
+ + + +
+ schneier@schneier.com +
+ + + +
+ fluffy@cisco.com +
+ + + +
+ ted.ietf@gmail.com +
+ + + +
+ ietf@trammell.ch +
+ + + +
+ huitema@huitema.net +
+ + + +
+ dborkman@redhat.com +
+ + + + + + + + + + + +Documents published in 2013 revealed several classes of pervasive surveillance attack on Internet communications. In this document we develop a threat model that describes these pervasive attacks. We start by assuming a completely passive attacker with an interest in undetected, indiscriminate eavesdropping, then expand the threat model with a set of verified attacks that have been published. + + + + + + + + + + + +
+ +Starting in June 2013, documents released to the press by Edward Snowden have revealed several operations undertaken by intelligence agencies to exploit Internet communications for intelligence purposes. These attacks were largely based on protocol vulnerabilities that were already known to exist. The attacks were nonetheless striking in their pervasive nature, both in terms of the amount of Internet communications targeted, and in terms of the diversity of attack techniques employed. + +To ensure that the Internet can be trusted by users, it is necessary for the Internet technical community to address the vulnerabilities exploited in these attacks . The goal of this document is to describe more precisely the threats posed by these pervasive attacks, and based on those threats, lay out the problems that need to be solved in order to secure the Internet in the face of those threats. + +The remainder of this document is structured as follows. In , we describe an idealized passive attacker, one which could completely undetectably compromise communications at Internet scale. In , we provide a brief summary of some attacks that have been disclosed, and use these to expand the assumed capabilities of our idealized attacker. describes a threat model based on these attacks, focusing on classes of attack that have not been a focus of Internet engineering to date. + +
+
+ +This document makes extensive use of standard security and privacy terminology; see and . Terms used from include Eavesdropper, Observer, Initiator, Intermediary, Recipient, Attack (in a privacy context), Correlation, Fingerprint, Traffic Analysis, and Identifiability (and related terms). In addition, we use a few terms that are specific to the attacks discussed here: + + + + In this document, the term passive attack is used with respect to the traffic stream: a passive attack does not modify the packets in the traffic stream between two endpoints, modify the treatment of packets in the traffic stream (e.g. delay, routing), or add or remove packets in the traffic stream. Passive attacks are undetectable from the endpoints. + + In constrast to a passive attack, and active attack may modify a traffic stream, at the cost of possible detection at the endpoints. + + An attack on Internet communications that makes use of access at a large number of points in the network, or otherwise provides the attacker with access to a large amount of Internet traffic; see + + Information collected directly from communications by an eavesdropper or observer. For example, the knowledge that <alice@example.com> sent a message to <bob@example.com> via SMTP taken from the headers of an observed SMTP message would be an observation. + + Information extracted from analysis of information collected directly from communications by an eavesdropper or observer. For example, the knowledge that a given web page was accessed by a given IP address, by comparing the size in octets of measured network flow records to fingerprints derived from known sizes of linked resources on the web servers involved, would be an +inference. + + An entity that is a legitimate participant in a communication, but who deliberately provides information about that interaction to an attacker. + + An entity that is a legitimate participant in a communication, and who is the source of information obtained by the attacker without the entity’s consent or intention, because the attacker has exploited some technology used by the entity. + + The transmission of keying material for an encrypted communication from a collaborator, deliberately or unwittingly, to an attacker + + The transmission of the content of a communication from a collaborator, deliberately or unwittingly, to an attacker + + +
+
+ +In considering the threat posed by pervasive surveillance, we begin by defining an idealized pervasive passive attacker. While this attacker is less capable than those which we now know to have compromised the Internet from press reports, as elaborated in , it does set a lower bound on the capabilities of an attacker interested in indiscriminate passive surveillance while interested in remaining undetectable. We note that, prior to the Snowden revelations in 2013, the assumptions of attacker capability presented here would be considered on the border of paranoia outside the network security community. + +Our idealized attacker is an indiscriminate eavesdropper on an Internet-attached computer network that: + + + can observe every packet of all communications at any hop in any network path between an initiator and a recipient; + can observe data at rest in any intermediate system between the endpoints controlled by the initiator and recipient; and + can share information with other such attackers; but + takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.). + + +The techniques available to our ideal attacker are direct observation and inference. Direct observation involves taking information directly from eavesdropped communications - e.g., URLs identifying content or email addresses identifying individuals from application-layer headers. Inference, on the other hand, involves analyzing eavesdropped information to derive new information from it; e.g., searching for application or behavioral fingerprints in observed traffic to derive information about the observed individual from them, in absence of directly-observed sources of the same information. The use of encryption to protect confidentiality is generally enough to prevent direct observation of unencrypted content, assuming uncompromised encryption implementations and key material. However, it provides less complete protection against inference, especially inference based only on unprotected portions of communications (e.g. IP and TCP headers for TLS ). + +
+ +Protocols which do not encrypt their payload make the entire content of the communication available to the idealized attacker along their path. Following the advice in , most such protocols have a secure variant which encrypts payload for confidentiality, and these secure variants are seeing ever-wider deployment. A noteworthy exception is DNS , as DNSSEC does not have confidentiality as a requirement. This implies that, in the absence of changes to the protocol as presently under development in the DPRIVE working group, all DNS queries and answers generated by the activities of any protocol are available to the attacker. + +Protocols which imply the storage of some data at rest in intermediaries (e.g. SMTP ) leave this data subject to observation by an attacker that has compromised these intermediaries, unless the data is encrypted end-to-end by the application layer protocol, or the implementation uses an encrypted store for this data. + +
+
+ +Inference is information extracted from later analysis of an observed or eavesdropped communication, and/or correlation of observed or eavesdropped information with information available from other sources. Indeed, most useful inference performed by the attacker falls under the rubric of correlation. The simplest example of this is the observation of DNS queries and answers from and to a source and correlating those with IP addresses with which that source communicates. This can give access to information otherwise not available from encrypted application payloads (e.g., the Host: HTTP/1.1 request header when HTTP is used with TLS). + +Protocols which encrypt their payload using an application- or transport-layer encryption scheme (e.g. TLS) still expose all the information in their network and transport layer headers to the attacker, including source and destination addresses and ports. IPsec ESP further encrypts the transport-layer headers, but still leaves IP address information unencrypted; in tunnel mode, these addresses correspond to the tunnel endpoints. Features of the cryptographic protocols themselves, e.g. the TLS session identifier, may leak information that can be used for correlation and inference. While this information is much less semantically rich than the application payload, it can still be useful for the inferring an individual’s activities. + +Inference can also leverage information obtained from sources other than direct traffic observation. Geolocation databases, for example, have been developed map IP addresses to a location, in order to provide location-aware services such as targeted advertising. This location information is often of sufficient resolution that it can be used to draw further inferences toward identifying or profiling an individual. + +Social media provide another source of more or less publicly accessible information. This information can be extremely semantically rich, including information about an individual’s location, associations with other individuals and groups, and activities. Further, this information is generally contributed and curated voluntarily by the individuals themselves: it represents information which the individuals are not necessarily interested in protecting for privacy reasons. However, correlation of this social networking data with information available from direct observation of network traffic allows the creation of a much richer picture of an individual’s activities than either alone. + +We note with some alarm that there is little that can be done at protocol design time to limit such correlation by the attacker, and that the existence of such data sources in many cases greatly complicates the problem of protecting privacy by hardening protocols alone. + +
+
+ +To illustrate how capable the idealized attacker is even given its limitations, we explore the non-anonymity of encrypted IP traffic in this section. Here we examine in detail some inference techniques for associating a set of addresses with an individual, in order to illustrate the difficulty of defending communications against our idealized attacker. Here, the basic problem is that information radiated even from protocols which have no obvious connection with personal data can be correlated with other information which can paint a very rich behavioral picture, that only takes one unprotected link in the chain to associate with an identity. + +
+ +Internet traffic can be monitored by tapping Internet links, or by installing monitoring tools in Internet routers. Of course, a single link or a single router only provides access to a fraction of the global Internet traffic. However, monitoring a number of high capacity links or a set of routers placed at strategic locations provides access to a good sampling of Internet traffic. + +Tools like IPFIX allow administrators to acquire statistics about sequences of packets with some common properties that pass through a network device. The most common set of properties used in flow measurement is the “five-tuple”of source and destination addresses, protocol type, and source and destination ports. These statistics are commonly used for network engineering, but could certainly be used for other purposes. + +Let’s assume for a moment that IP addresses can be correlated to specific services or specific users. Analysis of the sequences of packets will quickly reveal which users use what services, and also which users engage in peer-to-peer connections with other users. Analysis of traffic variations over time can be used to detect increased activity by particular users, or in the case of peer-to-peer connections increased activity within groups of users. + +
+
+ +The correlation of IP addresses with specific users can be done in various ways. For example, tools like reverse DNS lookup can be used to retrieve the DNS names of servers. Since the addresses of servers tend to be quite stable and since servers are relatively less numerous than users, an attacker could easily maintain its own copy of the DNS for well-known or popular servers, to accelerate such lookups. + +On the other hand, the reverse lookup of IP addresses of users is generally less informative. For example, a lookup of the address currently used by one author’s home network returns a name of the form “c-192-000-002-033.hsd1.wa.comcast.net”. This particular type of reverse DNS lookup generally reveals only coarse-grained location or provider information, equivalent to that available from geolocation databases. + +In many jurisdictions, Internet Service Providers (ISPs) are required to provide identification on a case by case basis of the “owner” of a specific IP address for law enforcement purposes. This is a reasonably expedient process for targeted investigations, but pervasive surveillance requires something more efficient. This provides an incentive for the attacker to secure the cooperation of the ISP in order to automate this correlation. + +
+
+ +Even if the ISP does not cooperate, user identity can often be obtained via inference. POP3 and IMAP are used to retrieve mail from mail servers, while a variant of SMTP is used to submit messages through mail servers. IMAP connections originate from the client, and typically start with an authentication exchange in which the client proves its identity by answering a password challenge. The same holds for the SIP protocol and many instant messaging services operating over the Internet using proprietary protocols. + +The username is directly observable if any of these protocols operate in cleartext; the username can then be directly associated with the source address. + +
+
+ +SMTP requires that each successive SMTP relay adds a “Received” header to the mail headers. The purpose of these headers is to enable audit of mail transmission, and perhaps to distinguish between regular mail and spam. Here is an extract from the headers of a message recently received from the “perpass” mailing list: + + + Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?) + (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA + (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100 + Message-ID: <526D7BD2.7070908@example.org> + Date: Sun, 27 Oct 2013 20:47:14 +0000 + From: Some One <some.one@example.org> + + +This is the first “Received” header attached to the message by the first SMTP relay; for privacy reasons, the field values have been anonymized. We learn here that the message was submitted by “Some One” on October 27, from a host behind a NAT (192.168.1.100) that used the IP address 192.0.2.44. The information remained in the message, and is accessible by all recipients of the “perpass” mailing list, or indeed by any attacker that sees at least one copy of the message. + +An attacker that can observe sufficient email traffic can regularly update the mapping between public IP addresses and individual email identities. Even if the SMTP traffic was encrypted on submission and relaying, the attacker can still receive a copy of public mailing lists like “perpass”. + +
+
+ +Many web sites only encrypt a small fraction of their transactions. A popular pattern is to use HTTPS for the login information, and then use a “cookie” to associate following clear-text transactions with the user’s identity. Cookies are also used by various advertisement services to quickly identify the users and serve them with “personalized” advertisements. Such cookies are particularly useful if the advertisement services want to keep tracking the user across multiple sessions that may use different IP addresses. + +As cookies are sent in clear text, an attacker can build a database that associates cookies to IP addresses for non-HTTPS traffic. If the IP address is already identified, the cookie can be linked to the user identify. After that, if the same cookie appears on a new IP address, the new IP address can be immediately associated with the pre-determined identity. + +
+
+ +An attacker can track traffic from an IP address not yet associated with an individual to various public services (e.g. websites, mail servers, game servers), and exploit patterns in the observed traffic to correlate this address with other addresses that show similar patterns. For example, any two addresses that show connections to the same IMAP or webmail services, the same set of favorite websites, and game servers at similar times of day may be associated with the same individual. Correlated addresses can then be tied to an individual through one of the techniques above, walking the “network graph” to expand the set of attributable traffic. + +
+
+ +Moving back down the stack, technologies like Ethernet or Wi-Fi use MAC Addresses to identify link-level destinations. MAC Addresses assigned according to IEEE-802 standards are unique to the device. If the link is publicly accessible, an attacker can track it. For example, the attacker can track the wireless traffic at public Wi-Fi networks. Simple devices can monitor the traffic, and reveal which MAC Addresses are present. If the network does not use some form of Wi-Fi encryption, or if the attacker can access the decrypted traffic, the analysis will also provide the correlation between MAC Addresses and IP addresses. Additional monitoring using techniques exposed in the previous sections will reveal the correlation between MAC Addresses, IP Addresses, and user identity. + +Given that large-scale databases of the MAC addresses of wireless access points for geolocation purposes have been known to exist for some time, the attacker could easily build a database linking MAC Addresses and device or user identities, and use it to track the movement of devices and of their owners. + +
+
+
+
+ +The situation in reality is more bleak than that suggested by an analysis of our idealized attacker. Through revelations of sensitive documents in several media outlets, the Internet community has been made aware of several intelligence activities conducted by US and UK national intelligence agencies, particularly the US National Security Agency (NSA) and the UK Government Communications Headquarters (GCHQ). These documents have revealed methods that these agencies use to attack Internet applications and obtain sensitive user information. + +First, they have confirmed that these agencies have capabilities in line with those of our idealized attacker, thorugh the large-scale passive collection of Internet traffic . For example: + - The NSA XKEYSCORE system accesses data from multiple access points and searches for “selectors” such as email addresses, at the scale of tens of terabytes of data per day. + - The GCHQ Tempora system appears to have access to around 1,500 major cables passing through the UK. + - The NSA MUSCULAR program tapped cables between data centers belonging to major service providers. + - Several programs appear to perform wide-scale collection of cookies in web traffic and location data from location-aware portable devices such as smartphones. + +However, the capabilities described go beyond those available to our idealized attacker, including: + + + Decryption of TLS-protected Internet sessions . For example, the NSA BULLRUN project appears to have had a budget of around $250M per year to undermine encryption through multiple approaches. + Insertion of NSA devices as a man-in-the-middle of Internet transactions . For example, the NSA QUANTUM system appears to use several different techniques to hijack HTTP connections, ranging from DNS response injection to HTTP 302 redirects. + Direct acquisition of bulk data and metadata from service providers . For example, the NSA PRISM program provides the agency with access to many types of user data (e.g., email, chat, VoIP). + Use of implants (covert modifications or malware) to undermine security and anonymity features . For example: + NSA appears to use the QUANTUM man-in-the-middle system to direct users to a FOXACID server, which delivers an implant to compromise the browser of a user of the Tor anonymous communications network. + The BULLRUN program mentioned above includes the addition of covert modifications to software as one means to undermine encryption. + There is also some suspicion that NSA modifications to the DUAL_EC_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA. These suspicions have been reinforced by reports that RSA Security was paid roughly $10M to make DUAL_EC_DRBG the default in their products. + + + +We use the term “pervasive attack” to collectively describe these operations. The term “pervasive” is used because the attacks are designed to indiscriminately gather as much data as possible and to apply selective analysis on targets after the fact. This means that all, or nearly all, Internet communications are targets for these attacks. To achieve this scale, the attacks are physically pervasive; they affect a large number of Internet communications. They are pervasive in content, consuming and exploiting any information revealed by the protocol. And they are pervasive in technology, exploiting many different vulnerabilities in many different protocols. + +It’s important to note that although the attacks mentioned above were executed by NSA and GCHQ, there are many other organizations that can mount pervasive surveillance attacks. Because of the resources required to achieve pervasive scale, these attacks are most commonly undertaken by nation-state actors. For example, the Chinese Internet filtering system known as the “Great Firewall of China” uses several techniques that are similar to the QUANTUM program, and which have a high degree of pervasiveness with regard to the Internet in China. + +
+
+ +Given these disclosures, we must consider a broader threat model. + +Pervasive surveillance aims to collect information across a large number of Internet communications, analyzing the collected communications to identify information of interest within individual communications, or inferring information from correlated communications. his analysis sometimes benefits from decryption of encrypted communications and deanonymization of anonymized communications. As a result, these attackers desire both access to the bulk of Internet traffic and to the keying material required to decrypt any traffic that has been encrypted. Even if keys are not available, note that the presence of a communication and the fact that it is encrypted may both be inputs to an analysis, even if the attacker cannot decrypt the communication. + +The attacks listed above highlight new avenues both for access to traffic and for access to relevant encryption keys. They further indicate that the scale of surveillance is sufficient to provide a general capability to cross-correlate communications, a threat not previously thought to be relevant at the scale of the Internet. + +
+ + + Attack Class + Capability + Passive observation + Directly capture data in transit + Passive inference + Infer from reduced/encrypted data + Active + Manipulate / inject data in transit + Static key exfiltration + Obtain key material once / rarely + Dynamic key exfiltration + Obtain per-session key material + Content exfiltration + Access data at rest + + +Security analyses of Internet protocols commonly consider two classes of attacker: Passive attackers, who can simply listen in on communications as they transit the network, and active attackers, who can modify or delete packets in addition to simply collecting them. + +In the context of pervasive passive surveillance, these attacks take on an even greater significance. In the past, these attackers were often assumed to operate near the edge of the network, where attacks can be simpler. For example, in some LANs, it is simple for any node to engage in passive listening to other nodes’ traffic or inject packets to accomplish active attacks. However, as we now know, both passive and active attacks are undertaken by pervasive attackers closer to the core of the network, greatly expanding the scope and capability of the attacker. + +Eavesdropping and observation at a larger scale make passive inference attacks easier to carry out: a passive attacker with access to a large portion of the Internet can analyze collected traffic to create a much more detailed view of individual behavior than an attacker that collects at a single point. Even the usual claim that encryption defeats passive attackers is weakened, since a pervasive passive attacker can infer relationships from correlations over large numbers of sessions, e.g., pairing encrypted sessions with unencrypted sessions from the same host, or performing traffic fingerprinting between known and unknown encrypted sessions. Reports on the NSA XKEYSCORE system would indicate it is an example of such an attacker. + +A pervasive active attacker likewise has capabilities beyond those of a localized active attacker. Active attacks are often limited by network topology, for example by a requirement that the attacker be able to see a targeted session as well as inject packets into it. A pervasive active attacker with access at multiple points within the core of the Internet is able to overcome these topological limitations and perform attacks over a much broader scope. Being positioned in the core of the network rather than the edge can also enable a pervasive active attacker to reroute targeted traffic, amplifying the ability to perform both eavesdropping and traffic injection. Pervasive active attackers can also benefit from pervasive passive collection to identify vulnerable hosts. + +While not directly related to pervasiveness, attackers that are in a position to mount a pervasive active attack are also often in a position to subvert authentication, a traditional protection against such attacks. Authentication in the Internet is often achieved via trusted third party authorities such as the Certificate Authorities (CAs) that provide web sites with authentication credentials. An attacker with sufficient resources may also be able to induce an authority to grant credentials for an identity of the attacker’s choosing. If the parties to a communication will trust multiple authorities to certify a specific identity, this attack may be mounted by suborning any one of the authorities (the proverbial “weakest link”). Subversion of authorities in this way can allow an active attack to succeed in spite of an authentication check. + +Beyond these three classes (observation, inference, and active), reports on the BULLRUN effort to defeat encryption and the PRISM effort to obtain data from service providers suggest three more classes of attack: + + + Static key exfiltration + Dynamic key exfiltration + Content exfiltration + + +These attacks all rely on a collaborator providing the attacker with some information, either keys or data. These attacks have not traditionally been considered in scope for the Security Considerations sections of IETF protocols, as they occur outside the protocol. + +The term “key exfiltration” refers to the transfer of keying material for an encrypted communication from the collaborator to the attacker. By “static”, we mean that the transfer of keys happens once, or rarely, typically of a long-lived key. For example, this case would cover a web site operator that provides the private key corresponding to its HTTPS certificate to an intelligence agency. + +“Dynamic” key exfiltration, by contrast, refers to attacks in which the collaborator delivers keying material to the attacker frequently, e.g., on a per-session basis. This does not necessarily imply frequent communications with the attacker; the transfer of keying material may be virtual. For example, if an endpoint were modified in such a way that the attacker could predict the state of its psuedorandom number generator, then the attacker would be able to derive per-session keys even without per-session communications. + +Finally, content exfiltration is the attack in which the collaborator simply provides the attacker with the desired data or metadata. Unlike the key exfiltration cases, this attack does not require the attacker to capture the desired data as it flows through the network. The risk is to data at rest as opposed to data in transit. This increases the scope of data that the attacker can obtain, since the attacker can access historical data – the attacker does not have to be listening at the time the communication happens. + +Exfiltration attacks can be accomplished via attacks against one of the parties to a communication, i.e., by the attacker stealing the keys or content rather than the party providing them willingly. In these cases, the party may not be aware that they are collaborating, at least at a human level. Rather, the subverted technical assets are “collaborating” with the attacker (by providing keys/content) without their owner’s knowledge or consent. + +Any party that has access to encryption keys or unencrypted data can be a collaborator. While collaborators are typically the endpoints of a communication (with encryption securing the links), intermediaries in an unencrypted communication can also facilitate content exfiltration attacks as collaborators by providing the attacker access to those communications. For example, documents describing the NSA PRISM program claim that NSA is able to access user data directly from servers, where it is stored unencrypted. In these cases, the operator of the server would be a collaborator, if an unwitting one. By contrast, in the NSA MUSCULAR program, a set of collaborators enabled attackers to access the cables connecting data centers used by service providers such as Google and Yahoo. Because communications among these data centers were not encrypted, the collaboration by an intermediate entity allowed NSA to collect unencrypted user data. + +
+
+ + + Attack Class + Cost / Risk to Attacker + Passive observation + Passive data access + Passive inference + Passive data access + processing + Active + Active data access + processing + Static key exfiltration + One-time interaction + Dynamic key exfiltration + Ongoing interaction / code change + Content exfiltration + Ongoing, bulk interaction + + +Each of the attack types discussed in the previous section entails certain costs and risks. These costs differ by attack, and can be helpful in guiding response to pervasive attack. + +Depending on the attack, the attacker may be exposed to several types of risk, ranging from simply losing access to arrest or prosecution. In order for any of these negative consequences to occur, however, the attacker must first be discovered and identified. So the primary risk we focus on here is the risk of discovery and attribution. + +A passive attack is the simplest to mount in some ways. The base requirement is that the attacker obtain physical access to a communications medium and extract communications from it. For example, the attacker might tap a fiber-optic cable, acquire a mirror port on a switch, or listen to a wireless signal. The need for these taps to have physical access or proximity to a link exposes the attacker to the risk that the taps will be discovered. For example, a fiber tap or mirror port might be discovered by network operators noticing increased attenuation in the fiber or a change in switch configuration. Of course, passive attacks may be accomplished with the cooperation of the network operator, in which case there is a risk that the attacker’s interactions with the network operator will be exposed. + +In many ways, the costs and risks for an active attack are similar to those for a passive attack, with a few additions. An active attacker requires more robust network access than a passive attacker, since for example they will often need to transmit data as well as receiving it. In the wireless example above, the attacker would need to act as an transmitter as well as receiver, greatly increasing the probability the attacker will be discovered (e.g., using direction-finding technology). Active attacks are also much more observable at higher layers of the network. For example, an active attacker that attempts to use a mis-issued certificate could be detected via Certificate Transparency . + +In terms of raw implementation complexity, passive attacks require only enough processing to extract information from the network and store it. Active attacks, by contrast, often depend on winning race conditions to inject pakets into active connections. So active attacks in the core of the network require processing hardware to that can operate at line speed (roughly 100Gbps to 1Tbps in the core) to identify opportunities for attack and insert attack traffic in a high-volume traffic. +Key exfiltration attacks rely on passive attack for access to encrypted data, with the collaborator providing keys to decrypt the data. So the attacker undertakes the cost and risk of a passive attack, as well as additional risk of discovery via the interactions that the attacker has with the collaborator. + +In this sense, static exfiltration has a lower risk profile than dynamic. In the static case, the attacker need only interact with the collaborator a small number of times, possibly only once, say to exchange a private key. In the dynamic case, the attacker must have continuing interactions with the collaborator. As noted above these interactions may real, such as in-person meetings, or virtual, such as software modifications that render keys available to the attacker. Both of these types of interactions introduce a risk that they will be discovered, e.g., by employees of the collaborator organization noticing suspicious meetings or suspicious code changes. + +Content exfiltration has a similar risk profile to dynamic key exfiltration. In a content exfiltration attack, the attacker saves the cost and risk of conducting a passive attack. The risk of discovery through interactions with the collaborator, however, is still present, and may be higher. The content of a communication is obviously larger than the key used to encrypt it, often by several orders of magnitude. So in the content exfiltration case, the interactions between the collaborator and the attacker need to be much higher-bandwidth than in the key exfiltration cases, with a corresponding increase in the risk that this high-bandwidth channel will be discovered. + +It should also be noted that in these latter three exfiltration cases, the collaborator also undertakes a risk that his collaboration with the attacker will be discovered. Thus the attacker may have to incur additional cost in order to convince the collaborator to participate in the attack. Likewise, the scope of these attacks is limited to case where the attacker can convince a collaborator to participate. If the attacker is a national government, for example, it may be able to compel participation within its borders, but have a much more difficult time recruiting foreign collaborators. + +As noted above, the collaborator in an exfiltration attack can be unwitting; the attacker can steal keys or data to enable the attack. In some ways, the risks of this approach are similar to the case of an active collaborator. In the static case, the attacker needs to steal information from the collaborator once; in the dynamic case, the attacker needs to continued presence inside the collaborators systems. The main difference is that the risk in this case is of automated discovery (e.g., by intrusion detection systems) rather than discovery by humans. + +
+
+
+ +This document describes a threat model for pervasive surveillance attacks. Mitigations are to be given in a future document. + +
+
+ +This document has no actions for IANA. + +
+
+ +Thanks to Dave Thaler for the list of attacks and taxonomy; to Security Area Directors Stephen Farrell, Sean Turner, and Kathleen Moriarty for starting and managing the IETF’s discussion on pervasive attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, Evangelos Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, as well as the IAB Privacy and Security Program, for their input. + +
+ + + + + + + + +&RFC6973; + + + + + + + + + How the NSA is still harvesting your online data + + The Guardian + + + + + + + NSA's Prism surveillance program: how it works and what it can do + + The Guardian + + + + + + + XKeyscore: NSA tool collects 'nearly everything a user does on the internet' + + The Guardian + + + + + + + How does GCHQ's internet surveillance work? + + The Guardian + + + + + + + N.S.A. Able to Foil Basic Safeguards of Privacy on Web + + The New York Times + + + + + + + Project Bullrun – classification guide to the NSA's decryption program + + The Guardian + + + + + + + Revealed: how US and UK spy agencies defeat internet privacy and security + + The Guardian + + + + + + + Tor + + The Tor Project + + + + + + + How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID + + + + + + + + + 'Tor Stinks' presentation – read the full document + + The Guardian + + + + + + + NSA collecting phone records of millions of Verizon customers daily + + The Guardian + + + + + + + NSA Prism program taps in to user data of Apple, Google and others + + The Guardian + + + + + + + Sigint – how the NSA collaborates with technology companies + + The Guardian + + + + + + + NSA surveillance: A guide to staying secure + + The Guardian + + + + + + + NSA Leak Leaves Crypto-Math Intact but Highlights Known Workarounds + + Technology Review + + + + + + + The Design and Implementation of Protocol-Based Hidden Key Recovery + + + + + + +&RFC1035; +&RFC1918; +&RFC1939; +&RFC2015; +&RFC2821; +&RFC3261; +&RFC3365; +&RFC3501; +&RFC3851; +&RFC4033; +&RFC4301; +&RFC4303; +&RFC4306; +&RFC4949; +&RFC5246; +&RFC5321; +&RFC5655; +&RFC5750; +&RFC6120; +&RFC6962; +&RFC6698; +&RFC7011; +&RFC7258; + + + + + + + + + diff --git a/draft-iab-privsec-confidentiality-threat-03.md b/draft-iab-privsec-confidentiality-threat-03.md new file mode 100644 index 0000000..b3bad71 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-03.md @@ -0,0 +1,951 @@ +--- +title: "Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement" +abbrev: Confidentiality Threat Model +docname: draft-iab-privsec-confidentiality-threat-03 +date: 2015-02-20 +category: info +ipr: trust200902 + +author: + - + ins: R. Barnes + name: Richard Barnes + email: rlb@ipv.sx + - + ins: B. Schneier + name: Bruce Schneier + email: schneier@schneier.com + - + ins: C. Jennings + name: Cullen Jennings + email: fluffy@cisco.com + - + ins: T. Hardie + name: Ted Hardie + email: ted.ietf@gmail.com + - + ins: B. Trammell + name: Brian Trammell + email: ietf@trammell.ch + - + ins: C. Huitema + name: Christian Huitema + email: huitema@huitema.net + - + ins: D. Borkmann + name: Daniel Borkmann + email: dborkman@redhat.com + +normative: + RFC6973: + +informative: + pass1: + target: http://www.theguardian.com/world/2013/jun/27/nsa-online-metadata-collection + title: "How the NSA is still harvesting your online data" + author: + organization: The Guardian + date: 2013 + pass2: + target: http://www.theguardian.com/world/2013/jun/08/nsa-prism-server-collection-facebook-google + title: "NSA's Prism surveillance program: how it works and what it can do" + author: + organization: The Guardian + date: 2013 + pass3: + target: http://www.theguardian.com/world/2013/jul/31/nsa-top-secret-program-online-data + title: "XKeyscore: NSA tool collects 'nearly everything a user does on the internet'" + author: + organization: The Guardian + date: 2013 + pass4: + target: http://www.theguardian.com/uk/2013/jun/21/how-does-gchq-internet-surveillance-work + title: "How does GCHQ's internet surveillance work?" + author: + organization: The Guardian + dec1: + target: http://www.nytimes.com/2013/09/06/us/nsa-foils-much-internet-encryption.html + title: "N.S.A. Able to Foil Basic Safeguards of Privacy on Web" + author: + organization: The New York Times + date: 2013 + dec2: + target: http://www.theguardian.com/world/interactive/2013/sep/05/nsa-project-bullrun-classification-guide + title: "Project Bullrun – classification guide to the NSA's decryption program" + author: + organization: The Guardian + date: 2013 + dec3: + target: http://www.theguardian.com/world/2013/sep/05/nsa-gchq-encryption-codes-security + title: "Revealed: how US and UK spy agencies defeat internet privacy and security" + author: + organization: The Guardian + date: 2013 + TOR: + target: https://www.torproject.org/ + title: "Tor" + author: + organization: The Tor Project + date: 2013 + TOR1: + target: https://www.schneier.com/blog/archives/2013/10/how_the_nsa_att.html + title: "How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID" + author: + name: Bruce Schneier + ins: B. Schneier + date: 2013 + TOR2: + target: http://www.theguardian.com/world/interactive/2013/oct/04/tor-stinks-nsa-presentation-document + title: "'Tor Stinks' presentation – read the full document" + author: + organization: The Guardian + date: 2013 + dir1: + target: http://www.theguardian.com/world/2013/jun/06/nsa-phone-records-verizon-court-order + title: "NSA collecting phone records of millions of Verizon customers daily" + author: + organization: The Guardian + date: 2013 + dir2: + target: http://www.theguardian.com/world/2013/jun/06/us-tech-giants-nsa-data + title: "NSA Prism program taps in to user data of Apple, Google and others" + author: + organization: The Guardian + date: 2013 + dir3: + target: http://www.theguardian.com/world/interactive/2013/sep/05/sigint-nsa-collaborates-technology-companies + title: "Sigint – how the NSA collaborates with technology companies" + author: + organization: The Guardian + date: 2013 + secure: + target: http://www.theguardian.com/world/2013/sep/05/nsa-how-to-remain-secure-surveillance + title: "NSA surveillance: A guide to staying secure" + author: + name: Bruce Schneier + ins: B. Schneier + organization: The Guardian + date: 2013 + snowden: + target: http://www.technologyreview.com/news/519171/nsa-leak-leaves-crypto-math-intact-but-highlights-known-workarounds/ + title: "NSA Leak Leaves Crypto-Math Intact but Highlights Known Workarounds" + author: + organization: Technology Review + date: 2013 + spiegel1: + target: http://www.spiegel.de/international/world/nsa-secret-toolbox-ant-unit-offers-spy-gadgets-for-every-need-a-941006.html + title: "NSA's Secret Toolbox: Unit Offers Spy Gadgets for Every Need" + author: + ins: J Applebaum + name: Jacob Applebaum + author: + ins: J Horchert + name: Judith Horchert + author: + ins: O Reissmann + name: Ole Reissmann + author: + ins: M Rosenbach + name: Marcel Rosenbach + author: + ins: J Schindler + name: Jorg Schindler + author: + ins: C Stocker + name: Christian Stocker + date: 2013-12-30 + spiegel3: + target: http://www.spiegel.de/international/world/new-snowden-docs-indicate-scope-of-nsa-preparations-for-cyber-battle-a-1013409.html + title: "The Digital Arms Race: NSA Preps America for Future Battle" + author: + ins: J Appelbaum + name: Jacob Appelbaum + author: + ins: A Gibson + name: Aaron Gibson + author: + ins: C Guarnieri + name: Claudio Guarnieri + author: + ins: A Muller-Maguhn + name: Andy Muller-Maguhn + author: + ins: M Sontheimer + name: Michael Sontheimer + author: + ins: L Poitras + name: Laura Poitras + author: + ins: M Rosenbach + name: Marcel Rosenbach + author: + ins: L Ryge + name: Leif Ryge + author: + ins: H Schmundt + name: Hilmar Schmundt + date: 2014-01-17 + key-recovery: + target: http://crypto.stanford.edu/~pgolle/papers/escrow.pdf + title: The Design and Implementation of Protocol-Based Hidden Key Recovery + author: + ins: E.-J. Goh + name: Eu-Jin Goh + author: + ins: D. Boneh + name: Dan Boneh + author: + ins: B. Pinkas + name: Benny Pinkas + author: + ins: P. Golle + name: Phillippe Golle + date: 2003 + RFC1035: + RFC1918: + RFC1939: + RFC2015: + RFC2821: + RFC3261: + RFC3365: + RFC3501: + RFC3851: + RFC4033: + RFC4301: + RFC4303: + RFC4306: + RFC4949: + RFC5246: + RFC5321: + RFC5655: + RFC5750: + RFC6120: + RFC6962: + RFC6698: + RFC7011: + RFC7258: + +--- abstract + +Documents published since initial revelations in 2013 have revealed +several classes of pervasive surveillance attack on Internet +communications. In this document we develop a threat model that +describes these pervasive attacks. We start by assuming an attacker +with an interest in undetected, indiscriminate eavesdropping, then +expand the threat model with a set of verified attacks that have been +published. + +--- middle + +# Introduction + +Starting in June 2013, documents released to the press by Edward +Snowden have revealed several operations undertaken by intelligence +agencies to exploit Internet communications for intelligence purposes. +These attacks were largely based on protocol vulnerabilities that were +already known to exist. The attacks were nonetheless striking in +their pervasive nature, both in terms of the amount of Internet +communications targeted, and in terms of the diversity of attack +techniques employed. + +To ensure that the Internet can be trusted by users, it is necessary +for the Internet technical community to address the vulnerabilities +exploited in these attacks {{RFC7258}}. The goal of this document is +to describe more precisely the threats posed by these pervasive +attacks, and based on those threats, lay out the problems that need to +be solved in order to secure the Internet in the face of those +threats. + +The remainder of this document is structured as follows. In +{{adversary}}, we describe an idealized flow access attacker, one which +could completely undetectably compromise communications at Internet +scale. In {{reported}}, we provide a brief summary of some attacks +that have been disclosed, and use these to expand the assumed +capabilities of our idealized attacker. Note that we do not attempt +to describe all possible attacks, but focus on those which result in +undetected eavesdropping. {{model}} describes a threat model based on +these attacks, focusing on classes of attack that have not been a +focus of Internet engineering to date. + +# Terminology {#terminology} + +This document makes extensive use of standard security and privacy +terminology; see {{RFC4949}} and {{RFC6973}}. Terms used from +{{RFC6973}} include Eavesdropper, Observer, Initiator, Intermediary, +Recipient, Attack (in a privacy context), Correlation, Fingerprint, +Traffic Analysis, and Identifiability (and related terms). In +addition, we use a few terms that are specific to the attacks +discussed here: + +Flow Access Attack: +: An eavesdropping attack in which the packets +in a traffic stream between two endpoints are eavesdropped upon, but +in which the attacker does not modify the packets in the traffic +stream between two endpoints, modify the treatment of packets in the +traffic stream (e.g. delay, routing), or add or remove packets in the +traffic stream. Flow access attacks are undetectable from the +endpoints. + +Flow Modification Attack: +: An attack which includes both eavesdropping (as in a +flow access attack) as well as modification, addition, or removal of +packets in a traffic stream, or modification of treatment of packets +in the traffic stream. Flow modification attacks provide more +capabilities to the attacker at the cost of possible detection at the +endpoints. + +Pervasive Attack: +: An attack on Internet communications that makes +use of access at a large number of points in the network, or otherwise +provides the attacker with access to a large amount of Internet +traffic; see {{RFC7258}} + +Observation: +: Information collected directly from communications by an +eavesdropper or observer. For example, the knowledge that +<alice@example.com> sent a message to <bob@example.com> +via SMTP taken from the headers of an observed SMTP message would be +an observation. + +Inference: +: Information extracted from analysis of information collected +directly from communications by an eavesdropper or observer. For +example, the knowledge that a given web page was accessed by a given +IP address, by comparing the size in octets of measured network flow +records to fingerprints derived from known sizes of linked resources +on the web servers involved, would be an inference. + +Collaborator: +: An entity that is a legitimate participant in a communication, but +who deliberately provides information about that interaction to an +attacker. + +Unwitting Collaborator: +: An entity that is a legitimate participant in a communication, and +who is the source of information obtained by the attacker without the +entity's consent or intention, because the attacker has exploited some +technology used by the entity. + +Key Exfiltration: +: The transmission of keying material for an encrypted communication +from a collaborator, deliberately or unwittingly, to an attacker + +Content Exfiltration: +: The transmission of the content of a communication from a collaborator, deliberately or unwittingly, to an attacker + +# An Idealized Pervasive Flow Access Attacker {#adversary} + +In considering the threat posed by pervasive surveillance, we begin by +defining an idealized pervasive flow access attacker. While this attacker +is less capable than those which we now know to have compromised the +Internet from press reports, as elaborated in {{reported}}, it does +set a lower bound on the capabilities of an attacker interested in +indiscriminate passive surveillance while interested in remaining +undetectable. We note that, prior to the Snowden revelations in 2013, +the assumptions of attacker capability presented here would be +considered on the border of paranoia outside the network security +community. + +Our idealized attacker is an indiscriminate eavesdropper on an Internet-attached computer network that: + +- can observe every packet of all communications at any hop in any network path between an initiator and a recipient; +- can observe data at rest in any intermediate system between the endpoints controlled by the initiator and recipient; and +- can share information with other such attackers; but +- takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.). + +The techniques available to our ideal attacker are direct observation +and inference. Direct observation involves taking information directly +from eavesdropped communications - e.g., URLs identifying content or +email addresses identifying individuals from application-layer +headers. Inference, on the other hand, involves analyzing eavesdropped +information to derive new information from it; e.g., searching for +application or behavioral fingerprints in observed traffic to derive +information about the observed individual from them, in absence of +directly-observed sources of the same information. The use of +encryption to protect confidentiality is generally enough to prevent +direct observation of unencrypted content, assuming uncompromised +encryption implementations and key material. However, it provides less +complete protection against inference, especially inference based only +on unprotected portions of communications (e.g. IP and TCP headers for +TLS {{RFC5246}}). + +## Information subject to direct observation + +Protocols which do not encrypt their payload make the entire content +of the communication available to the idealized attacker along their +path. Following the advice in {{RFC3365}}, most such protocols have a +secure variant which encrypts payload for confidentiality, and these +secure variants are seeing ever-wider deployment. A noteworthy +exception is DNS {{RFC1035}}, as DNSSEC {{RFC4033}} does not have +confidentiality as a requirement. This implies that, in the absence of +changes to the protocol as presently under development in the DPRIVE +working group, all DNS queries and answers generated by the activities +of any protocol are available to the attacker. + +Protocols which imply the storage of some data at rest in +intermediaries (e.g. SMTP {{RFC5321}}) leave this data subject to +observation by an attacker that has compromised these intermediaries, +unless the data is encrypted end-to-end by the application layer +protocol, or the implementation uses an encrypted store for this data. + +## Information useful for inference + +Inference is information extracted from later analysis of an observed +or eavesdropped communication, and/or correlation of observed or +eavesdropped information with information available from other +sources. Indeed, most useful inference performed by the attacker falls +under the rubric of correlation. The simplest example of this is the +observation of DNS queries and answers from and to a source and +correlating those with IP addresses with which that source +communicates. This can give access to information otherwise not +available from encrypted application payloads (e.g., the Host: +HTTP/1.1 request header when HTTP is used with TLS). + +Protocols which encrypt their payload using an application- or +transport-layer encryption scheme (e.g. TLS) still expose all the +information in their network and transport layer headers to the +attacker, including source and destination addresses and ports. IPsec +ESP{{RFC4303}} further encrypts the transport-layer headers, but still +leaves IP address information unencrypted; in tunnel mode, these +addresses correspond to the tunnel endpoints. Features of the +cryptographic protocols themselves, e.g. the TLS session identifier, +may leak information that can be used for correlation and +inference. While this information is much less semantically rich than +the application payload, it can still be useful for the inferring an +individual's activities. + +Inference can also leverage information obtained from sources other +than direct traffic observation. Geolocation databases, for example, +have been developed map IP addresses to a location, in order to +provide location-aware services such as targeted advertising. This +location information is often of sufficient resolution that it can be +used to draw further inferences toward identifying or profiling an +individual. + +Social media provide another source of more or less publicly +accessible information. This information can be extremely semantically +rich, including information about an individual's location, +associations with other individuals and groups, and +activities. Further, this information is generally contributed and +curated voluntarily by the individuals themselves: it represents +information which the individuals are not necessarily interested in +protecting for privacy reasons. However, correlation of this social +networking data with information available from direct observation of +network traffic allows the creation of a much richer picture of an +individual's activities than either alone. + +We note with some alarm that there is little that can be done at +protocol design time to limit such correlation by the attacker, and +that the existence of such data sources in many cases greatly +complicates the problem of protecting privacy by hardening protocols +alone. + +## An illustration of an ideal flow access attack + +To illustrate how capable the idealized attacker is even given its +limitations, we explore the non-anonymity of encrypted IP traffic in +this section. Here we examine in detail some inference techniques for +associating a set of addresses with an individual, in order to +illustrate the difficulty of defending communications against our +idealized attacker. Here, the basic problem is that information +radiated even from protocols which have no obvious connection with +personal data can be correlated with other information which can paint +a very rich behavioral picture, that only takes one unprotected link +in the chain to associate with an identity. + +### Analysis of IP headers + +Internet traffic can be monitored by tapping Internet links, or by +installing monitoring tools in Internet routers. Of course, a single +link or a single router only provides access to a fraction of the +global Internet traffic. However, monitoring a number of high capacity +links or a set of routers placed at strategic locations provides +access to a good sampling of Internet traffic. + +Tools like IPFIX {{RFC7011}} allow administrators to acquire +statistics about sequences of packets with some common properties that +pass through a network device. The most common set of properties used +in flow measurement is the "five-tuple"of source and destination +addresses, protocol type, and source and destination ports. These +statistics are commonly used for network engineering, but could +certainly be used for other purposes. + +Let's assume for a moment that IP addresses can be correlated to +specific services or specific users. Analysis of the sequences of +packets will quickly reveal which users use what services, and also +which users engage in peer-to-peer connections with other +users. Analysis of traffic variations over time can be used to detect +increased activity by particular users, or in the case of peer-to-peer +connections increased activity within groups of users. + +### Correlation of IP addresses to user identities + +The correlation of IP addresses with specific users can be done in +various ways. For example, tools like reverse DNS lookup can be used +to retrieve the DNS names of servers. Since the addresses of servers +tend to be quite stable and since servers are relatively less numerous +than users, an attacker could easily maintain its own copy of the DNS +for well-known or popular servers, to accelerate such lookups. + +On the other hand, the reverse lookup of IP addresses of users is +generally less informative. For example, a lookup of the address +currently used by one author's home network returns a name of the form +"c-192-000-002-033.hsd1.wa.comcast.net". This particular type of +reverse DNS lookup generally reveals only coarse-grained location or +provider information, equivalent to that available from geolocation +databases. + +In many jurisdictions, Internet Service Providers (ISPs) are required +to provide identification on a case by case basis of the "owner" of a +specific IP address for law enforcement purposes. This is a reasonably +expedient process for targeted investigations, but pervasive +surveillance requires something more efficient. This provides an +incentive for the attacker to secure the cooperation of the ISP in +order to automate this correlation. + +### Monitoring messaging clients for IP address correlation + +Even if the ISP does not cooperate, user identity can often be +obtained via inference. POP3 {{RFC1939}} and IMAP {{RFC3501}} are used +to retrieve mail from mail servers, while a variant of SMTP is used to +submit messages through mail servers. IMAP connections originate from +the client, and typically start with an authentication exchange in +which the client proves its identity by answering a password +challenge. The same holds for the SIP protocol {{RFC3261}} and many +instant messaging services operating over the Internet using +proprietary protocols. + +The username is directly observable if any of these protocols operate +in cleartext; the username can then be directly associated with the +source address. + +### Retrieving IP addresses from mail headers + +SMTP {{RFC5321}} requires that each successive SMTP relay adds a +"Received" header to the mail headers. The purpose of these headers is +to enable audit of mail transmission, and perhaps to distinguish +between regular mail and spam. Here is an extract from the headers of +a message recently received from the "perpass" mailing list: + +``` + Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?) + (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA + (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100 + Message-ID: <526D7BD2.7070908@example.org> + Date: Sun, 27 Oct 2013 20:47:14 +0000 + From: Some One +``` + +This is the first "Received" header attached to the message by the +first SMTP relay; for privacy reasons, the field values have been +anonymized. We learn here that the message was submitted by "Some One" +on October 27, from a host behind a NAT (192.168.1.100) {{RFC1918}} +that used the IP address 192.0.2.44. The information remained in the +message, and is accessible by all recipients of the "perpass" mailing +list, or indeed by any attacker that sees at least one copy of the +message. + +An attacker that can observe sufficient email traffic can regularly +update the mapping between public IP addresses and individual email +identities. Even if the SMTP traffic was encrypted on submission and +relaying, the attacker can still receive a copy of public mailing +lists like "perpass". + +### Tracking address usage with web cookies + +Many web sites only encrypt a small fraction of their transactions. A +popular pattern is to use HTTPS for the login information, and then +use a "cookie" to associate following clear-text transactions with the +user's identity. Cookies are also used by various advertisement +services to quickly identify the users and serve them with +"personalized" advertisements. Such cookies are particularly useful if +the advertisement services want to keep tracking the user across +multiple sessions that may use different IP addresses. + +As cookies are sent in clear text, an attacker can build a database +that associates cookies to IP addresses for non-HTTPS traffic. If the +IP address is already identified, the cookie can be linked to the user +identify. After that, if the same cookie appears on a new IP address, +the new IP address can be immediately associated with the +pre-determined identity. + +### Graph-based approaches to address correlation + +An attacker can track traffic from an IP address not yet associated +with an individual to various public services (e.g. websites, mail +servers, game servers), and exploit patterns in the observed traffic +to correlate this address with other addresses that show similar +patterns. For example, any two addresses that show connections to the +same IMAP or webmail services, the same set of favorite websites, and +game servers at similar times of day may be associated with the same +individual. Correlated addresses can then be tied to an individual +through one of the techniques above, walking the "network graph" to +expand the set of attributable traffic. + +### Tracking of MAC Addresses + +Moving back down the stack, technologies like Ethernet or Wi-Fi use +MAC Addresses to identify link-level destinations. MAC Addresses +assigned according to IEEE-802 standards are unique to the device. If +the link is publicly accessible, an attacker can track it. For +example, the attacker can track the wireless traffic at public Wi-Fi +networks. Simple devices can monitor the traffic, and reveal which MAC +Addresses are present. If the network does not use some form of Wi-Fi +encryption, or if the attacker can access the decrypted traffic, the +analysis will also provide the correlation between MAC Addresses and +IP addresses. Additional monitoring using techniques exposed in the +previous sections will reveal the correlation between MAC Addresses, +IP Addresses, and user identity. + +Given that large-scale databases of the MAC addresses of wireless +access points for geolocation purposes have been known to exist for +some time, the attacker could easily build a database linking MAC +Addresses and device or user identities, and use it to track the +movement of devices and of their owners. + +# Reported Instances of Large-Scale Attacks {#reported} + +The situation in reality is more bleak than that suggested by an +analysis of our idealized attacker. Through revelations of sensitive +documents in several media outlets, the Internet community has been +made aware of several intelligence activities conducted by US and UK +national intelligence agencies, particularly the US National Security +Agency (NSA) and the UK Government Communications Headquarters +(GCHQ). These documents have revealed methods that these agencies use +to attack Internet applications and obtain sensitive user information. + +First, they have confirmed that these agencies have capabilities in +line with those of our idealized attacker, thorugh the large-scale +passive collection of Internet traffic +{{pass1}}{{pass2}}{{pass3}}{{pass4}}. For example: - The NSA XKEYSCORE +system accesses data from multiple access points and searches for +"selectors" such as email addresses, at the scale of tens of terabytes +of data per day. - The GCHQ Tempora system appears to have access to +around 1,500 major cables passing through the UK. - The NSA MUSCULAR +program tapped cables between data centers belonging to major service +providers. - Several programs appear to perform wide-scale collection +of cookies in web traffic and location data from location-aware +portable devices such as smartphones. + +However, the capabilities described go beyond those available to our idealized attacker, including: + +* Decryption of TLS-protected Internet sessions + {{dec1}}{{dec2}}{{dec3}}. For example, the NSA BULLRUN project + appears to have had a budget of around $250M per year to undermine + encryption through multiple approaches. + +* Insertion of NSA devices as a man-in-the-middle of Internet + transactions {{TOR1}}{{TOR2}}. For example, the NSA QUANTUM system + appears to use several different techniques to hijack HTTP + connections, ranging from DNS response injection to HTTP 302 + redirects. + +* Direct acquisition of bulk data and metadata from service providers + {{dir1}}{{dir2}}{{dir3}}. For example, the NSA PRISM program + provides the agency with access to many types of user data (e.g., + email, chat, VoIP). + +* Use of implants (covert modifications or malware) to undermine security and anonymity features {{dec2}}{{TOR1}}{{TOR2}}. For example: + * NSA appears to use the QUANTUM man-in-the-middle system to direct users to a FOXACID server, which delivers an implant to compromise the browser of a user of the Tor anonymous communications network. + * Implants are apparently available for Cisco, Juniper, Huawei, Dell, and HP network elements, provided by the NSA Advanced Network Technology group {{spiegel1}} + * Compromised hosts at botnet scale, using tools by the NSA's Remote Operations Center {{spiegel3}} + * The BULLRUN program mentioned above includes the addition of covert modifications to software as one means to undermine encryption. + * There is also some suspicion that NSA modifications to the DUAL\_EC\_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA. These suspicions have been reinforced by reports that RSA Security was paid roughly $10M to make DUAL\_EC\_DRBG the default in their products. + +We use the term "pervasive attack" {{RFC7258}} to collectively +describe these operations. The term "pervasive" is used because the +attacks are designed to indiscriminately gather as much data as +possible and to apply selective analysis on targets after the fact. +This means that all, or nearly all, Internet communications are +targets for these attacks. To achieve this scale, the attacks are +physically pervasive; they affect a large number of Internet +communications. They are pervasive in content, consuming and +exploiting any information revealed by the protocol. And they are +pervasive in technology, exploiting many different vulnerabilities in +many different protocols. + +It's important to note that although the attacks mentioned above were +executed by NSA and GCHQ, there are many other organizations that can +mount pervasive surveillance attacks. Because of the resources +required to achieve pervasive scale, these attacks are most commonly +undertaken by nation-state actors. For example, the Chinese Internet +filtering system known as the "Great Firewall of China" uses several +techniques that are similar to the QUANTUM program, and which have a +high degree of pervasiveness with regard to the Internet in China. + +# Threat Model {#model} + +Given these disclosures, we must consider a broader threat model. + +Pervasive surveillance aims to collect information across a large +number of Internet communications, analyzing the collected +communications to identify information of interest within individual +communications, or inferring information from correlated +communications. his analysis sometimes benefits from decryption of +encrypted communications and deanonymization of anonymized +communications. As a result, these attackers desire both access to +the bulk of Internet traffic and to the keying material required to +decrypt any traffic that has been encrypted. Even if keys are not +available, note that the presence of a communication and the fact that +it is encrypted may both be inputs to an analysis, even if the +attacker cannot decrypt the communication. + +The attacks listed above highlight new avenues both for access to +traffic and for access to relevant encryption keys. They further +indicate that the scale of surveillance is sufficient to provide a +general capability to cross-correlate communications, a threat not +previously thought to be relevant at the scale of the Internet. + +## Attacker Capabilities + +| Attack Class | Capability | +|:--------------------------|:------------------------------------------| +| Passive observation | Directly capture data in transit | +| Passive inference | Infer from reduced/encrypted data | +| Active | Manipulate / inject data in transit | +| Static key exfiltration | Obtain key material once / rarely | +| Dynamic key exfiltration | Obtain per-session key material | +| Content exfiltration | Access data at rest | + +Security analyses of Internet protocols commonly consider two classes +of attacker: flow access attackers, who can simply listen in on +communications as they transit the network, and flow modification +attackers, who can modify or delete packets in addition to simply +collecting them. + +In the context of pervasive passive surveillance, these attacks take +on an even greater significance. In the past, these attackers were +often assumed to operate near the edge of the network, where attacks +can be simpler. For example, in some LANs, it is simple for any node +to engage in passive listening to other nodes' traffic or inject +packets to accomplish flow modification attacks. However, as we now +know, both passive and flow modification attacks are undertaken by +pervasive attackers closer to the core of the network, greatly +expanding the scope and capability of the attacker. + +Eavesdropping and observation at a larger scale make passive inference +attacks easier to carry out: a flow access attacker with access to a +large portion of the Internet can analyze collected traffic to create +a much more detailed view of individual behavior than an attacker that +collects at a single point. Even the usual claim that encryption +defeats flow access attackers is weakened, since a pervasive flow +access attacker can infer relationships from correlations over large +numbers of sessions, e.g., pairing encrypted sessions with unencrypted +sessions from the same host, or performing traffic fingerprinting +between known and unknown encrypted sessions. Reports on the NSA +XKEYSCORE system would indicate it is an example of such an attacker. + +A pervasive flow modification attacker likewise has capabilities +beyond those of a localized flow modification attacker. flow +modification attacks are often limited by network topology, for +example by a requirement that the attacker be able to see a targeted +session as well as inject packets into it. A pervasive flow +modification attacker with access at multiple points within the core +of the Internet is able to overcome these topological limitations and +perform attacks over a much broader scope. Being positioned in the +core of the network rather than the edge can also enable a pervasive +flow modification attacker to reroute targeted traffic, amplifying the +ability to perform both eavesdropping and traffic injection. +Pervasive flow modification attackers can also benefit from pervasive +passive collection to identify vulnerable hosts. + +While not directly related to pervasiveness, attackers that are in a +position to mount a pervasive flow modification attack are also often +in a position to subvert authentication, a traditional protection +against such attacks. Authentication in the Internet is often +achieved via trusted third party authorities such as the Certificate +Authorities (CAs) that provide web sites with authentication +credentials. An attacker with sufficient resources may also be able to +induce an authority to grant credentials for an identity of the +attacker’s choosing. If the parties to a communication will trust +multiple authorities to certify a specific identity, this attack may +be mounted by suborning any one of the authorities (the proverbial +"weakest link"). Subversion of authorities in this way can allow an +flow modification attack to succeed in spite of an authentication +check. + +Beyond these three classes (observation, inference, and active), +reports on the BULLRUN effort to defeat encryption and the PRISM +effort to obtain data from service providers suggest three more +classes of attack: + +* Static key exfiltration +* Dynamic key exfiltration +* Content exfiltration + +These attacks all rely on a collaborator providing the attacker with +some information, either keys or data. These attacks have not +traditionally been considered in scope for the Security Considerations +sections of IETF protocols, as they occur outside the protocol. + +The term "key exfiltration" refers to the transfer of keying material +for an encrypted communication from the collaborator to the attacker. +By "static", we mean that the transfer of keys happens once, or +rarely, typically of a long-lived key. For example, this case would +cover a web site operator that provides the private key corresponding +to its HTTPS certificate to an intelligence agency. + +"Dynamic" key exfiltration, by contrast, refers to attacks in which +the collaborator delivers keying material to the attacker frequently, +e.g., on a per-session basis. This does not necessarily imply +frequent communications with the attacker; the transfer of keying +material may be virtual. For example, if an endpoint were modified in +such a way that the attacker could predict the state of its +psuedorandom number generator, then the attacker would be able to +derive per-session keys even without per-session communications. + +Finally, content exfiltration is the attack in which the collaborator +simply provides the attacker with the desired data or metadata. Unlike +the key exfiltration cases, this attack does not require the attacker +to capture the desired data as it flows through the network. The risk +is to data at rest as opposed to data in transit. This increases the +scope of data that the attacker can obtain, since the attacker can +access historical data -- the attacker does not have to be listening +at the time the communication happens. + +Exfiltration attacks can be accomplished via attacks against one of +the parties to a communication, i.e., by the attacker stealing the +keys or content rather than the party providing them willingly. In +these cases, the party may not be aware that they are collaborating, +at least at a human level. Rather, the subverted technical assets are +"collaborating" with the attacker (by providing keys/content) without +their owner's knowledge or consent. + +Any party that has access to encryption keys or unencrypted data can +be a collaborator. While collaborators are typically the endpoints of +a communication (with encryption securing the links), intermediaries +in an unencrypted communication can also facilitate content +exfiltration attacks as collaborators by providing the attacker access +to those communications. For example, documents describing the NSA +PRISM program claim that NSA is able to access user data directly from +servers, where it is stored unencrypted. In these cases, the operator +of the server would be a collaborator, if an unwitting one. By +contrast, in the NSA MUSCULAR program, a set of collaborators enabled +attackers to access the cables connecting data centers used by service +providers such as Google and Yahoo. Because communications among +these data centers were not encrypted, the collaboration by an +intermediate entity allowed NSA to collect unencrypted user data. + +## Attacker Costs + +| Attack Class | Cost / Risk to Attacker | +|:--------------------------|:----------------------------------| +| Passive observation | Passive data access | +| Passive inference | Passive data access + processing | +| Active | Active data access + processing | +| Static key exfiltration | One-time interaction | +| Dynamic key exfiltration | Ongoing interaction / code change | +| Content exfiltration | Ongoing, bulk interaction | + +Each of the attack types discussed in the previous section entails +certain costs and risks. These costs differ by attack, and can be +helpful in guiding response to pervasive attack. + +Depending on the attack, the attacker may be exposed to several types +of risk, ranging from simply losing access to arrest or prosecution. +In order for any of these negative consequences to occur, however, the +attacker must first be discovered and identified. So the primary risk +we focus on here is the risk of discovery and attribution. + +A flow access attack is the simplest to mount in some ways. The base +requirement is that the attacker obtain physical access to a +communications medium and extract communications from it. For +example, the attacker might tap a fiber-optic cable, acquire a mirror +port on a switch, or listen to a wireless signal. The need for these +taps to have physical access or proximity to a link exposes the +attacker to the risk that the taps will be discovered. For example, a +fiber tap or mirror port might be discovered by network operators +noticing increased attenuation in the fiber or a change in switch +configuration. Of course, flow access attacks may be accomplished +with the cooperation of the network operator, in which case there is a +risk that the attacker's interactions with the network operator will +be exposed. + +In many ways, the costs and risks for an flow modification attack are +similar to those for a flow access attack, with a few additions. An +flow modification attacker requires more robust network access than a +flow access attacker, since for example they will often need to +transmit data as well as receiving it. In the wireless example above, +the attacker would need to act as an transmitter as well as receiver, +greatly increasing the probability the attacker will be discovered +(e.g., using direction-finding technology). flow modification attacks +are also much more observable at higher layers of the network. For +example, an flow modification attacker that attempts to use a +mis-issued certificate could be detected via Certificate Transparency +{{RFC6962}}. + +In terms of raw implementation complexity, flow access attacks require +only enough processing to extract information from the network and +store it. flow modification attacks, by contrast, often depend on +winning race conditions to inject pakets into active connections. So +flow modification attacks in the core of the network require +processing hardware to that can operate at line speed (roughly 100Gbps +to 1Tbps in the core) to identify opportunities for attack and insert +attack traffic in a high-volume traffic. Key exfiltration attacks +rely on flow access attack for access to encrypted data, with the +collaborator providing keys to decrypt the data. So the attacker +undertakes the cost and risk of a flow access attack, as well as +additional risk of discovery via the interactions that the attacker +has with the collaborator. + +In this sense, static exfiltration has a lower risk profile than +dynamic. In the static case, the attacker need only interact with the +collaborator a small number of times, possibly only once, say to +exchange a private key. In the dynamic case, the attacker must have +continuing interactions with the collaborator. As noted above these +interactions may real, such as in-person meetings, or virtual, such as +software modifications that render keys available to the attacker. +Both of these types of interactions introduce a risk that they will be +discovered, e.g., by employees of the collaborator organization +noticing suspicious meetings or suspicious code changes. + +Content exfiltration has a similar risk profile to dynamic key +exfiltration. In a content exfiltration attack, the attacker saves +the cost and risk of conducting a flow access attack. The risk of +discovery through interactions with the collaborator, however, is +still present, and may be higher. The content of a communication is +obviously larger than the key used to encrypt it, often by several +orders of magnitude. So in the content exfiltration case, the +interactions between the collaborator and the attacker need to be much +higher-bandwidth than in the key exfiltration cases, with a +corresponding increase in the risk that this high-bandwidth channel +will be discovered. + +It should also be noted that in these latter three exfiltration cases, +the collaborator also undertakes a risk that his collaboration with +the attacker will be discovered. Thus the attacker may have to incur +additional cost in order to convince the collaborator to participate +in the attack. Likewise, the scope of these attacks is limited to +case where the attacker can convince a collaborator to participate. +If the attacker is a national government, for example, it may be able +to compel participation within its borders, but have a much more +difficult time recruiting foreign collaborators. + +As noted above, the collaborator in an exfiltration attack can be +unwitting; the attacker can steal keys or data to enable the attack. +In some ways, the risks of this approach are similar to the case of an +active collaborator. In the static case, the attacker needs to steal +information from the collaborator once; in the dynamic case, the +attacker needs to continued presence inside the collaborators systems. +The main difference is that the risk in this case is of automated +discovery (e.g., by intrusion detection systems) rather than discovery +by humans. + +# Security Considerations + +This document describes a threat model for pervasive surveillance +attacks. Mitigations are to be given in a future document. + +# IANA Considerations + +This document has no actions for IANA. + +# Acknowledgements + +Thanks to Dave Thaler for the list of attacks and taxonomy; to +Security Area Directors Stephen Farrell, Sean Turner, and Kathleen +Moriarty for starting and managing the IETF's discussion on pervasive +attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, Evangelos +Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, as well as the IAB +Privacy and Security Program, for their input. + diff --git a/draft-iab-privsec-confidentiality-threat-03.pdf b/draft-iab-privsec-confidentiality-threat-03.pdf new file mode 100644 index 0000000..5b26b13 Binary files /dev/null and b/draft-iab-privsec-confidentiality-threat-03.pdf differ diff --git a/draft-iab-privsec-confidentiality-threat-03.txt b/draft-iab-privsec-confidentiality-threat-03.txt new file mode 100644 index 0000000..d6c32be --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-03.txt @@ -0,0 +1,1232 @@ + + + + +Network Working Group R. Barnes +Internet-Draft +Intended status: Informational B. Schneier +Expires: August 24, 2015 + C. Jennings + + T. Hardie + + B. Trammell + + C. Huitema + + D. Borkmann + + February 20, 2015 + + + Confidentiality in the Face of Pervasive Surveillance: A Threat Model + and Problem Statement + draft-iab-privsec-confidentiality-threat-03 + +Abstract + + Documents published since initial revelations in 2013 have revealed + several classes of pervasive surveillance attack on Internet + communications. In this document we develop a threat model that + describes these pervasive attacks. We start by assuming an attacker + with an interest in undetected, indiscriminate eavesdropping, then + expand the threat model with a set of verified attacks that have been + published. + +Status of This Memo + + This Internet-Draft is submitted in full conformance with the + provisions of BCP 78 and BCP 79. + + Internet-Drafts are working documents of the Internet Engineering + Task Force (IETF). Note that other groups may also distribute + working documents as Internet-Drafts. The list of current Internet- + Drafts is at http://datatracker.ietf.org/drafts/current/. + + Internet-Drafts are draft documents valid for a maximum of six months + and may be updated, replaced, or obsoleted by other documents at any + time. It is inappropriate to use Internet-Drafts as reference + material or to cite them other than as "work in progress." + + This Internet-Draft will expire on August 24, 2015. + + + + +Barnes, et al. Expires August 24, 2015 [Page 1] + +Internet-Draft Confidentiality Threat Model February 2015 + + +Copyright Notice + + Copyright (c) 2015 IETF Trust and the persons identified as the + document authors. All rights reserved. + + This document is subject to BCP 78 and the IETF Trust's Legal + Provisions Relating to IETF Documents + (http://trustee.ietf.org/license-info) in effect on the date of + publication of this document. Please review these documents + carefully, as they describe your rights and restrictions with respect + to this document. Code Components extracted from this document must + include Simplified BSD License text as described in Section 4.e of + the Trust Legal Provisions and are provided without warranty as + described in the Simplified BSD License. + +1. Introduction + + Starting in June 2013, documents released to the press by Edward + Snowden have revealed several operations undertaken by intelligence + agencies to exploit Internet communications for intelligence + purposes. These attacks were largely based on protocol + vulnerabilities that were already known to exist. The attacks were + nonetheless striking in their pervasive nature, both in terms of the + amount of Internet communications targeted, and in terms of the + diversity of attack techniques employed. + + To ensure that the Internet can be trusted by users, it is necessary + for the Internet technical community to address the vulnerabilities + exploited in these attacks [RFC7258]. The goal of this document is + to describe more precisely the threats posed by these pervasive + attacks, and based on those threats, lay out the problems that need + to be solved in order to secure the Internet in the face of those + threats. + + The remainder of this document is structured as follows. In + Section 3, we describe an idealized flow access attacker, one which + could completely undetectably compromise communications at Internet + scale. In Section 4, we provide a brief summary of some attacks that + have been disclosed, and use these to expand the assumed capabilities + of our idealized attacker. Note that we do not attempt to describe + all possible attacks, but focus on those which result in undetected + eavesdropping. Section 5 describes a threat model based on these + attacks, focusing on classes of attack that have not been a focus of + Internet engineering to date. + + + + + + + +Barnes, et al. Expires August 24, 2015 [Page 2] + +Internet-Draft Confidentiality Threat Model February 2015 + + +2. Terminology + + This document makes extensive use of standard security and privacy + terminology; see [RFC4949] and [RFC6973]. Terms used from [RFC6973] + include Eavesdropper, Observer, Initiator, Intermediary, Recipient, + Attack (in a privacy context), Correlation, Fingerprint, Traffic + Analysis, and Identifiability (and related terms). In addition, we + use a few terms that are specific to the attacks discussed here: + + Flow Access Attack: An eavesdropping attack in which the packets + in a traffic stream between two endpoints are eavesdropped upon, + but in which the attacker does not modify the packets in the + traffic stream between two endpoints, modify the treatment of + packets in the traffic stream (e.g. delay, routing), or add or + remove packets in the traffic stream. Flow access attacks are + undetectable from the endpoints. + + Flow Modification Attack: An attack which includes both + eavesdropping (as in a flow access attack) as well as + modification, addition, or removal of packets in a traffic stream, + or modification of treatment of packets in the traffic stream. + Flow modification attacks provide more capabilities to the + attacker at the cost of possible detection at the endpoints. + + Pervasive Attack: An attack on Internet communications that makes + use of access at a large number of points in the network, or + otherwise provides the attacker with access to a large amount of + Internet traffic; see [RFC7258] + + Observation: Information collected directly from communications by + an eavesdropper or observer. For example, the knowledge that + sent a message to via SMTP + taken from the headers of an observed SMTP message would be an + observation. + + Inference: Information extracted from analysis of information + collected directly from communications by an eavesdropper or + observer. For example, the knowledge that a given web page was + accessed by a given IP address, by comparing the size in octets of + measured network flow records to fingerprints derived from known + sizes of linked resources on the web servers involved, would be an + inference. + + Collaborator: An entity that is a legitimate participant in a + communication, but who deliberately provides information about + that interaction to an attacker. + + + + + +Barnes, et al. Expires August 24, 2015 [Page 3] + +Internet-Draft Confidentiality Threat Model February 2015 + + + Unwitting Collaborator: An entity that is a legitimate participant + in a communication, and who is the source of information obtained + by the attacker without the entity's consent or intention, because + the attacker has exploited some technology used by the entity. + + Key Exfiltration: The transmission of keying material for an + encrypted communication from a collaborator, deliberately or + unwittingly, to an attacker + + Content Exfiltration: The transmission of the content of a + communication from a collaborator, deliberately or unwittingly, to + an attacker + +3. An Idealized Pervasive Flow Access Attacker + + In considering the threat posed by pervasive surveillance, we begin + by defining an idealized pervasive flow access attacker. While this + attacker is less capable than those which we now know to have + compromised the Internet from press reports, as elaborated in + Section 4, it does set a lower bound on the capabilities of an + attacker interested in indiscriminate passive surveillance while + interested in remaining undetectable. We note that, prior to the + Snowden revelations in 2013, the assumptions of attacker capability + presented here would be considered on the border of paranoia outside + the network security community. + + Our idealized attacker is an indiscriminate eavesdropper on an + Internet-attached computer network that: + + o can observe every packet of all communications at any hop in any + network path between an initiator and a recipient; + + o can observe data at rest in any intermediate system between the + endpoints controlled by the initiator and recipient; and + + o can share information with other such attackers; but + + o takes no other action with respect to these communications (i.e., + blocking, modification, injection, etc.). + + The techniques available to our ideal attacker are direct observation + and inference. Direct observation involves taking information + directly from eavesdropped communications - e.g., URLs identifying + content or email addresses identifying individuals from application- + layer headers. Inference, on the other hand, involves analyzing + eavesdropped information to derive new information from it; e.g., + searching for application or behavioral fingerprints in observed + traffic to derive information about the observed individual from + + + +Barnes, et al. Expires August 24, 2015 [Page 4] + +Internet-Draft Confidentiality Threat Model February 2015 + + + them, in absence of directly-observed sources of the same + information. The use of encryption to protect confidentiality is + generally enough to prevent direct observation of unencrypted + content, assuming uncompromised encryption implementations and key + material. However, it provides less complete protection against + inference, especially inference based only on unprotected portions of + communications (e.g. IP and TCP headers for TLS [RFC5246]). + +3.1. Information subject to direct observation + + Protocols which do not encrypt their payload make the entire content + of the communication available to the idealized attacker along their + path. Following the advice in [RFC3365], most such protocols have a + secure variant which encrypts payload for confidentiality, and these + secure variants are seeing ever-wider deployment. A noteworthy + exception is DNS [RFC1035], as DNSSEC [RFC4033] does not have + confidentiality as a requirement. This implies that, in the absence + of changes to the protocol as presently under development in the + DPRIVE working group, all DNS queries and answers generated by the + activities of any protocol are available to the attacker. + + Protocols which imply the storage of some data at rest in + intermediaries (e.g. SMTP [RFC5321]) leave this data subject to + observation by an attacker that has compromised these intermediaries, + unless the data is encrypted end-to-end by the application layer + protocol, or the implementation uses an encrypted store for this + data. + +3.2. Information useful for inference + + Inference is information extracted from later analysis of an observed + or eavesdropped communication, and/or correlation of observed or + eavesdropped information with information available from other + sources. Indeed, most useful inference performed by the attacker + falls under the rubric of correlation. The simplest example of this + is the observation of DNS queries and answers from and to a source + and correlating those with IP addresses with which that source + communicates. This can give access to information otherwise not + available from encrypted application payloads (e.g., the Host: + HTTP/1.1 request header when HTTP is used with TLS). + + Protocols which encrypt their payload using an application- or + transport-layer encryption scheme (e.g. TLS) still expose all the + information in their network and transport layer headers to the + attacker, including source and destination addresses and ports. + IPsec ESP[RFC4303] further encrypts the transport-layer headers, but + still leaves IP address information unencrypted; in tunnel mode, + these addresses correspond to the tunnel endpoints. Features of the + + + +Barnes, et al. Expires August 24, 2015 [Page 5] + +Internet-Draft Confidentiality Threat Model February 2015 + + + cryptographic protocols themselves, e.g. the TLS session identifier, + may leak information that can be used for correlation and inference. + While this information is much less semantically rich than the + application payload, it can still be useful for the inferring an + individual's activities. + + Inference can also leverage information obtained from sources other + than direct traffic observation. Geolocation databases, for example, + have been developed map IP addresses to a location, in order to + provide location-aware services such as targeted advertising. This + location information is often of sufficient resolution that it can be + used to draw further inferences toward identifying or profiling an + individual. + + Social media provide another source of more or less publicly + accessible information. This information can be extremely + semantically rich, including information about an individual's + location, associations with other individuals and groups, and + activities. Further, this information is generally contributed and + curated voluntarily by the individuals themselves: it represents + information which the individuals are not necessarily interested in + protecting for privacy reasons. However, correlation of this social + networking data with information available from direct observation of + network traffic allows the creation of a much richer picture of an + individual's activities than either alone. + + We note with some alarm that there is little that can be done at + protocol design time to limit such correlation by the attacker, and + that the existence of such data sources in many cases greatly + complicates the problem of protecting privacy by hardening protocols + alone. + +3.3. An illustration of an ideal flow access attack + + To illustrate how capable the idealized attacker is even given its + limitations, we explore the non-anonymity of encrypted IP traffic in + this section. Here we examine in detail some inference techniques + for associating a set of addresses with an individual, in order to + illustrate the difficulty of defending communications against our + idealized attacker. Here, the basic problem is that information + radiated even from protocols which have no obvious connection with + personal data can be correlated with other information which can + paint a very rich behavioral picture, that only takes one unprotected + link in the chain to associate with an identity. + + + + + + + +Barnes, et al. Expires August 24, 2015 [Page 6] + +Internet-Draft Confidentiality Threat Model February 2015 + + +3.3.1. Analysis of IP headers + + Internet traffic can be monitored by tapping Internet links, or by + installing monitoring tools in Internet routers. Of course, a single + link or a single router only provides access to a fraction of the + global Internet traffic. However, monitoring a number of high + capacity links or a set of routers placed at strategic locations + provides access to a good sampling of Internet traffic. + + Tools like IPFIX [RFC7011] allow administrators to acquire statistics + about sequences of packets with some common properties that pass + through a network device. The most common set of properties used in + flow measurement is the "five-tuple"of source and destination + addresses, protocol type, and source and destination ports. These + statistics are commonly used for network engineering, but could + certainly be used for other purposes. + + Let's assume for a moment that IP addresses can be correlated to + specific services or specific users. Analysis of the sequences of + packets will quickly reveal which users use what services, and also + which users engage in peer-to-peer connections with other users. + Analysis of traffic variations over time can be used to detect + increased activity by particular users, or in the case of peer-to- + peer connections increased activity within groups of users. + +3.3.2. Correlation of IP addresses to user identities + + The correlation of IP addresses with specific users can be done in + various ways. For example, tools like reverse DNS lookup can be used + to retrieve the DNS names of servers. Since the addresses of servers + tend to be quite stable and since servers are relatively less + numerous than users, an attacker could easily maintain its own copy + of the DNS for well-known or popular servers, to accelerate such + lookups. + + On the other hand, the reverse lookup of IP addresses of users is + generally less informative. For example, a lookup of the address + currently used by one author's home network returns a name of the + form "c-192-000-002-033.hsd1.wa.comcast.net". This particular type + of reverse DNS lookup generally reveals only coarse-grained location + or provider information, equivalent to that available from + geolocation databases. + + In many jurisdictions, Internet Service Providers (ISPs) are required + to provide identification on a case by case basis of the "owner" of a + specific IP address for law enforcement purposes. This is a + reasonably expedient process for targeted investigations, but + pervasive surveillance requires something more efficient. This + + + +Barnes, et al. Expires August 24, 2015 [Page 7] + +Internet-Draft Confidentiality Threat Model February 2015 + + + provides an incentive for the attacker to secure the cooperation of + the ISP in order to automate this correlation. + +3.3.3. Monitoring messaging clients for IP address correlation + + Even if the ISP does not cooperate, user identity can often be + obtained via inference. POP3 [RFC1939] and IMAP [RFC3501] are used + to retrieve mail from mail servers, while a variant of SMTP is used + to submit messages through mail servers. IMAP connections originate + from the client, and typically start with an authentication exchange + in which the client proves its identity by answering a password + challenge. The same holds for the SIP protocol [RFC3261] and many + instant messaging services operating over the Internet using + proprietary protocols. + + The username is directly observable if any of these protocols operate + in cleartext; the username can then be directly associated with the + source address. + +3.3.4. Retrieving IP addresses from mail headers + + SMTP [RFC5321] requires that each successive SMTP relay adds a + "Received" header to the mail headers. The purpose of these headers + is to enable audit of mail transmission, and perhaps to distinguish + between regular mail and spam. Here is an extract from the headers + of a message recently received from the "perpass" mailing list: + + "Received: from 192-000-002-044.zone13.example.org (HELO + ?192.168.1.100?) (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net + with ESMTPSA (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct + 2013 21:47:14 +0100 Message-ID: <526D7BD2.7070908@example.org> Date: + Sun, 27 Oct 2013 20:47:14 +0000 From: Some One + " + + This is the first "Received" header attached to the message by the + first SMTP relay; for privacy reasons, the field values have been + anonymized. We learn here that the message was submitted by "Some + One" on October 27, from a host behind a NAT (192.168.1.100) + [RFC1918] that used the IP address 192.0.2.44. The information + remained in the message, and is accessible by all recipients of the + "perpass" mailing list, or indeed by any attacker that sees at least + one copy of the message. + + An attacker that can observe sufficient email traffic can regularly + update the mapping between public IP addresses and individual email + identities. Even if the SMTP traffic was encrypted on submission and + relaying, the attacker can still receive a copy of public mailing + lists like "perpass". + + + +Barnes, et al. Expires August 24, 2015 [Page 8] + +Internet-Draft Confidentiality Threat Model February 2015 + + +3.3.5. Tracking address usage with web cookies + + Many web sites only encrypt a small fraction of their transactions. + A popular pattern is to use HTTPS for the login information, and then + use a "cookie" to associate following clear-text transactions with + the user's identity. Cookies are also used by various advertisement + services to quickly identify the users and serve them with + "personalized" advertisements. Such cookies are particularly useful + if the advertisement services want to keep tracking the user across + multiple sessions that may use different IP addresses. + + As cookies are sent in clear text, an attacker can build a database + that associates cookies to IP addresses for non-HTTPS traffic. If + the IP address is already identified, the cookie can be linked to the + user identify. After that, if the same cookie appears on a new IP + address, the new IP address can be immediately associated with the + pre-determined identity. + +3.3.6. Graph-based approaches to address correlation + + An attacker can track traffic from an IP address not yet associated + with an individual to various public services (e.g. websites, mail + servers, game servers), and exploit patterns in the observed traffic + to correlate this address with other addresses that show similar + patterns. For example, any two addresses that show connections to + the same IMAP or webmail services, the same set of favorite websites, + and game servers at similar times of day may be associated with the + same individual. Correlated addresses can then be tied to an + individual through one of the techniques above, walking the "network + graph" to expand the set of attributable traffic. + +3.3.7. Tracking of MAC Addresses + + Moving back down the stack, technologies like Ethernet or Wi-Fi use + MAC Addresses to identify link-level destinations. MAC Addresses + assigned according to IEEE-802 standards are unique to the device. + If the link is publicly accessible, an attacker can track it. For + example, the attacker can track the wireless traffic at public Wi-Fi + networks. Simple devices can monitor the traffic, and reveal which + MAC Addresses are present. If the network does not use some form of + Wi-Fi encryption, or if the attacker can access the decrypted + traffic, the analysis will also provide the correlation between MAC + Addresses and IP addresses. Additional monitoring using techniques + exposed in the previous sections will reveal the correlation between + MAC Addresses, IP Addresses, and user identity. + + Given that large-scale databases of the MAC addresses of wireless + access points for geolocation purposes have been known to exist for + + + +Barnes, et al. Expires August 24, 2015 [Page 9] + +Internet-Draft Confidentiality Threat Model February 2015 + + + some time, the attacker could easily build a database linking MAC + Addresses and device or user identities, and use it to track the + movement of devices and of their owners. + +4. Reported Instances of Large-Scale Attacks + + The situation in reality is more bleak than that suggested by an + analysis of our idealized attacker. Through revelations of sensitive + documents in several media outlets, the Internet community has been + made aware of several intelligence activities conducted by US and UK + national intelligence agencies, particularly the US National Security + Agency (NSA) and the UK Government Communications Headquarters + (GCHQ). These documents have revealed methods that these agencies + use to attack Internet applications and obtain sensitive user + information. + + First, they have confirmed that these agencies have capabilities in + line with those of our idealized attacker, thorugh the large-scale + passive collection of Internet traffic [pass1][pass2][pass3][pass4]. + For example: - The NSA XKEYSCORE system accesses data from multiple + access points and searches for "selectors" such as email addresses, + at the scale of tens of terabytes of data per day. - The GCHQ + Tempora system appears to have access to around 1,500 major cables + passing through the UK. - The NSA MUSCULAR program tapped cables + between data centers belonging to major service providers. - Several + programs appear to perform wide-scale collection of cookies in web + traffic and location data from location-aware portable devices such + as smartphones. + + However, the capabilities described go beyond those available to our + idealized attacker, including: + + o Decryption of TLS-protected Internet sessions [dec1][dec2][dec3]. + For example, the NSA BULLRUN project appears to have had a budget + of around $250M per year to undermine encryption through multiple + approaches. + + o Insertion of NSA devices as a man-in-the-middle of Internet + transactions [TOR1][TOR2]. For example, the NSA QUANTUM system + appears to use several different techniques to hijack HTTP + connections, ranging from DNS response injection to HTTP 302 + redirects. + + o Direct acquisition of bulk data and metadata from service + providers [dir1][dir2][dir3]. For example, the NSA PRISM program + provides the agency with access to many types of user data (e.g., + email, chat, VoIP). + + + + +Barnes, et al. Expires August 24, 2015 [Page 10] + +Internet-Draft Confidentiality Threat Model February 2015 + + + o Use of implants (covert modifications or malware) to undermine + security and anonymity features [dec2][TOR1][TOR2]. For example: + + * NSA appears to use the QUANTUM man-in-the-middle system to + direct users to a FOXACID server, which delivers an implant to + compromise the browser of a user of the Tor anonymous + communications network. + + * Implants are apparently available for Cisco, Juniper, Huawei, + Dell, and HP network elements, provided by the NSA Advanced + Network Technology group [spiegel1] + + * Compromised hosts at botnet scale, using tools by the NSA's + Remote Operations Center [spiegel3] + + * The BULLRUN program mentioned above includes the addition of + covert modifications to software as one means to undermine + encryption. + + * There is also some suspicion that NSA modifications to the + DUAL_EC_DRBG random number generator were made to ensure that + keys generated using that generator could be predicted by NSA. + These suspicions have been reinforced by reports that RSA + Security was paid roughly $10M to make DUAL_EC_DRBG the default + in their products. + + We use the term "pervasive attack" [RFC7258] to collectively describe + these operations. The term "pervasive" is used because the attacks + are designed to indiscriminately gather as much data as possible and + to apply selective analysis on targets after the fact. This means + that all, or nearly all, Internet communications are targets for + these attacks. To achieve this scale, the attacks are physically + pervasive; they affect a large number of Internet communications. + They are pervasive in content, consuming and exploiting any + information revealed by the protocol. And they are pervasive in + technology, exploiting many different vulnerabilities in many + different protocols. + + It's important to note that although the attacks mentioned above were + executed by NSA and GCHQ, there are many other organizations that can + mount pervasive surveillance attacks. Because of the resources + required to achieve pervasive scale, these attacks are most commonly + undertaken by nation-state actors. For example, the Chinese Internet + filtering system known as the "Great Firewall of China" uses several + techniques that are similar to the QUANTUM program, and which have a + high degree of pervasiveness with regard to the Internet in China. + + + + + +Barnes, et al. Expires August 24, 2015 [Page 11] + +Internet-Draft Confidentiality Threat Model February 2015 + + +5. Threat Model + + Given these disclosures, we must consider a broader threat model. + + Pervasive surveillance aims to collect information across a large + number of Internet communications, analyzing the collected + communications to identify information of interest within individual + communications, or inferring information from correlated + communications. his analysis sometimes benefits from decryption of + encrypted communications and deanonymization of anonymized + communications. As a result, these attackers desire both access to + the bulk of Internet traffic and to the keying material required to + decrypt any traffic that has been encrypted. Even if keys are not + available, note that the presence of a communication and the fact + that it is encrypted may both be inputs to an analysis, even if the + attacker cannot decrypt the communication. + + The attacks listed above highlight new avenues both for access to + traffic and for access to relevant encryption keys. They further + indicate that the scale of surveillance is sufficient to provide a + general capability to cross-correlate communications, a threat not + previously thought to be relevant at the scale of the Internet. + +5.1. Attacker Capabilities + + +--------------------------+-------------------------------------+ + | Attack Class | Capability | + +--------------------------+-------------------------------------+ + | Passive observation | Directly capture data in transit | + | | | + | Passive inference | Infer from reduced/encrypted data | + | | | + | Active | Manipulate / inject data in transit | + | | | + | Static key exfiltration | Obtain key material once / rarely | + | | | + | Dynamic key exfiltration | Obtain per-session key material | + | | | + | Content exfiltration | Access data at rest | + +--------------------------+-------------------------------------+ + + Security analyses of Internet protocols commonly consider two classes + of attacker: flow access attackers, who can simply listen in on + communications as they transit the network, and flow modification + attackers, who can modify or delete packets in addition to simply + collecting them. + + + + + +Barnes, et al. Expires August 24, 2015 [Page 12] + +Internet-Draft Confidentiality Threat Model February 2015 + + + In the context of pervasive passive surveillance, these attacks take + on an even greater significance. In the past, these attackers were + often assumed to operate near the edge of the network, where attacks + can be simpler. For example, in some LANs, it is simple for any node + to engage in passive listening to other nodes' traffic or inject + packets to accomplish flow modification attacks. However, as we now + know, both passive and flow modification attacks are undertaken by + pervasive attackers closer to the core of the network, greatly + expanding the scope and capability of the attacker. + + Eavesdropping and observation at a larger scale make passive + inference attacks easier to carry out: a flow access attacker with + access to a large portion of the Internet can analyze collected + traffic to create a much more detailed view of individual behavior + than an attacker that collects at a single point. Even the usual + claim that encryption defeats flow access attackers is weakened, + since a pervasive flow access attacker can infer relationships from + correlations over large numbers of sessions, e.g., pairing encrypted + sessions with unencrypted sessions from the same host, or performing + traffic fingerprinting between known and unknown encrypted sessions. + Reports on the NSA XKEYSCORE system would indicate it is an example + of such an attacker. + + A pervasive flow modification attacker likewise has capabilities + beyond those of a localized flow modification attacker. flow + modification attacks are often limited by network topology, for + example by a requirement that the attacker be able to see a targeted + session as well as inject packets into it. A pervasive flow + modification attacker with access at multiple points within the core + of the Internet is able to overcome these topological limitations and + perform attacks over a much broader scope. Being positioned in the + core of the network rather than the edge can also enable a pervasive + flow modification attacker to reroute targeted traffic, amplifying + the ability to perform both eavesdropping and traffic injection. + Pervasive flow modification attackers can also benefit from pervasive + passive collection to identify vulnerable hosts. + + While not directly related to pervasiveness, attackers that are in a + position to mount a pervasive flow modification attack are also often + in a position to subvert authentication, a traditional protection + against such attacks. Authentication in the Internet is often + achieved via trusted third party authorities such as the Certificate + Authorities (CAs) that provide web sites with authentication + credentials. An attacker with sufficient resources may also be able + to induce an authority to grant credentials for an identity of the + attacker's choosing. If the parties to a communication will trust + multiple authorities to certify a specific identity, this attack may + be mounted by suborning any one of the authorities (the proverbial + + + +Barnes, et al. Expires August 24, 2015 [Page 13] + +Internet-Draft Confidentiality Threat Model February 2015 + + + "weakest link"). Subversion of authorities in this way can allow an + flow modification attack to succeed in spite of an authentication + check. + + Beyond these three classes (observation, inference, and active), + reports on the BULLRUN effort to defeat encryption and the PRISM + effort to obtain data from service providers suggest three more + classes of attack: + + o Static key exfiltration + + o Dynamic key exfiltration + + o Content exfiltration + + These attacks all rely on a collaborator providing the attacker with + some information, either keys or data. These attacks have not + traditionally been considered in scope for the Security + Considerations sections of IETF protocols, as they occur outside the + protocol. + + The term "key exfiltration" refers to the transfer of keying material + for an encrypted communication from the collaborator to the attacker. + By "static", we mean that the transfer of keys happens once, or + rarely, typically of a long-lived key. For example, this case would + cover a web site operator that provides the private key corresponding + to its HTTPS certificate to an intelligence agency. + + "Dynamic" key exfiltration, by contrast, refers to attacks in which + the collaborator delivers keying material to the attacker frequently, + e.g., on a per-session basis. This does not necessarily imply + frequent communications with the attacker; the transfer of keying + material may be virtual. For example, if an endpoint were modified + in such a way that the attacker could predict the state of its + psuedorandom number generator, then the attacker would be able to + derive per-session keys even without per-session communications. + + Finally, content exfiltration is the attack in which the collaborator + simply provides the attacker with the desired data or metadata. + Unlike the key exfiltration cases, this attack does not require the + attacker to capture the desired data as it flows through the network. + The risk is to data at rest as opposed to data in transit. This + increases the scope of data that the attacker can obtain, since the + attacker can access historical data - the attacker does not have to + be listening at the time the communication happens. + + Exfiltration attacks can be accomplished via attacks against one of + the parties to a communication, i.e., by the attacker stealing the + + + +Barnes, et al. Expires August 24, 2015 [Page 14] + +Internet-Draft Confidentiality Threat Model February 2015 + + + keys or content rather than the party providing them willingly. In + these cases, the party may not be aware that they are collaborating, + at least at a human level. Rather, the subverted technical assets + are "collaborating" with the attacker (by providing keys/content) + without their owner's knowledge or consent. + + Any party that has access to encryption keys or unencrypted data can + be a collaborator. While collaborators are typically the endpoints + of a communication (with encryption securing the links), + intermediaries in an unencrypted communication can also facilitate + content exfiltration attacks as collaborators by providing the + attacker access to those communications. For example, documents + describing the NSA PRISM program claim that NSA is able to access + user data directly from servers, where it is stored unencrypted. In + these cases, the operator of the server would be a collaborator, if + an unwitting one. By contrast, in the NSA MUSCULAR program, a set of + collaborators enabled attackers to access the cables connecting data + centers used by service providers such as Google and Yahoo. Because + communications among these data centers were not encrypted, the + collaboration by an intermediate entity allowed NSA to collect + unencrypted user data. + +5.2. Attacker Costs + + +--------------------------+-----------------------------------+ + | Attack Class | Cost / Risk to Attacker | + +--------------------------+-----------------------------------+ + | Passive observation | Passive data access | + | | | + | Passive inference | Passive data access + processing | + | | | + | Active | Active data access + processing | + | | | + | Static key exfiltration | One-time interaction | + | | | + | Dynamic key exfiltration | Ongoing interaction / code change | + | | | + | Content exfiltration | Ongoing, bulk interaction | + +--------------------------+-----------------------------------+ + + Each of the attack types discussed in the previous section entails + certain costs and risks. These costs differ by attack, and can be + helpful in guiding response to pervasive attack. + + Depending on the attack, the attacker may be exposed to several types + of risk, ranging from simply losing access to arrest or prosecution. + In order for any of these negative consequences to occur, however, + + + + +Barnes, et al. Expires August 24, 2015 [Page 15] + +Internet-Draft Confidentiality Threat Model February 2015 + + + the attacker must first be discovered and identified. So the primary + risk we focus on here is the risk of discovery and attribution. + + A flow access attack is the simplest to mount in some ways. The base + requirement is that the attacker obtain physical access to a + communications medium and extract communications from it. For + example, the attacker might tap a fiber-optic cable, acquire a mirror + port on a switch, or listen to a wireless signal. The need for these + taps to have physical access or proximity to a link exposes the + attacker to the risk that the taps will be discovered. For example, + a fiber tap or mirror port might be discovered by network operators + noticing increased attenuation in the fiber or a change in switch + configuration. Of course, flow access attacks may be accomplished + with the cooperation of the network operator, in which case there is + a risk that the attacker's interactions with the network operator + will be exposed. + + In many ways, the costs and risks for an flow modification attack are + similar to those for a flow access attack, with a few additions. An + flow modification attacker requires more robust network access than a + flow access attacker, since for example they will often need to + transmit data as well as receiving it. In the wireless example + above, the attacker would need to act as an transmitter as well as + receiver, greatly increasing the probability the attacker will be + discovered (e.g., using direction-finding technology). flow + modification attacks are also much more observable at higher layers + of the network. For example, an flow modification attacker that + attempts to use a mis-issued certificate could be detected via + Certificate Transparency [RFC6962]. + + In terms of raw implementation complexity, flow access attacks + require only enough processing to extract information from the + network and store it. flow modification attacks, by contrast, often + depend on winning race conditions to inject pakets into active + connections. So flow modification attacks in the core of the network + require processing hardware to that can operate at line speed + (roughly 100Gbps to 1Tbps in the core) to identify opportunities for + attack and insert attack traffic in a high-volume traffic. Key + exfiltration attacks rely on flow access attack for access to + encrypted data, with the collaborator providing keys to decrypt the + data. So the attacker undertakes the cost and risk of a flow access + attack, as well as additional risk of discovery via the interactions + that the attacker has with the collaborator. + + In this sense, static exfiltration has a lower risk profile than + dynamic. In the static case, the attacker need only interact with + the collaborator a small number of times, possibly only once, say to + exchange a private key. In the dynamic case, the attacker must have + + + +Barnes, et al. Expires August 24, 2015 [Page 16] + +Internet-Draft Confidentiality Threat Model February 2015 + + + continuing interactions with the collaborator. As noted above these + interactions may real, such as in-person meetings, or virtual, such + as software modifications that render keys available to the attacker. + Both of these types of interactions introduce a risk that they will + be discovered, e.g., by employees of the collaborator organization + noticing suspicious meetings or suspicious code changes. + + Content exfiltration has a similar risk profile to dynamic key + exfiltration. In a content exfiltration attack, the attacker saves + the cost and risk of conducting a flow access attack. The risk of + discovery through interactions with the collaborator, however, is + still present, and may be higher. The content of a communication is + obviously larger than the key used to encrypt it, often by several + orders of magnitude. So in the content exfiltration case, the + interactions between the collaborator and the attacker need to be + much higher-bandwidth than in the key exfiltration cases, with a + corresponding increase in the risk that this high-bandwidth channel + will be discovered. + + It should also be noted that in these latter three exfiltration + cases, the collaborator also undertakes a risk that his collaboration + with the attacker will be discovered. Thus the attacker may have to + incur additional cost in order to convince the collaborator to + participate in the attack. Likewise, the scope of these attacks is + limited to case where the attacker can convince a collaborator to + participate. If the attacker is a national government, for example, + it may be able to compel participation within its borders, but have a + much more difficult time recruiting foreign collaborators. + + As noted above, the collaborator in an exfiltration attack can be + unwitting; the attacker can steal keys or data to enable the attack. + In some ways, the risks of this approach are similar to the case of + an active collaborator. In the static case, the attacker needs to + steal information from the collaborator once; in the dynamic case, + the attacker needs to continued presence inside the collaborators + systems. The main difference is that the risk in this case is of + automated discovery (e.g., by intrusion detection systems) rather + than discovery by humans. + +6. Security Considerations + + This document describes a threat model for pervasive surveillance + attacks. Mitigations are to be given in a future document. + + + + + + + + +Barnes, et al. Expires August 24, 2015 [Page 17] + +Internet-Draft Confidentiality Threat Model February 2015 + + +7. IANA Considerations + + This document has no actions for IANA. + +8. Acknowledgements + + Thanks to Dave Thaler for the list of attacks and taxonomy; to + Security Area Directors Stephen Farrell, Sean Turner, and Kathleen + Moriarty for starting and managing the IETF's discussion on pervasive + attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, + Evangelos Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, as well as + the IAB Privacy and Security Program, for their input. + +9. References + +9.1. Normative References + + [RFC6973] Cooper, A., Tschofenig, H., Aboba, B., Peterson, J., + Morris, J., Hansen, M., and R. Smith, "Privacy + Considerations for Internet Protocols", RFC 6973, July + 2013. + +9.2. Informative References + + [pass1] The Guardian, "How the NSA is still harvesting your online + data", 2013, + . + + [pass2] The Guardian, "NSA's Prism surveillance program: how it + works and what it can do", 2013, + . + + [pass3] The Guardian, "XKeyscore: NSA tool collects 'nearly + everything a user does on the internet'", 2013, + . + + [pass4] The Guardian, "How does GCHQ's internet surveillance + work?", n.d., . + + [dec1] The New York Times, "N.S.A. Able to Foil Basic Safeguards + of Privacy on Web", 2013, + . + + + + +Barnes, et al. Expires August 24, 2015 [Page 18] + +Internet-Draft Confidentiality Threat Model February 2015 + + + [dec2] The Guardian, "Project Bullrun - classification guide to + the NSA's decryption program", 2013, + . + + [dec3] The Guardian, "Revealed: how US and UK spy agencies defeat + internet privacy and security", 2013, + . + + [TOR] The Tor Project, "Tor", 2013, + . + + [TOR1] Schneier, B., "How the NSA Attacks Tor/Firefox Users With + QUANTUM and FOXACID", 2013, + . + + [TOR2] The Guardian, "'Tor Stinks' presentation - read the full + document", 2013, + . + + [dir1] The Guardian, "NSA collecting phone records of millions of + Verizon customers daily", 2013, + . + + [dir2] The Guardian, "NSA Prism program taps in to user data of + Apple, Google and others", 2013, + . + + [dir3] The Guardian, "Sigint - how the NSA collaborates with + technology companies", 2013, + . + + [secure] Schneier, B., "NSA surveillance: A guide to staying + secure", 2013, + . + + [snowden] Technology Review, "NSA Leak Leaves Crypto-Math Intact but + Highlights Known Workarounds", 2013, + . + + + +Barnes, et al. Expires August 24, 2015 [Page 19] + +Internet-Draft Confidentiality Threat Model February 2015 + + + [spiegel1] + C Stocker, ., "NSA's Secret Toolbox: Unit Offers Spy + Gadgets for Every Need", December 2013, + . + + [spiegel3] + H Schmundt, ., "The Digital Arms Race: NSA Preps America + for Future Battle", January 2014, + . + + [key-recovery] + Golle, P., "The Design and Implementation of Protocol- + Based Hidden Key Recovery", 2003, + . + + [RFC1035] Mockapetris, P., "Domain names - implementation and + specification", STD 13, RFC 1035, November 1987. + + [RFC1918] Rekhter, Y., Moskowitz, R., Karrenberg, D., Groot, G., and + E. Lear, "Address Allocation for Private Internets", BCP + 5, RFC 1918, February 1996. + + [RFC1939] Myers, J. and M. Rose, "Post Office Protocol - Version 3", + STD 53, RFC 1939, May 1996. + + [RFC2015] Elkins, M., "MIME Security with Pretty Good Privacy + (PGP)", RFC 2015, October 1996. + + [RFC2821] Klensin, J., "Simple Mail Transfer Protocol", RFC 2821, + April 2001. + + [RFC3261] Rosenberg, J., Schulzrinne, H., Camarillo, G., Johnston, + A., Peterson, J., Sparks, R., Handley, M., and E. + Schooler, "SIP: Session Initiation Protocol", RFC 3261, + June 2002. + + [RFC3365] Schiller, J., "Strong Security Requirements for Internet + Engineering Task Force Standard Protocols", BCP 61, RFC + 3365, August 2002. + + [RFC3501] Crispin, M., "INTERNET MESSAGE ACCESS PROTOCOL - VERSION + 4rev1", RFC 3501, March 2003. + + + + + +Barnes, et al. Expires August 24, 2015 [Page 20] + +Internet-Draft Confidentiality Threat Model February 2015 + + + [RFC3851] Ramsdell, B., "Secure/Multipurpose Internet Mail + Extensions (S/MIME) Version 3.1 Message Specification", + RFC 3851, July 2004. + + [RFC4033] Arends, R., Austein, R., Larson, M., Massey, D., and S. + Rose, "DNS Security Introduction and Requirements", RFC + 4033, March 2005. + + [RFC4301] Kent, S. and K. Seo, "Security Architecture for the + Internet Protocol", RFC 4301, December 2005. + + [RFC4303] Kent, S., "IP Encapsulating Security Payload (ESP)", RFC + 4303, December 2005. + + [RFC4306] Kaufman, C., "Internet Key Exchange (IKEv2) Protocol", RFC + 4306, December 2005. + + [RFC4949] Shirey, R., "Internet Security Glossary, Version 2", RFC + 4949, August 2007. + + [RFC5246] Dierks, T. and E. Rescorla, "The Transport Layer Security + (TLS) Protocol Version 1.2", RFC 5246, August 2008. + + [RFC5321] Klensin, J., "Simple Mail Transfer Protocol", RFC 5321, + October 2008. + + [RFC5655] Trammell, B., Boschi, E., Mark, L., Zseby, T., and A. + Wagner, "Specification of the IP Flow Information Export + (IPFIX) File Format", RFC 5655, October 2009. + + [RFC5750] Ramsdell, B. and S. Turner, "Secure/Multipurpose Internet + Mail Extensions (S/MIME) Version 3.2 Certificate + Handling", RFC 5750, January 2010. + + [RFC6120] Saint-Andre, P., "Extensible Messaging and Presence + Protocol (XMPP): Core", RFC 6120, March 2011. + + [RFC6962] Laurie, B., Langley, A., and E. Kasper, "Certificate + Transparency", RFC 6962, June 2013. + + [RFC6698] Hoffman, P. and J. Schlyter, "The DNS-Based Authentication + of Named Entities (DANE) Transport Layer Security (TLS) + Protocol: TLSA", RFC 6698, August 2012. + + [RFC7011] Claise, B., Trammell, B., and P. Aitken, "Specification of + the IP Flow Information Export (IPFIX) Protocol for the + Exchange of Flow Information", STD 77, RFC 7011, September + 2013. + + + +Barnes, et al. Expires August 24, 2015 [Page 21] + +Internet-Draft Confidentiality Threat Model February 2015 + + + [RFC7258] Farrell, S. and H. Tschofenig, "Pervasive Monitoring Is an + Attack", BCP 188, RFC 7258, May 2014. + +Authors' Addresses + + Richard Barnes + + Email: rlb@ipv.sx + + + Bruce Schneier + + Email: schneier@schneier.com + + + Cullen Jennings + + Email: fluffy@cisco.com + + + Ted Hardie + + Email: ted.ietf@gmail.com + + + Brian Trammell + + Email: ietf@trammell.ch + + + Christian Huitema + + Email: huitema@huitema.net + + + Daniel Borkmann + + Email: dborkman@redhat.com + + + + + + + + + + + + + +Barnes, et al. Expires August 24, 2015 [Page 22] diff --git a/draft-iab-privsec-confidentiality-threat-03.xml b/draft-iab-privsec-confidentiality-threat-03.xml new file mode 100644 index 0000000..8df1731 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-03.xml @@ -0,0 +1,1062 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + +]> + + + + + + Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement + + + +
+ rlb@ipv.sx +
+ + + +
+ schneier@schneier.com +
+ + + +
+ fluffy@cisco.com +
+ + + +
+ ted.ietf@gmail.com +
+ + + +
+ ietf@trammell.ch +
+ + + +
+ huitema@huitema.net +
+ + + +
+ dborkman@redhat.com +
+ + + + + + + + + + + +Documents published since initial revelations in 2013 have revealed +several classes of pervasive surveillance attack on Internet +communications. In this document we develop a threat model that +describes these pervasive attacks. We start by assuming an attacker +with an interest in undetected, indiscriminate eavesdropping, then +expand the threat model with a set of verified attacks that have been +published. + + + + + + + + + + + +
+ +Starting in June 2013, documents released to the press by Edward +Snowden have revealed several operations undertaken by intelligence +agencies to exploit Internet communications for intelligence purposes. +These attacks were largely based on protocol vulnerabilities that were +already known to exist. The attacks were nonetheless striking in +their pervasive nature, both in terms of the amount of Internet +communications targeted, and in terms of the diversity of attack +techniques employed. + +To ensure that the Internet can be trusted by users, it is necessary +for the Internet technical community to address the vulnerabilities +exploited in these attacks . The goal of this document is +to describe more precisely the threats posed by these pervasive +attacks, and based on those threats, lay out the problems that need to +be solved in order to secure the Internet in the face of those +threats. + +The remainder of this document is structured as follows. In +, we describe an idealized flow access attacker, one which +could completely undetectably compromise communications at Internet +scale. In , we provide a brief summary of some attacks +that have been disclosed, and use these to expand the assumed +capabilities of our idealized attacker. Note that we do not attempt +to describe all possible attacks, but focus on those which result in +undetected eavesdropping. describes a threat model based on +these attacks, focusing on classes of attack that have not been a +focus of Internet engineering to date. + +
+
+ +This document makes extensive use of standard security and privacy +terminology; see and . Terms used from + include Eavesdropper, Observer, Initiator, Intermediary, +Recipient, Attack (in a privacy context), Correlation, Fingerprint, +Traffic Analysis, and Identifiability (and related terms). In +addition, we use a few terms that are specific to the attacks +discussed here: + + + + An eavesdropping attack in which the packets +in a traffic stream between two endpoints are eavesdropped upon, but +in which the attacker does not modify the packets in the traffic +stream between two endpoints, modify the treatment of packets in the +traffic stream (e.g. delay, routing), or add or remove packets in the +traffic stream. Flow access attacks are undetectable from the +endpoints. + + An attack which includes both eavesdropping (as in a +flow access attack) as well as modification, addition, or removal of +packets in a traffic stream, or modification of treatment of packets +in the traffic stream. Flow modification attacks provide more +capabilities to the attacker at the cost of possible detection at the +endpoints. + + An attack on Internet communications that makes +use of access at a large number of points in the network, or otherwise +provides the attacker with access to a large amount of Internet +traffic; see + + Information collected directly from communications by an +eavesdropper or observer. For example, the knowledge that +<alice@example.com> sent a message to <bob@example.com> +via SMTP taken from the headers of an observed SMTP message would be +an observation. + + Information extracted from analysis of information collected +directly from communications by an eavesdropper or observer. For +example, the knowledge that a given web page was accessed by a given +IP address, by comparing the size in octets of measured network flow +records to fingerprints derived from known sizes of linked resources +on the web servers involved, would be an inference. + + An entity that is a legitimate participant in a communication, but +who deliberately provides information about that interaction to an +attacker. + + An entity that is a legitimate participant in a communication, and +who is the source of information obtained by the attacker without the +entity’s consent or intention, because the attacker has exploited some +technology used by the entity. + + The transmission of keying material for an encrypted communication +from a collaborator, deliberately or unwittingly, to an attacker + + The transmission of the content of a communication from a collaborator, deliberately or unwittingly, to an attacker + + +
+
+ +In considering the threat posed by pervasive surveillance, we begin by +defining an idealized pervasive flow access attacker. While this attacker +is less capable than those which we now know to have compromised the +Internet from press reports, as elaborated in , it does +set a lower bound on the capabilities of an attacker interested in +indiscriminate passive surveillance while interested in remaining +undetectable. We note that, prior to the Snowden revelations in 2013, +the assumptions of attacker capability presented here would be +considered on the border of paranoia outside the network security +community. + +Our idealized attacker is an indiscriminate eavesdropper on an Internet-attached computer network that: + + + can observe every packet of all communications at any hop in any network path between an initiator and a recipient; + can observe data at rest in any intermediate system between the endpoints controlled by the initiator and recipient; and + can share information with other such attackers; but + takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.). + + +The techniques available to our ideal attacker are direct observation +and inference. Direct observation involves taking information directly +from eavesdropped communications - e.g., URLs identifying content or +email addresses identifying individuals from application-layer +headers. Inference, on the other hand, involves analyzing eavesdropped +information to derive new information from it; e.g., searching for +application or behavioral fingerprints in observed traffic to derive +information about the observed individual from them, in absence of +directly-observed sources of the same information. The use of +encryption to protect confidentiality is generally enough to prevent +direct observation of unencrypted content, assuming uncompromised +encryption implementations and key material. However, it provides less +complete protection against inference, especially inference based only +on unprotected portions of communications (e.g. IP and TCP headers for +TLS ). + +
+ +Protocols which do not encrypt their payload make the entire content +of the communication available to the idealized attacker along their +path. Following the advice in , most such protocols have a +secure variant which encrypts payload for confidentiality, and these +secure variants are seeing ever-wider deployment. A noteworthy +exception is DNS , as DNSSEC does not have +confidentiality as a requirement. This implies that, in the absence of +changes to the protocol as presently under development in the DPRIVE +working group, all DNS queries and answers generated by the activities +of any protocol are available to the attacker. + +Protocols which imply the storage of some data at rest in +intermediaries (e.g. SMTP ) leave this data subject to +observation by an attacker that has compromised these intermediaries, +unless the data is encrypted end-to-end by the application layer +protocol, or the implementation uses an encrypted store for this data. + +
+
+ +Inference is information extracted from later analysis of an observed +or eavesdropped communication, and/or correlation of observed or +eavesdropped information with information available from other +sources. Indeed, most useful inference performed by the attacker falls +under the rubric of correlation. The simplest example of this is the +observation of DNS queries and answers from and to a source and +correlating those with IP addresses with which that source +communicates. This can give access to information otherwise not +available from encrypted application payloads (e.g., the Host: +HTTP/1.1 request header when HTTP is used with TLS). + +Protocols which encrypt their payload using an application- or +transport-layer encryption scheme (e.g. TLS) still expose all the +information in their network and transport layer headers to the +attacker, including source and destination addresses and ports. IPsec +ESP further encrypts the transport-layer headers, but still +leaves IP address information unencrypted; in tunnel mode, these +addresses correspond to the tunnel endpoints. Features of the +cryptographic protocols themselves, e.g. the TLS session identifier, +may leak information that can be used for correlation and +inference. While this information is much less semantically rich than +the application payload, it can still be useful for the inferring an +individual’s activities. + +Inference can also leverage information obtained from sources other +than direct traffic observation. Geolocation databases, for example, +have been developed map IP addresses to a location, in order to +provide location-aware services such as targeted advertising. This +location information is often of sufficient resolution that it can be +used to draw further inferences toward identifying or profiling an +individual. + +Social media provide another source of more or less publicly +accessible information. This information can be extremely semantically +rich, including information about an individual’s location, +associations with other individuals and groups, and +activities. Further, this information is generally contributed and +curated voluntarily by the individuals themselves: it represents +information which the individuals are not necessarily interested in +protecting for privacy reasons. However, correlation of this social +networking data with information available from direct observation of +network traffic allows the creation of a much richer picture of an +individual’s activities than either alone. + +We note with some alarm that there is little that can be done at +protocol design time to limit such correlation by the attacker, and +that the existence of such data sources in many cases greatly +complicates the problem of protecting privacy by hardening protocols +alone. + +
+
+ +To illustrate how capable the idealized attacker is even given its +limitations, we explore the non-anonymity of encrypted IP traffic in +this section. Here we examine in detail some inference techniques for +associating a set of addresses with an individual, in order to +illustrate the difficulty of defending communications against our +idealized attacker. Here, the basic problem is that information +radiated even from protocols which have no obvious connection with +personal data can be correlated with other information which can paint +a very rich behavioral picture, that only takes one unprotected link +in the chain to associate with an identity. + +
+ +Internet traffic can be monitored by tapping Internet links, or by +installing monitoring tools in Internet routers. Of course, a single +link or a single router only provides access to a fraction of the +global Internet traffic. However, monitoring a number of high capacity +links or a set of routers placed at strategic locations provides +access to a good sampling of Internet traffic. + +Tools like IPFIX allow administrators to acquire +statistics about sequences of packets with some common properties that +pass through a network device. The most common set of properties used +in flow measurement is the “five-tuple”of source and destination +addresses, protocol type, and source and destination ports. These +statistics are commonly used for network engineering, but could +certainly be used for other purposes. + +Let’s assume for a moment that IP addresses can be correlated to +specific services or specific users. Analysis of the sequences of +packets will quickly reveal which users use what services, and also +which users engage in peer-to-peer connections with other +users. Analysis of traffic variations over time can be used to detect +increased activity by particular users, or in the case of peer-to-peer +connections increased activity within groups of users. + +
+
+ +The correlation of IP addresses with specific users can be done in +various ways. For example, tools like reverse DNS lookup can be used +to retrieve the DNS names of servers. Since the addresses of servers +tend to be quite stable and since servers are relatively less numerous +than users, an attacker could easily maintain its own copy of the DNS +for well-known or popular servers, to accelerate such lookups. + +On the other hand, the reverse lookup of IP addresses of users is +generally less informative. For example, a lookup of the address +currently used by one author’s home network returns a name of the form +“c-192-000-002-033.hsd1.wa.comcast.net”. This particular type of +reverse DNS lookup generally reveals only coarse-grained location or +provider information, equivalent to that available from geolocation +databases. + +In many jurisdictions, Internet Service Providers (ISPs) are required +to provide identification on a case by case basis of the “owner” of a +specific IP address for law enforcement purposes. This is a reasonably +expedient process for targeted investigations, but pervasive +surveillance requires something more efficient. This provides an +incentive for the attacker to secure the cooperation of the ISP in +order to automate this correlation. + +
+
+ +Even if the ISP does not cooperate, user identity can often be +obtained via inference. POP3 and IMAP are used +to retrieve mail from mail servers, while a variant of SMTP is used to +submit messages through mail servers. IMAP connections originate from +the client, and typically start with an authentication exchange in +which the client proves its identity by answering a password +challenge. The same holds for the SIP protocol and many +instant messaging services operating over the Internet using +proprietary protocols. + +The username is directly observable if any of these protocols operate +in cleartext; the username can then be directly associated with the +source address. + +
+
+ +SMTP requires that each successive SMTP relay adds a +“Received” header to the mail headers. The purpose of these headers is +to enable audit of mail transmission, and perhaps to distinguish +between regular mail and spam. Here is an extract from the headers of +a message recently received from the “perpass” mailing list: + + + Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?) + (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA + (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100 + Message-ID: <526D7BD2.7070908@example.org> + Date: Sun, 27 Oct 2013 20:47:14 +0000 + From: Some One <some.one@example.org> + + +This is the first “Received” header attached to the message by the +first SMTP relay; for privacy reasons, the field values have been +anonymized. We learn here that the message was submitted by “Some One” +on October 27, from a host behind a NAT (192.168.1.100) +that used the IP address 192.0.2.44. The information remained in the +message, and is accessible by all recipients of the “perpass” mailing +list, or indeed by any attacker that sees at least one copy of the +message. + +An attacker that can observe sufficient email traffic can regularly +update the mapping between public IP addresses and individual email +identities. Even if the SMTP traffic was encrypted on submission and +relaying, the attacker can still receive a copy of public mailing +lists like “perpass”. + +
+
+ +Many web sites only encrypt a small fraction of their transactions. A +popular pattern is to use HTTPS for the login information, and then +use a “cookie” to associate following clear-text transactions with the +user’s identity. Cookies are also used by various advertisement +services to quickly identify the users and serve them with +“personalized” advertisements. Such cookies are particularly useful if +the advertisement services want to keep tracking the user across +multiple sessions that may use different IP addresses. + +As cookies are sent in clear text, an attacker can build a database +that associates cookies to IP addresses for non-HTTPS traffic. If the +IP address is already identified, the cookie can be linked to the user +identify. After that, if the same cookie appears on a new IP address, +the new IP address can be immediately associated with the +pre-determined identity. + +
+
+ +An attacker can track traffic from an IP address not yet associated +with an individual to various public services (e.g. websites, mail +servers, game servers), and exploit patterns in the observed traffic +to correlate this address with other addresses that show similar +patterns. For example, any two addresses that show connections to the +same IMAP or webmail services, the same set of favorite websites, and +game servers at similar times of day may be associated with the same +individual. Correlated addresses can then be tied to an individual +through one of the techniques above, walking the “network graph” to +expand the set of attributable traffic. + +
+
+ +Moving back down the stack, technologies like Ethernet or Wi-Fi use +MAC Addresses to identify link-level destinations. MAC Addresses +assigned according to IEEE-802 standards are unique to the device. If +the link is publicly accessible, an attacker can track it. For +example, the attacker can track the wireless traffic at public Wi-Fi +networks. Simple devices can monitor the traffic, and reveal which MAC +Addresses are present. If the network does not use some form of Wi-Fi +encryption, or if the attacker can access the decrypted traffic, the +analysis will also provide the correlation between MAC Addresses and +IP addresses. Additional monitoring using techniques exposed in the +previous sections will reveal the correlation between MAC Addresses, +IP Addresses, and user identity. + +Given that large-scale databases of the MAC addresses of wireless +access points for geolocation purposes have been known to exist for +some time, the attacker could easily build a database linking MAC +Addresses and device or user identities, and use it to track the +movement of devices and of their owners. + +
+
+
+
+ +The situation in reality is more bleak than that suggested by an +analysis of our idealized attacker. Through revelations of sensitive +documents in several media outlets, the Internet community has been +made aware of several intelligence activities conducted by US and UK +national intelligence agencies, particularly the US National Security +Agency (NSA) and the UK Government Communications Headquarters +(GCHQ). These documents have revealed methods that these agencies use +to attack Internet applications and obtain sensitive user information. + +First, they have confirmed that these agencies have capabilities in +line with those of our idealized attacker, thorugh the large-scale +passive collection of Internet traffic +. For example: - The NSA XKEYSCORE +system accesses data from multiple access points and searches for +“selectors” such as email addresses, at the scale of tens of terabytes +of data per day. - The GCHQ Tempora system appears to have access to +around 1,500 major cables passing through the UK. - The NSA MUSCULAR +program tapped cables between data centers belonging to major service +providers. - Several programs appear to perform wide-scale collection +of cookies in web traffic and location data from location-aware +portable devices such as smartphones. + +However, the capabilities described go beyond those available to our idealized attacker, including: + + + Decryption of TLS-protected Internet sessions +. For example, the NSA BULLRUN project +appears to have had a budget of around $250M per year to undermine +encryption through multiple approaches. + Insertion of NSA devices as a man-in-the-middle of Internet +transactions . For example, the NSA QUANTUM system +appears to use several different techniques to hijack HTTP +connections, ranging from DNS response injection to HTTP 302 +redirects. + Direct acquisition of bulk data and metadata from service providers +. For example, the NSA PRISM program +provides the agency with access to many types of user data (e.g., +email, chat, VoIP). + Use of implants (covert modifications or malware) to undermine security and anonymity features . For example: + NSA appears to use the QUANTUM man-in-the-middle system to direct users to a FOXACID server, which delivers an implant to compromise the browser of a user of the Tor anonymous communications network. + Implants are apparently available for Cisco, Juniper, Huawei, Dell, and HP network elements, provided by the NSA Advanced Network Technology group + Compromised hosts at botnet scale, using tools by the NSA’s Remote Operations Center + The BULLRUN program mentioned above includes the addition of covert modifications to software as one means to undermine encryption. + There is also some suspicion that NSA modifications to the DUAL_EC_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA. These suspicions have been reinforced by reports that RSA Security was paid roughly $10M to make DUAL_EC_DRBG the default in their products. + + + +We use the term “pervasive attack” to collectively +describe these operations. The term “pervasive” is used because the +attacks are designed to indiscriminately gather as much data as +possible and to apply selective analysis on targets after the fact. +This means that all, or nearly all, Internet communications are +targets for these attacks. To achieve this scale, the attacks are +physically pervasive; they affect a large number of Internet +communications. They are pervasive in content, consuming and +exploiting any information revealed by the protocol. And they are +pervasive in technology, exploiting many different vulnerabilities in +many different protocols. + +It’s important to note that although the attacks mentioned above were +executed by NSA and GCHQ, there are many other organizations that can +mount pervasive surveillance attacks. Because of the resources +required to achieve pervasive scale, these attacks are most commonly +undertaken by nation-state actors. For example, the Chinese Internet +filtering system known as the “Great Firewall of China” uses several +techniques that are similar to the QUANTUM program, and which have a +high degree of pervasiveness with regard to the Internet in China. + +
+
+ +Given these disclosures, we must consider a broader threat model. + +Pervasive surveillance aims to collect information across a large +number of Internet communications, analyzing the collected +communications to identify information of interest within individual +communications, or inferring information from correlated +communications. his analysis sometimes benefits from decryption of +encrypted communications and deanonymization of anonymized +communications. As a result, these attackers desire both access to +the bulk of Internet traffic and to the keying material required to +decrypt any traffic that has been encrypted. Even if keys are not +available, note that the presence of a communication and the fact that +it is encrypted may both be inputs to an analysis, even if the +attacker cannot decrypt the communication. + +The attacks listed above highlight new avenues both for access to +traffic and for access to relevant encryption keys. They further +indicate that the scale of surveillance is sufficient to provide a +general capability to cross-correlate communications, a threat not +previously thought to be relevant at the scale of the Internet. + +
+ + + Attack Class + Capability + Passive observation + Directly capture data in transit + Passive inference + Infer from reduced/encrypted data + Active + Manipulate / inject data in transit + Static key exfiltration + Obtain key material once / rarely + Dynamic key exfiltration + Obtain per-session key material + Content exfiltration + Access data at rest + + +Security analyses of Internet protocols commonly consider two classes +of attacker: flow access attackers, who can simply listen in on +communications as they transit the network, and flow modification +attackers, who can modify or delete packets in addition to simply +collecting them. + +In the context of pervasive passive surveillance, these attacks take +on an even greater significance. In the past, these attackers were +often assumed to operate near the edge of the network, where attacks +can be simpler. For example, in some LANs, it is simple for any node +to engage in passive listening to other nodes’ traffic or inject +packets to accomplish flow modification attacks. However, as we now +know, both passive and flow modification attacks are undertaken by +pervasive attackers closer to the core of the network, greatly +expanding the scope and capability of the attacker. + +Eavesdropping and observation at a larger scale make passive inference +attacks easier to carry out: a flow access attacker with access to a +large portion of the Internet can analyze collected traffic to create +a much more detailed view of individual behavior than an attacker that +collects at a single point. Even the usual claim that encryption +defeats flow access attackers is weakened, since a pervasive flow +access attacker can infer relationships from correlations over large +numbers of sessions, e.g., pairing encrypted sessions with unencrypted +sessions from the same host, or performing traffic fingerprinting +between known and unknown encrypted sessions. Reports on the NSA +XKEYSCORE system would indicate it is an example of such an attacker. + +A pervasive flow modification attacker likewise has capabilities +beyond those of a localized flow modification attacker. flow +modification attacks are often limited by network topology, for +example by a requirement that the attacker be able to see a targeted +session as well as inject packets into it. A pervasive flow +modification attacker with access at multiple points within the core +of the Internet is able to overcome these topological limitations and +perform attacks over a much broader scope. Being positioned in the +core of the network rather than the edge can also enable a pervasive +flow modification attacker to reroute targeted traffic, amplifying the +ability to perform both eavesdropping and traffic injection. +Pervasive flow modification attackers can also benefit from pervasive +passive collection to identify vulnerable hosts. + +While not directly related to pervasiveness, attackers that are in a +position to mount a pervasive flow modification attack are also often +in a position to subvert authentication, a traditional protection +against such attacks. Authentication in the Internet is often +achieved via trusted third party authorities such as the Certificate +Authorities (CAs) that provide web sites with authentication +credentials. An attacker with sufficient resources may also be able to +induce an authority to grant credentials for an identity of the +attacker’s choosing. If the parties to a communication will trust +multiple authorities to certify a specific identity, this attack may +be mounted by suborning any one of the authorities (the proverbial +“weakest link”). Subversion of authorities in this way can allow an +flow modification attack to succeed in spite of an authentication +check. + +Beyond these three classes (observation, inference, and active), +reports on the BULLRUN effort to defeat encryption and the PRISM +effort to obtain data from service providers suggest three more +classes of attack: + + + Static key exfiltration + Dynamic key exfiltration + Content exfiltration + + +These attacks all rely on a collaborator providing the attacker with +some information, either keys or data. These attacks have not +traditionally been considered in scope for the Security Considerations +sections of IETF protocols, as they occur outside the protocol. + +The term “key exfiltration” refers to the transfer of keying material +for an encrypted communication from the collaborator to the attacker. +By “static”, we mean that the transfer of keys happens once, or +rarely, typically of a long-lived key. For example, this case would +cover a web site operator that provides the private key corresponding +to its HTTPS certificate to an intelligence agency. + +“Dynamic” key exfiltration, by contrast, refers to attacks in which +the collaborator delivers keying material to the attacker frequently, +e.g., on a per-session basis. This does not necessarily imply +frequent communications with the attacker; the transfer of keying +material may be virtual. For example, if an endpoint were modified in +such a way that the attacker could predict the state of its +psuedorandom number generator, then the attacker would be able to +derive per-session keys even without per-session communications. + +Finally, content exfiltration is the attack in which the collaborator +simply provides the attacker with the desired data or metadata. Unlike +the key exfiltration cases, this attack does not require the attacker +to capture the desired data as it flows through the network. The risk +is to data at rest as opposed to data in transit. This increases the +scope of data that the attacker can obtain, since the attacker can +access historical data – the attacker does not have to be listening +at the time the communication happens. + +Exfiltration attacks can be accomplished via attacks against one of +the parties to a communication, i.e., by the attacker stealing the +keys or content rather than the party providing them willingly. In +these cases, the party may not be aware that they are collaborating, +at least at a human level. Rather, the subverted technical assets are +“collaborating” with the attacker (by providing keys/content) without +their owner’s knowledge or consent. + +Any party that has access to encryption keys or unencrypted data can +be a collaborator. While collaborators are typically the endpoints of +a communication (with encryption securing the links), intermediaries +in an unencrypted communication can also facilitate content +exfiltration attacks as collaborators by providing the attacker access +to those communications. For example, documents describing the NSA +PRISM program claim that NSA is able to access user data directly from +servers, where it is stored unencrypted. In these cases, the operator +of the server would be a collaborator, if an unwitting one. By +contrast, in the NSA MUSCULAR program, a set of collaborators enabled +attackers to access the cables connecting data centers used by service +providers such as Google and Yahoo. Because communications among +these data centers were not encrypted, the collaboration by an +intermediate entity allowed NSA to collect unencrypted user data. + +
+
+ + + Attack Class + Cost / Risk to Attacker + Passive observation + Passive data access + Passive inference + Passive data access + processing + Active + Active data access + processing + Static key exfiltration + One-time interaction + Dynamic key exfiltration + Ongoing interaction / code change + Content exfiltration + Ongoing, bulk interaction + + +Each of the attack types discussed in the previous section entails +certain costs and risks. These costs differ by attack, and can be +helpful in guiding response to pervasive attack. + +Depending on the attack, the attacker may be exposed to several types +of risk, ranging from simply losing access to arrest or prosecution. +In order for any of these negative consequences to occur, however, the +attacker must first be discovered and identified. So the primary risk +we focus on here is the risk of discovery and attribution. + +A flow access attack is the simplest to mount in some ways. The base +requirement is that the attacker obtain physical access to a +communications medium and extract communications from it. For +example, the attacker might tap a fiber-optic cable, acquire a mirror +port on a switch, or listen to a wireless signal. The need for these +taps to have physical access or proximity to a link exposes the +attacker to the risk that the taps will be discovered. For example, a +fiber tap or mirror port might be discovered by network operators +noticing increased attenuation in the fiber or a change in switch +configuration. Of course, flow access attacks may be accomplished +with the cooperation of the network operator, in which case there is a +risk that the attacker’s interactions with the network operator will +be exposed. + +In many ways, the costs and risks for an flow modification attack are +similar to those for a flow access attack, with a few additions. An +flow modification attacker requires more robust network access than a +flow access attacker, since for example they will often need to +transmit data as well as receiving it. In the wireless example above, +the attacker would need to act as an transmitter as well as receiver, +greatly increasing the probability the attacker will be discovered +(e.g., using direction-finding technology). flow modification attacks +are also much more observable at higher layers of the network. For +example, an flow modification attacker that attempts to use a +mis-issued certificate could be detected via Certificate Transparency +. + +In terms of raw implementation complexity, flow access attacks require +only enough processing to extract information from the network and +store it. flow modification attacks, by contrast, often depend on +winning race conditions to inject pakets into active connections. So +flow modification attacks in the core of the network require +processing hardware to that can operate at line speed (roughly 100Gbps +to 1Tbps in the core) to identify opportunities for attack and insert +attack traffic in a high-volume traffic. Key exfiltration attacks +rely on flow access attack for access to encrypted data, with the +collaborator providing keys to decrypt the data. So the attacker +undertakes the cost and risk of a flow access attack, as well as +additional risk of discovery via the interactions that the attacker +has with the collaborator. + +In this sense, static exfiltration has a lower risk profile than +dynamic. In the static case, the attacker need only interact with the +collaborator a small number of times, possibly only once, say to +exchange a private key. In the dynamic case, the attacker must have +continuing interactions with the collaborator. As noted above these +interactions may real, such as in-person meetings, or virtual, such as +software modifications that render keys available to the attacker. +Both of these types of interactions introduce a risk that they will be +discovered, e.g., by employees of the collaborator organization +noticing suspicious meetings or suspicious code changes. + +Content exfiltration has a similar risk profile to dynamic key +exfiltration. In a content exfiltration attack, the attacker saves +the cost and risk of conducting a flow access attack. The risk of +discovery through interactions with the collaborator, however, is +still present, and may be higher. The content of a communication is +obviously larger than the key used to encrypt it, often by several +orders of magnitude. So in the content exfiltration case, the +interactions between the collaborator and the attacker need to be much +higher-bandwidth than in the key exfiltration cases, with a +corresponding increase in the risk that this high-bandwidth channel +will be discovered. + +It should also be noted that in these latter three exfiltration cases, +the collaborator also undertakes a risk that his collaboration with +the attacker will be discovered. Thus the attacker may have to incur +additional cost in order to convince the collaborator to participate +in the attack. Likewise, the scope of these attacks is limited to +case where the attacker can convince a collaborator to participate. +If the attacker is a national government, for example, it may be able +to compel participation within its borders, but have a much more +difficult time recruiting foreign collaborators. + +As noted above, the collaborator in an exfiltration attack can be +unwitting; the attacker can steal keys or data to enable the attack. +In some ways, the risks of this approach are similar to the case of an +active collaborator. In the static case, the attacker needs to steal +information from the collaborator once; in the dynamic case, the +attacker needs to continued presence inside the collaborators systems. +The main difference is that the risk in this case is of automated +discovery (e.g., by intrusion detection systems) rather than discovery +by humans. + +
+
+
+ +This document describes a threat model for pervasive surveillance +attacks. Mitigations are to be given in a future document. + +
+
+ +This document has no actions for IANA. + +
+
+ +Thanks to Dave Thaler for the list of attacks and taxonomy; to +Security Area Directors Stephen Farrell, Sean Turner, and Kathleen +Moriarty for starting and managing the IETF’s discussion on pervasive +attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, Evangelos +Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, as well as the IAB +Privacy and Security Program, for their input. + +
+ + + + + + + + +&RFC6973; + + + + + + + + + How the NSA is still harvesting your online data + + The Guardian + + + + + + + NSA's Prism surveillance program: how it works and what it can do + + The Guardian + + + + + + + XKeyscore: NSA tool collects 'nearly everything a user does on the internet' + + The Guardian + + + + + + + How does GCHQ's internet surveillance work? + + The Guardian + + + + + + + N.S.A. Able to Foil Basic Safeguards of Privacy on Web + + The New York Times + + + + + + + Project Bullrun – classification guide to the NSA's decryption program + + The Guardian + + + + + + + Revealed: how US and UK spy agencies defeat internet privacy and security + + The Guardian + + + + + + + Tor + + The Tor Project + + + + + + + How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID + + + + + + + + + 'Tor Stinks' presentation – read the full document + + The Guardian + + + + + + + NSA collecting phone records of millions of Verizon customers daily + + The Guardian + + + + + + + NSA Prism program taps in to user data of Apple, Google and others + + The Guardian + + + + + + + Sigint – how the NSA collaborates with technology companies + + The Guardian + + + + + + + NSA surveillance: A guide to staying secure + + The Guardian + + + + + + + NSA Leak Leaves Crypto-Math Intact but Highlights Known Workarounds + + Technology Review + + + + + + + NSA's Secret Toolbox: Unit Offers Spy Gadgets for Every Need + + + + + + + + + The Digital Arms Race: NSA Preps America for Future Battle + + + + + + + + + The Design and Implementation of Protocol-Based Hidden Key Recovery + + + + + + +&RFC1035; +&RFC1918; +&RFC1939; +&RFC2015; +&RFC2821; +&RFC3261; +&RFC3365; +&RFC3501; +&RFC3851; +&RFC4033; +&RFC4301; +&RFC4303; +&RFC4306; +&RFC4949; +&RFC5246; +&RFC5321; +&RFC5655; +&RFC5750; +&RFC6120; +&RFC6962; +&RFC6698; +&RFC7011; +&RFC7258; + + + + + + + + + diff --git a/draft-iab-privsec-confidentiality-threat-04.md b/draft-iab-privsec-confidentiality-threat-04.md new file mode 100644 index 0000000..3b678c5 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-04.md @@ -0,0 +1,1039 @@ +--- +title: "Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement" +abbrev: Confidentiality Threat Model +docname: draft-iab-privsec-confidentiality-threat-04 +date: 2015-03-11 +category: info +ipr: trust200902 + +author: + - + ins: R. Barnes + name: Richard Barnes + email: rlb@ipv.sx + - + ins: B. Schneier + name: Bruce Schneier + email: schneier@schneier.com + - + ins: C. Jennings + name: Cullen Jennings + email: fluffy@cisco.com + - + ins: T. Hardie + name: Ted Hardie + email: ted.ietf@gmail.com + - + ins: B. Trammell + name: Brian Trammell + email: ietf@trammell.ch + - + ins: C. Huitema + name: Christian Huitema + email: huitema@huitema.net + - + ins: D. Borkmann + name: Daniel Borkmann + email: dborkman@redhat.com + +normative: + RFC6973: + +informative: + pass1: + target: http://www.theguardian.com/world/2013/jun/27/nsa-online-metadata-collection + title: "How the NSA is still harvesting your online data" + author: + organization: The Guardian + date: 2013 + pass2: + target: http://www.theguardian.com/world/2013/jun/08/nsa-prism-server-collection-facebook-google + title: "NSA's Prism surveillance program: how it works and what it can do" + author: + organization: The Guardian + date: 2013 + pass3: + target: http://www.theguardian.com/world/2013/jul/31/nsa-top-secret-program-online-data + title: "XKeyscore: NSA tool collects 'nearly everything a user does on the internet'" + author: + organization: The Guardian + date: 2013 + pass4: + target: http://www.theguardian.com/uk/2013/jun/21/how-does-gchq-internet-surveillance-work + title: "How does GCHQ's internet surveillance work?" + author: + organization: The Guardian + dec1: + target: http://www.nytimes.com/2013/09/06/us/nsa-foils-much-internet-encryption.html + title: "N.S.A. Able to Foil Basic Safeguards of Privacy on Web" + author: + organization: The New York Times + date: 2013 + dec2: + target: http://www.theguardian.com/world/interactive/2013/sep/05/nsa-project-bullrun-classification-guide + title: "Project Bullrun – classification guide to the NSA's decryption program" + author: + organization: The Guardian + date: 2013 + dec3: + target: http://www.theguardian.com/world/2013/sep/05/nsa-gchq-encryption-codes-security + title: "Revealed: how US and UK spy agencies defeat internet privacy and security" + author: + organization: The Guardian + date: 2013 + TOR: + target: https://www.torproject.org/ + title: "Tor" + author: + organization: The Tor Project + date: 2013 + TOR1: + target: https://www.schneier.com/blog/archives/2013/10/how_the_nsa_att.html + title: "How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID" + author: + name: Bruce Schneier + ins: B. Schneier + date: 2013 + TOR2: + target: http://www.theguardian.com/world/interactive/2013/oct/04/tor-stinks-nsa-presentation-document + title: "'Tor Stinks' presentation – read the full document" + author: + organization: The Guardian + date: 2013 + dir1: + target: http://www.theguardian.com/world/2013/jun/06/nsa-phone-records-verizon-court-order + title: "NSA collecting phone records of millions of Verizon customers daily" + author: + organization: The Guardian + date: 2013 + dir2: + target: http://www.theguardian.com/world/2013/jun/06/us-tech-giants-nsa-data + title: "NSA Prism program taps in to user data of Apple, Google and others" + author: + organization: The Guardian + date: 2013 + dir3: + target: http://www.theguardian.com/world/interactive/2013/sep/05/sigint-nsa-collaborates-technology-companies + title: "Sigint – how the NSA collaborates with technology companies" + author: + organization: The Guardian + date: 2013 + secure: + target: http://www.theguardian.com/world/2013/sep/05/nsa-how-to-remain-secure-surveillance + title: "NSA surveillance: A guide to staying secure" + author: + name: Bruce Schneier + ins: B. Schneier + organization: The Guardian + date: 2013 + snowden: + target: http://www.technologyreview.com/news/519171/nsa-leak-leaves-crypto-math-intact-but-highlights-known-workarounds/ + title: "NSA Leak Leaves Crypto-Math Intact but Highlights Known Workarounds" + author: + organization: Technology Review + date: 2013 + spiegel1: + target: http://www.spiegel.de/international/world/nsa-secret-toolbox-ant-unit-offers-spy-gadgets-for-every-need-a-941006.html + title: "NSA's Secret Toolbox: Unit Offers Spy Gadgets for Every Need" + author: + ins: J Applebaum + name: Jacob Applebaum + author: + ins: J Horchert + name: Judith Horchert + author: + ins: O Reissmann + name: Ole Reissmann + author: + ins: M Rosenbach + name: Marcel Rosenbach + author: + ins: J Schindler + name: Jorg Schindler + author: + ins: C Stocker + name: Christian Stocker + date: 2013-12-30 + spiegel3: + target: http://www.spiegel.de/international/world/new-snowden-docs-indicate-scope-of-nsa-preparations-for-cyber-battle-a-1013409.html + title: "The Digital Arms Race: NSA Preps America for Future Battle" + author: + ins: J Appelbaum + name: Jacob Appelbaum + author: + ins: A Gibson + name: Aaron Gibson + author: + ins: C Guarnieri + name: Claudio Guarnieri + author: + ins: A Muller-Maguhn + name: Andy Muller-Maguhn + author: + ins: M Sontheimer + name: Michael Sontheimer + author: + ins: L Poitras + name: Laura Poitras + author: + ins: M Rosenbach + name: Marcel Rosenbach + author: + ins: L Ryge + name: Leif Ryge + author: + ins: H Schmundt + name: Hilmar Schmundt + date: 2014-01-17 + key-recovery: + target: http://crypto.stanford.edu/~pgolle/papers/escrow.pdf + title: The Design and Implementation of Protocol-Based Hidden Key Recovery + author: + ins: E.-J. Goh + name: Eu-Jin Goh + author: + ins: D. Boneh + name: Dan Boneh + author: + ins: B. Pinkas + name: Benny Pinkas + author: + ins: P. Golle + name: Phillippe Golle + date: 2003 + great-cannon: + target: https://citizenlab.org/2015/04/chinas-great-cannon/ + title: "China's Great Cannon" + author: + name: Bill Marczak + ins: B. Marczak + author: + name: Nicholas Weaver + ins: N. Weaver + author: + name: Jakub Dalek + ins: J. Dalek + author: + name: Roya Ensafi + ins: R. Ensafi + author: + name: David Fifield + ins: D. Fifield + author: + name: Sarah McKune + ins: S. McKune + author: + name: Arn Rey + ins: A. Rey + author: + name: John Scott-Railton + ins: J. Scott-Railton + author: + name: Ronald Deibert + ins: R. Deibert + author: + name: Vern Paxson + ins: V. Paxson + date: 2015 + RFC1035: + RFC1918: + RFC1939: + RFC2015: + RFC2821: + RFC3261: + RFC3365: + RFC3501: + RFC3851: + RFC4033: + RFC4301: + RFC4303: + RFC4306: + RFC4949: + RFC5246: + RFC5321: + RFC5655: + RFC5750: + RFC6120: + RFC6962: + RFC6698: + RFC7011: + RFC7258: + I-D.ietf-dprive-problem-statement: + +--- abstract + +Documents published since initial revelations in 2013 have revealed +several classes of pervasive surveillance attack on Internet +communications. In this document we develop a threat model that +describes these pervasive attacks. We start by assuming an attacker +with an interest in undetected, indiscriminate eavesdropping, then +expand the threat model with a set of verified attacks that have been +published. + +--- middle + +# Introduction + +Starting in June 2013, documents released to the press by Edward +Snowden have revealed several operations undertaken by intelligence +agencies to exploit Internet communications for intelligence purposes. +These attacks were largely based on protocol vulnerabilities that were +already known to exist. The attacks were nonetheless striking in +their pervasive nature, both in terms of the amount of Internet +communications targeted, and in terms of the diversity of attack +techniques employed. + +To ensure that the Internet can be trusted by users, it is necessary +for the Internet technical community to address the vulnerabilities +exploited in these attacks {{RFC7258}}. The goal of this document is +to describe more precisely the threats posed by these pervasive +attacks, and based on those threats, lay out the problems that need to +be solved in order to secure the Internet in the face of those +threats. + +The remainder of this document is structured as follows. In +{{adversary}}, we describe an idealized passive pervasive attacker, one which +could completely undetectably compromise communications at Internet +scale. In {{reported}}, we provide a brief summary of some attacks +that have been disclosed, and use these to expand the assumed +capabilities of our idealized attacker. Note that we do not attempt +to describe all possible attacks, but focus on those which result in +undetected eavesdropping. {{model}} describes a threat model based on +these attacks, focusing on classes of attack that have not been a +focus of Internet engineering to date. + +# Terminology {#terminology} + +This document makes extensive use of standard security and privacy +terminology; see {{RFC4949}} and {{RFC6973}}. Terms used from +{{RFC6973}} include Eavesdropper, Observer, Initiator, Intermediary, +Recipient, Attack (in a privacy context), Correlation, Fingerprint, +Traffic Analysis, and Identifiability (and related terms). In +addition, we use a few terms that are specific to the attacks +discussed in this document. Note especially that "passive" and "active" below +do not refer to the effort used to mount the attack; a "passive attack" +is any attack that accesses a flow but does not modify it, while an +"active attack" is any attack that modifies a flow. Some passive attacks +involve active interception and modifications of devices, rather than simple +access to the medium. The introduced terms are: + +Pervasive Attack: +: An attack on Internet communications that makes +use of access at a large number of points in the network, or otherwise +provides the attacker with access to a large amount of Internet +traffic; see {{RFC7258}} + +Passive Pervasive Attack: +: An eavesdropping attack undertaken by a pervasive attacker, in which the +packets in a traffic stream between two endpoints are eavesdropped upon, but +in which the attacker does not modify the packets in the traffic +stream between two endpoints, modify the treatment of packets in the +traffic stream (e.g. delay, routing), or add or remove packets in the +traffic stream. Passive pervasive attacks are undetectable from the +endpoints. Equivalent to passive wiretapping as defined in {{RFC4949}}; +we use an alternate term here since the methods employed are wider +than those implied by the word "wiretapping", including the active +compromise of intermediate systems. + +Active Pervasive Attack: +: An attack undertaken by a pervasive attacker, which in addition to +the elements of a passive pervasive attack, also includes modification, +addition, or removal of +packets in a traffic stream, or modification of treatment of packets +in the traffic stream. Active pervasive attacks provide more +capabilities to the attacker at the cost of possible detection at the +endpoints. Equivalent to active wiretapping as defined in {{RFC4949}}. + +Observation: +: Information collected directly from communications by an +eavesdropper or observer. For example, the knowledge that +<alice@example.com> sent a message to <bob@example.com> +via SMTP taken from the headers of an observed SMTP message would be +an observation. + +Inference: +: Information extracted from analysis of information collected +directly from communications by an eavesdropper or observer. For +example, the knowledge that a given web page was accessed by a given +IP address, by comparing the size in octets of measured network flow +records to fingerprints derived from known sizes of linked resources +on the web servers involved, would be an inference. + +Collaborator: +: An entity that is a legitimate participant in a communication, but +who deliberately provides information about that interaction to an +attacker. + +Unwitting Collaborator: +: An entity that is a legitimate participant in a communication, and +who is the source of information obtained by the attacker without the +entity's consent or intention, because the attacker has exploited some +technology used by the entity. + +Key Exfiltration: +: The transmission of keying material for an encrypted communication +from a collaborator, deliberately or unwittingly, to an attacker + +Content Exfiltration: +: The transmission of the content of a communication from a collaborator, deliberately or unwittingly, to an attacker + +# An Idealized Passive Pervasive Attacker {#adversary} + +In considering the threat posed by pervasive surveillance, we begin by +defining an idealized passive pervasive attacker. While this attacker +is less capable than those which we now know to have compromised the +Internet from press reports, as elaborated in {{reported}}, it does +set a lower bound on the capabilities of an attacker interested in +indiscriminate passive surveillance while interested in remaining +undetectable. We note that, prior to the Snowden revelations in 2013, +the assumptions of attacker capability presented here would be +considered on the border of paranoia outside the network security +community. + +Our idealized attacker is an indiscriminate eavesdropper on an Internet-attached computer network that: + +- can observe every packet of all communications at any hop in any network path between an initiator and a recipient; +- can observe data at rest in any intermediate system between the endpoints controlled by the initiator and recipient; and +- can share information with other such attackers; but +- takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.). + +The techniques available to our ideal attacker are direct observation +and inference. Direct observation involves taking information directly +from eavesdropped communications - e.g., URLs identifying content or +email addresses identifying individuals from application-layer +headers. Inference, on the other hand, involves analyzing eavesdropped +information to derive new information from it; e.g., searching for +application or behavioral fingerprints in observed traffic to derive +information about the observed individual from them, in absence of +directly-observed sources of the same information. The use of +encryption to protect confidentiality is generally enough to prevent +direct observation of unencrypted content, assuming uncompromised +encryption implementations and key material. However, it provides less +complete protection against inference, especially inference based only +on unprotected portions of communications (e.g. IP and TCP headers for +TLS {{RFC5246}}). + +## Information subject to direct observation + +Protocols which do not encrypt their payload make the entire content +of the communication available to the idealized attacker along their +path. Following the advice in {{RFC3365}}, most such protocols have a +secure variant which encrypts payload for confidentiality, and these +secure variants are seeing ever-wider deployment. A noteworthy +exception is DNS {{RFC1035}}, as DNSSEC {{RFC4033}} does not have +confidentiality as a requirement. + +This implies that, in the absence of +changes to the protocol as presently under development in the IETF's +DNS Private Exchange (DPRIVE) +working group {{I-D.ietf-dprive-problem-statement}}, all DNS queries and answers generated by the activities +of any protocol are available to the attacker. + +Protocols which imply the storage of some data at rest in +intermediaries (e.g. SMTP {{RFC5321}}) leave this data subject to +observation by an attacker that has compromised these intermediaries, +unless the data is encrypted end-to-end by the application layer +protocol, or the implementation uses an encrypted store for this data. + +## Information useful for inference + +Inference is information extracted from later analysis of an observed +or eavesdropped communication, and/or correlation of observed or +eavesdropped information with information available from other +sources. Indeed, most useful inference performed by the attacker falls +under the rubric of correlation. The simplest example of this is the +observation of DNS queries and answers from and to a source and +correlating those with IP addresses with which that source +communicates. This can give access to information otherwise not +available from encrypted application payloads (e.g., the Host: +HTTP/1.1 request header when HTTP is used with TLS). + +Protocols which encrypt their payload using an application- or +transport-layer encryption scheme (e.g. TLS) still expose all the +information in their network and transport layer headers to the +attacker, including source and destination addresses and ports. IPsec +ESP{{RFC4303}} further encrypts the transport-layer headers, but still +leaves IP address information unencrypted; in tunnel mode, these +addresses correspond to the tunnel endpoints. Features of the +cryptographic protocols themselves, e.g. the TLS session identifier, +may leak information that can be used for correlation and +inference. While this information is much less semantically rich than +the application payload, it can still be useful for the inferring an +individual's activities. + +Inference can also leverage information obtained from sources other +than direct traffic observation. Geolocation databases, for example, +have been developed map IP addresses to a location, in order to +provide location-aware services such as targeted advertising. This +location information is often of sufficient resolution that it can be +used to draw further inferences toward identifying or profiling an +individual. + +Social media provide another source of more or less publicly +accessible information. This information can be extremely semantically +rich, including information about an individual's location, +associations with other individuals and groups, and +activities. Further, this information is generally contributed and +curated voluntarily by the individuals themselves: it represents +information which the individuals are not necessarily interested in +protecting for privacy reasons. However, correlation of this social +networking data with information available from direct observation of +network traffic allows the creation of a much richer picture of an +individual's activities than either alone. + +We note with some alarm that there is little that can be done at +protocol design time to limit such correlation by the attacker, and +that the existence of such data sources in many cases greatly +complicates the problem of protecting privacy by hardening protocols +alone. + +## An illustration of an ideal passive pervasive attack + +To illustrate how capable the idealized attacker is even given its +limitations, we explore the non-anonymity of encrypted IP traffic in +this section. Here we examine in detail some inference techniques for +associating a set of addresses with an individual, in order to +illustrate the difficulty of defending communications against our +idealized attacker. Here, the basic problem is that information +radiated even from protocols which have no obvious connection with +personal data can be correlated with other information which can paint +a very rich behavioral picture, that only takes one unprotected link +in the chain to associate with an identity. + +### Analysis of IP headers + +Internet traffic can be monitored by tapping Internet links, or by +installing monitoring tools in Internet routers. Of course, a single +link or a single router only provides access to a fraction of the +global Internet traffic. However, monitoring a number of high capacity +links or a set of routers placed at strategic locations provides +access to a good sampling of Internet traffic. + +Tools like IPFIX {{RFC7011}} allow administrators to acquire +statistics about sequences of packets with some common properties that +pass through a network device. The most common set of properties used +in flow measurement is the "five-tuple"of source and destination +addresses, protocol type, and source and destination ports. These +statistics are commonly used for network engineering, but could +certainly be used for other purposes. + +Let's assume for a moment that IP addresses can be correlated to +specific services or specific users. Analysis of the sequences of +packets will quickly reveal which users use what services, and also +which users engage in peer-to-peer connections with other +users. Analysis of traffic variations over time can be used to detect +increased activity by particular users, or in the case of peer-to-peer +connections increased activity within groups of users. + +### Correlation of IP addresses to user identities + +The correlation of IP addresses with specific users can be done in +various ways. For example, tools like reverse DNS lookup can be used +to retrieve the DNS names of servers. Since the addresses of servers +tend to be quite stable and since servers are relatively less numerous +than users, an attacker could easily maintain its own copy of the DNS +for well-known or popular servers, to accelerate such lookups. + +On the other hand, the reverse lookup of IP addresses of users is +generally less informative. For example, a lookup of the address +currently used by one author's home network returns a name of the form +"c-192-000-002-033.hsd1.wa.comcast.net". This particular type of +reverse DNS lookup generally reveals only coarse-grained location or +provider information, equivalent to that available from geolocation +databases. + +In many jurisdictions, Internet Service Providers (ISPs) are required +to provide identification on a case by case basis of the "owner" of a +specific IP address for law enforcement purposes. This is a reasonably +expedient process for targeted investigations, but pervasive +surveillance requires something more efficient. This provides an +incentive for the attacker to secure the cooperation of the ISP in +order to automate this correlation. + +### Monitoring messaging clients for IP address correlation + +Even if the ISP does not cooperate, user identity can often be +obtained via inference. POP3 {{RFC1939}} and IMAP {{RFC3501}} are used +to retrieve mail from mail servers, while a variant of SMTP is used to +submit messages through mail servers. IMAP connections originate from +the client, and typically start with an authentication exchange in +which the client proves its identity by answering a password +challenge. The same holds for the SIP protocol {{RFC3261}} and many +instant messaging services operating over the Internet using +proprietary protocols. + +The username is directly observable if any of these protocols operate +in cleartext; the username can then be directly associated with the +source address. + +### Retrieving IP addresses from mail headers + +SMTP {{RFC5321}} requires that each successive SMTP relay adds a +"Received" header to the mail headers. The purpose of these headers is +to enable audit of mail transmission, and perhaps to distinguish +between regular mail and spam. Here is an extract from the headers of +a message recently received from the "perpass" mailing list: + +``` + Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?) + (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA + (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100 + Message-ID: <526D7BD2.7070908@example.org> + Date: Sun, 27 Oct 2013 20:47:14 +0000 + From: Some One +``` + +This is the first "Received" header attached to the message by the +first SMTP relay; for privacy reasons, the field values have been +anonymized. We learn here that the message was submitted by "Some One" +on October 27, from a host behind a NAT (192.168.1.100) {{RFC1918}} +that used the IP address 192.0.2.44. The information remained in the +message, and is accessible by all recipients of the "perpass" mailing +list, or indeed by any attacker that sees at least one copy of the +message. + +An attacker that can observe sufficient email traffic can regularly +update the mapping between public IP addresses and individual email +identities. Even if the SMTP traffic was encrypted on submission and +relaying, the attacker can still receive a copy of public mailing +lists like "perpass". + +### Tracking address usage with web cookies + +Many web sites only encrypt a small fraction of their transactions. A +popular pattern is to use HTTPS for the login information, and then +use a "cookie" to associate following clear-text transactions with the +user's identity. Cookies are also used by various advertisement +services to quickly identify the users and serve them with +"personalized" advertisements. Such cookies are particularly useful if +the advertisement services want to keep tracking the user across +multiple sessions that may use different IP addresses. + +As cookies are sent in clear text, an attacker can build a database +that associates cookies to IP addresses for non-HTTPS traffic. If the +IP address is already identified, the cookie can be linked to the user +identify. After that, if the same cookie appears on a new IP address, +the new IP address can be immediately associated with the +pre-determined identity. + +### Graph-based approaches to address correlation + +An attacker can track traffic from an IP address not yet associated +with an individual to various public services (e.g. websites, mail +servers, game servers), and exploit patterns in the observed traffic +to correlate this address with other addresses that show similar +patterns. For example, any two addresses that show connections to the +same IMAP or webmail services, the same set of favorite websites, and +game servers at similar times of day may be associated with the same +individual. Correlated addresses can then be tied to an individual +through one of the techniques above, walking the "network graph" to +expand the set of attributable traffic. + +### Tracking of MAC Addresses + +Moving back down the stack, technologies like Ethernet or Wi-Fi use +MAC Addresses to identify link-level destinations. MAC Addresses +assigned according to IEEE-802 standards are unique to the device. If +the link is publicly accessible, an attacker can track it. For +example, the attacker can track the wireless traffic at public Wi-Fi +networks. Simple devices can monitor the traffic, and reveal which MAC +Addresses are present. If the network does not use some form of Wi-Fi +encryption, or if the attacker can access the decrypted traffic, the +analysis will also provide the correlation between MAC Addresses and +IP addresses. Additional monitoring using techniques exposed in the +previous sections will reveal the correlation between MAC Addresses, +IP Addresses, and user identity. + +Given that large-scale databases of the MAC addresses of wireless +access points for geolocation purposes have been known to exist for +some time, the attacker could easily build a database linking MAC +Addresses and device or user identities, and use it to track the +movement of devices and of their owners. + +# Reported Instances of Large-Scale Attacks {#reported} + +The situation in reality is more bleak than that suggested by an +analysis of our idealized attacker. Through revelations of sensitive +documents in several media outlets, the Internet community has been +made aware of several intelligence activities conducted by US and UK +national intelligence agencies, particularly the US National Security +Agency (NSA) and the UK Government Communications Headquarters +(GCHQ). These documents have revealed methods that these agencies use +to attack Internet applications and obtain sensitive user information. +We note that these reports are primarily useful as an illustration of +the types of capabilities fielded by pervasive attackers as of the +date of the Snowden leaks in 2013. + +First, they confirm the deployment of large-scale passive +collection of Internet traffic, which confirms the existence of +pervasive passive attackers with at least the capabilities of our +idealized attacker. For example {{pass1}}{{pass2}}{{pass3}}{{pass4}}: + +- NSA's XKEYSCORE system accesses data from multiple access points and +searches for "selectors" such as email addresses, at the scale of tens +of terabytes of data per day. + +- GCHQ's Tempora system appears to have access to around 1,500 major cables +passing through the UK. + +- NSA's MUSCULAR program has tapped cables between data centers +belonging to major service providers. + +- Several programs appear to perform wide-scale collection +of cookies in web traffic and location data from location-aware +portable devices such as smartphones. + +However, the capabilities described by these reports go beyond those of our +idealized attacker. They include the compromise of cryptographic protocols, +including decryption of TLS-protected Internet sessions {{dec1}}{{dec2}}{{dec3}}. +For example, the NSA BULLRUN project worked to undermine encryption through +multiple approaches, including covert modifications to cryptographic +software on end systems. + +They also include the direct compromise of intermediate systems +and arrangements with service providers for bulk data and metadata +access {{dir1}}{{dir2}}{{dir3}}, bypassing the need to capture +traffic on the wire. For example, the NSA PRISM program provides the +agency with access to many types of user data (e.g., email, chat, VoIP). + +The reported capabilities also include elements of active pervasive attack, +including: + +* Insertion of devices as a man-in-the-middle of Internet + transactions {{TOR1}}{{TOR2}}. For example, NSA's QUANTUM system + appears to use several different techniques to hijack HTTP + connections, ranging from DNS response injection to HTTP 302 + redirects. + +* Use of implants on end systems to undermine security and anonymity + features {{dec2}}{{TOR1}}{{TOR2}}. For example, QUANTUM is used to + direct users to a FOXACID server, which in turn delivers an implant + to compromise browsers of Tor users. + +* Use of implants on network elements from many major equipment providers, + including Cisco, Juniper, Huawei, Dell, and HP, as provided by the NSA's + Advanced Network Technology group. {{spiegel1}} + +* Use of botnet-scale collections of compromised hosts {{spiegel3}}. + +The scale of the compromise extends beyond the network to include subversion of the technical standards process itself. For example, there is suspicion that NSA modifications to the DUAL_EC_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA. This RNG was made part of NIST's SP 800-90A, for which NIST acknowledges NSA's assistance. There have also been reports that the NSA paid RSA Security for a related contract with the result that the curve became the default in the RSA BSAFE product line. + +We use the term "pervasive attack" {{RFC7258}} to collectively +describe these operations. The term "pervasive" is used because the +attacks are designed to indiscriminately gather as much data as +possible and to apply selective analysis on targets after the fact. +This means that all, or nearly all, Internet communications are +targets for these attacks. To achieve this scale, the attacks are +physically pervasive; they affect a large number of Internet +communications. They are pervasive in content, consuming and +exploiting any information revealed by the protocol. And they are +pervasive in technology, exploiting many different vulnerabilities in +many different protocols. + +It's important to note that although the attacks mentioned above were +executed by NSA and GCHQ, there are many other organizations that can +mount pervasive surveillance attacks. Because of the resources +required to achieve pervasive scale, these attacks are most commonly +undertaken by nation-state actors. For example, the Chinese Internet +filtering system known as the "Great Firewall of China" uses several +techniques that are similar to the QUANTUM program, and which have a +high degree of pervasiveness with regard to the Internet in China. + +# Threat Model {#model} + +Given these disclosures, we must consider a broader threat model. + +Pervasive surveillance aims to collect information across a large +number of Internet communications, analyzing the collected +communications to identify information of interest within individual +communications, or inferring information from correlated +communications. his analysis sometimes benefits from decryption of +encrypted communications and deanonymization of anonymized +communications. As a result, these attackers desire both access to +the bulk of Internet traffic and to the keying material required to +decrypt any traffic that has been encrypted. Even if keys are not +available, note that the presence of a communication and the fact that +it is encrypted may both be inputs to an analysis, even if the +attacker cannot decrypt the communication. + +The attacks listed above highlight new avenues both for access to +traffic and for access to relevant encryption keys. They further +indicate that the scale of surveillance is sufficient to provide a +general capability to cross-correlate communications, a threat not +previously thought to be relevant at the scale of the Internet. + +## Attacker Capabilities + +| Attack Class | Capability | +|:--------------------------|:------------------------------------------| +| Passive observation | Directly capture data in transit | +| Passive inference | Infer from reduced/encrypted data | +| Active | Manipulate / inject data in transit | +| Static key exfiltration | Obtain key material once / rarely | +| Dynamic key exfiltration | Obtain per-session key material | +| Content exfiltration | Access data at rest | + +Security analyses of Internet protocols commonly consider two classes +of attacker: Passive pervasive attackers, who can simply listen in on +communications as they transit the network, and active pervasive +attackers, who can modify or delete packets in addition to simply +collecting them. + +In the context of pervasive passive surveillance, these attacks take +on an even greater significance. In the past, these attackers were +often assumed to operate near the edge of the network, where attacks +can be simpler. For example, in some LANs, it is simple for any node +to engage in passive listening to other nodes' traffic or inject +packets to accomplish active pervasive attacks. However, as we now +know, both passive and active pervasive attacks are undertaken by +pervasive attackers closer to the core of the network, greatly +expanding the scope and capability of the attacker. + +Eavesdropping and observation at a larger scale make passive inference +attacks easier to carry out: a passive pervasive attacker with access to a +large portion of the Internet can analyze collected traffic to create +a much more detailed view of individual behavior than an attacker that +collects at a single point. Even the usual claim that encryption +defeats passive pervasive attackers is weakened, since a pervasive flow +access attacker can infer relationships from correlations over large +numbers of sessions, e.g., pairing encrypted sessions with unencrypted +sessions from the same host, or performing traffic fingerprinting +between known and unknown encrypted sessions. Reports on the NSA +XKEYSCORE system would indicate it is an example of such an attacker. + +An active pervasive attacker likewise has capabilities +beyond those of a localized active attacker. flow +modification attacks are often limited by network topology, for +example by a requirement that the attacker be able to see a targeted +session as well as inject packets into it. A pervasive flow +modification attacker with access at multiple points within the core +of the Internet is able to overcome these topological limitations and +perform attacks over a much broader scope. Being positioned in the +core of the network rather than the edge can also enable an active +pervasive attacker to reroute targeted traffic, amplifying the +ability to perform both eavesdropping and traffic injection. +Active pervasive attackers can also benefit from passive pervasive +collection to identify vulnerable hosts. + +While not directly related to pervasiveness, attackers that are in a +position to mount a active pervasive attack are also often +in a position to subvert authentication, a traditional protection +against such attacks. Authentication in the Internet is often +achieved via trusted third party authorities such as the Certificate +Authorities (CAs) that provide web sites with authentication +credentials. An attacker with sufficient resources may also be able to +induce an authority to grant credentials for an identity of the +attacker’s choosing. If the parties to a communication will trust +multiple authorities to certify a specific identity, this attack may +be mounted by suborning any one of the authorities (the proverbial +"weakest link"). Subversion of authorities in this way can allow an +active attack to succeed in spite of an authentication +check. + +Beyond these three classes (observation, inference, and active), +reports on the BULLRUN effort to defeat encryption and the PRISM +effort to obtain data from service providers suggest three more +classes of attack: + +* Static key exfiltration +* Dynamic key exfiltration +* Content exfiltration + +These attacks all rely on a collaborator providing the attacker with +some information, either keys or data. These attacks have not +traditionally been considered in scope for the Security Considerations +sections of IETF protocols, as they occur outside the protocol. + +The term "key exfiltration" refers to the transfer of keying material +for an encrypted communication from the collaborator to the attacker. +By "static", we mean that the transfer of keys happens once, or +rarely, typically of a long-lived key. For example, this case would +cover a web site operator that provides the private key corresponding +to its HTTPS certificate to an intelligence agency. + +"Dynamic" key exfiltration, by contrast, refers to attacks in which +the collaborator delivers keying material to the attacker frequently, +e.g., on a per-session basis. This does not necessarily imply +frequent communications with the attacker; the transfer of keying +material may be virtual. For example, if an endpoint were modified in +such a way that the attacker could predict the state of its +psuedorandom number generator, then the attacker would be able to +derive per-session keys even without per-session communications. + +Finally, content exfiltration is the attack in which the collaborator +simply provides the attacker with the desired data or metadata. Unlike +the key exfiltration cases, this attack does not require the attacker +to capture the desired data as it flows through the network. The risk +is to data at rest as opposed to data in transit. This increases the +scope of data that the attacker can obtain, since the attacker can +access historical data -- the attacker does not have to be listening +at the time the communication happens. + +Exfiltration attacks can be accomplished via attacks against one of +the parties to a communication, i.e., by the attacker stealing the +keys or content rather than the party providing them willingly. In +these cases, the party may not be aware that they are collaborating, +at least at a human level. Rather, the subverted technical assets are +"collaborating" with the attacker (by providing keys/content) without +their owner's knowledge or consent. + +Any party that has access to encryption keys or unencrypted data can +be a collaborator. While collaborators are typically the endpoints of +a communication (with encryption securing the links), intermediaries +in an unencrypted communication can also facilitate content +exfiltration attacks as collaborators by providing the attacker access +to those communications. For example, documents describing the NSA +PRISM program claim that NSA is able to access user data directly from +servers, where it is stored unencrypted. In these cases, the operator +of the server would be a collaborator, if an unwitting one. By +contrast, in the NSA MUSCULAR program, a set of collaborators enabled +attackers to access the cables connecting data centers used by service +providers such as Google and Yahoo. Because communications among +these data centers were not encrypted, the collaboration by an +intermediate entity allowed NSA to collect unencrypted user data. + +## Attacker Costs + +| Attack Class | Cost / Risk to Attacker | +|:--------------------------|:----------------------------------| +| Passive observation | Passive data access | +| Passive inference | Passive data access + processing | +| Active | Active data access + processing | +| Static key exfiltration | One-time interaction | +| Dynamic key exfiltration | Ongoing interaction / code change | +| Content exfiltration | Ongoing, bulk interaction | + +Each of the attack types discussed in the previous section entails +certain costs and risks. These costs differ by attack, and can be +helpful in guiding response to pervasive attack. + +Depending on the attack, the attacker may be exposed to several types +of risk, ranging from simply losing access to arrest or prosecution. +In order for any of these negative consequences to occur, however, the +attacker must first be discovered and identified. So the primary risk +we focus on here is the risk of discovery and attribution. + +A passive pervasive attack is the simplest to mount in some ways. The base +requirement is that the attacker obtain physical access to a +communications medium and extract communications from it. For +example, the attacker might tap a fiber-optic cable, acquire a mirror +port on a switch, or listen to a wireless signal. The need for these +taps to have physical access or proximity to a link exposes the +attacker to the risk that the taps will be discovered. For example, a +fiber tap or mirror port might be discovered by network operators +noticing increased attenuation in the fiber or a change in switch +configuration. Of course, passive pervasive attacks may be accomplished +with the cooperation of the network operator, in which case there is a +risk that the attacker's interactions with the network operator will +be exposed. + +In many ways, the costs and risks for an active pervasive attack are +similar to those for a passive pervasive attack, with a few additions. An +active attacker requires more robust network access than a +passive attacker, since for example they will often need to +transmit data as well as receiving it. In the wireless example above, +the attacker would need to act as an transmitter as well as receiver, +greatly increasing the probability the attacker will be discovered +(e.g., using direction-finding technology). Active attacks +are also much more observable at higher layers of the network. For +example, an active attacker that attempts to use a +mis-issued certificate could be detected via Certificate Transparency +{{RFC6962}}. + +In terms of raw implementation complexity, passive pervasive attacks require +only enough processing to extract information from the network and +store it. Active pervasive attacks, by contrast, often depend on +winning race conditions to inject pakets into active connections. So +active pervasive attacks in the core of the network require +processing hardware to that can operate at line speed (roughly 100Gbps +to 1Tbps in the core) to identify opportunities for attack and insert +attack traffic in a high-volume traffic. Key exfiltration attacks +rely on passive pervasive attack for access to encrypted data, with the +collaborator providing keys to decrypt the data. So the attacker +undertakes the cost and risk of a passive pervasive attack, as well as +additional risk of discovery via the interactions that the attacker +has with the collaborator. + +Some active attacks are more expensive than others. For example, +active man-in-the-middle (MITM) attacks require access to the entire +network session and path in order to intercept and potentially modify, +as well as drop, legitimate packets in favor of the attacker's +packets. A similar but weaker form of attack, called an active +man-on-the-side (MOTS), does not require access to the entire session +and only part of the path. In an active MOTS attack, the attacker need +only be able to inject or modify traffic on the network element the +attacker has access to. While this may not allow for full control of a +communication session (as in an MITM attack), the attacker can perform +a number of powerful attacks, including but not limited to: injecting +packets that could terminate the session (e.g., TCP RST packets), +sending a fake DNS reply to redirect ensuing TCP connections to an +address of the attacker's choice (i.e., winning a "DNS response +race"), and mounting an HTTP Redirect attack by observing a TCP/HTTP +connection to a target address and injecting a TCP data packet +containing an HTTP redirect. For example, the system dubbed by +researchers as China's "Great Cannon" {{great-cannon}} can operate in +ful MITM mode to accomplish very complex attacks that can modify +content in transit while the well-known Great Firewall of China is a +MOTS system that focuses on blocking access to certain kinds of +traffic and destinations via TCP RST packet injection. + +In this sense, static exfiltration has a lower risk profile than +dynamic. In the static case, the attacker need only interact with the +collaborator a small number of times, possibly only once, say to +exchange a private key. In the dynamic case, the attacker must have +continuing interactions with the collaborator. As noted above these +interactions may be real, such as in-person meetings, or virtual, such as +software modifications that render keys available to the attacker. +Both of these types of interactions introduce a risk that they will be +discovered, e.g., by employees of the collaborator organization +noticing suspicious meetings or suspicious code changes. + +Content exfiltration has a similar risk profile to dynamic key +exfiltration. In a content exfiltration attack, the attacker saves +the cost and risk of conducting a passive pervasive attack. The risk of +discovery through interactions with the collaborator, however, is +still present, and may be higher. The content of a communication is +obviously larger than the key used to encrypt it, often by several +orders of magnitude. So in the content exfiltration case, the +interactions between the collaborator and the attacker need to be much +higher-bandwidth than in the key exfiltration cases, with a +corresponding increase in the risk that this high-bandwidth channel +will be discovered. + +It should also be noted that in these latter three exfiltration cases, +the collaborator also undertakes a risk that his collaboration with +the attacker will be discovered. Thus the attacker may have to incur +additional cost in order to convince the collaborator to participate +in the attack. Likewise, the scope of these attacks is limited to +case where the attacker can convince a collaborator to participate. +If the attacker is a national government, for example, it may be able +to compel participation within its borders, but have a much more +difficult time recruiting foreign collaborators. + +As noted above, the collaborator in an exfiltration attack can be +unwitting; the attacker can steal keys or data to enable the attack. +In some ways, the risks of this approach are similar to the case of an +active collaborator. In the static case, the attacker needs to steal +information from the collaborator once; in the dynamic case, the +attacker needs to continued presence inside the collaborators systems. +The main difference is that the risk in this case is of automated +discovery (e.g., by intrusion detection systems) rather than discovery +by humans. + +# Security Considerations + +This document describes a threat model for pervasive surveillance +attacks. Mitigations are to be given in a future document. + +# IANA Considerations + +This document has no actions for IANA. + +# Acknowledgements + +Thanks to Dave Thaler for the list of attacks and taxonomy; to +Security Area Directors Stephen Farrell, Sean Turner, and Kathleen +Moriarty for starting and managing the IETF's discussion on pervasive +attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, Evangelos +Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, Russ Housley, and the IAB +Privacy and Security Program for their input. diff --git a/draft-iab-privsec-confidentiality-threat-04.pdf b/draft-iab-privsec-confidentiality-threat-04.pdf new file mode 100644 index 0000000..285bde3 Binary files /dev/null and b/draft-iab-privsec-confidentiality-threat-04.pdf differ diff --git a/draft-iab-privsec-confidentiality-threat-04.txt b/draft-iab-privsec-confidentiality-threat-04.txt new file mode 100644 index 0000000..d8104a2 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-04.txt @@ -0,0 +1,1288 @@ + + + + +Network Working Group R. Barnes +Internet-Draft +Intended status: Informational B. Schneier +Expires: September 12, 2015 + C. Jennings + + T. Hardie + + B. Trammell + + C. Huitema + + D. Borkmann + + March 11, 2015 + + + Confidentiality in the Face of Pervasive Surveillance: A Threat Model + and Problem Statement + draft-iab-privsec-confidentiality-threat-04 + +Abstract + + Documents published since initial revelations in 2013 have revealed + several classes of pervasive surveillance attack on Internet + communications. In this document we develop a threat model that + describes these pervasive attacks. We start by assuming an attacker + with an interest in undetected, indiscriminate eavesdropping, then + expand the threat model with a set of verified attacks that have been + published. + +Status of This Memo + + This Internet-Draft is submitted in full conformance with the + provisions of BCP 78 and BCP 79. + + Internet-Drafts are working documents of the Internet Engineering + Task Force (IETF). Note that other groups may also distribute + working documents as Internet-Drafts. The list of current Internet- + Drafts is at http://datatracker.ietf.org/drafts/current/. + + Internet-Drafts are draft documents valid for a maximum of six months + and may be updated, replaced, or obsoleted by other documents at any + time. It is inappropriate to use Internet-Drafts as reference + material or to cite them other than as "work in progress." + + This Internet-Draft will expire on September 12, 2015. + + + + +Barnes, et al. Expires September 12, 2015 [Page 1] + +Internet-Draft Confidentiality Threat Model March 2015 + + +Copyright Notice + + Copyright (c) 2015 IETF Trust and the persons identified as the + document authors. All rights reserved. + + This document is subject to BCP 78 and the IETF Trust's Legal + Provisions Relating to IETF Documents + (http://trustee.ietf.org/license-info) in effect on the date of + publication of this document. Please review these documents + carefully, as they describe your rights and restrictions with respect + to this document. Code Components extracted from this document must + include Simplified BSD License text as described in Section 4.e of + the Trust Legal Provisions and are provided without warranty as + described in the Simplified BSD License. + +1. Introduction + + Starting in June 2013, documents released to the press by Edward + Snowden have revealed several operations undertaken by intelligence + agencies to exploit Internet communications for intelligence + purposes. These attacks were largely based on protocol + vulnerabilities that were already known to exist. The attacks were + nonetheless striking in their pervasive nature, both in terms of the + amount of Internet communications targeted, and in terms of the + diversity of attack techniques employed. + + To ensure that the Internet can be trusted by users, it is necessary + for the Internet technical community to address the vulnerabilities + exploited in these attacks [RFC7258]. The goal of this document is + to describe more precisely the threats posed by these pervasive + attacks, and based on those threats, lay out the problems that need + to be solved in order to secure the Internet in the face of those + threats. + + The remainder of this document is structured as follows. In + Section 3, we describe an idealized passive pervasive attacker, one + which could completely undetectably compromise communications at + Internet scale. In Section 4, we provide a brief summary of some + attacks that have been disclosed, and use these to expand the assumed + capabilities of our idealized attacker. Note that we do not attempt + to describe all possible attacks, but focus on those which result in + undetected eavesdropping. Section 5 describes a threat model based + on these attacks, focusing on classes of attack that have not been a + focus of Internet engineering to date. + + + + + + + +Barnes, et al. Expires September 12, 2015 [Page 2] + +Internet-Draft Confidentiality Threat Model March 2015 + + +2. Terminology + + This document makes extensive use of standard security and privacy + terminology; see [RFC4949] and [RFC6973]. Terms used from [RFC6973] + include Eavesdropper, Observer, Initiator, Intermediary, Recipient, + Attack (in a privacy context), Correlation, Fingerprint, Traffic + Analysis, and Identifiability (and related terms). In addition, we + use a few terms that are specific to the attacks discussed in this + document. Note especially that "passive" and "active" below do not + refer to the effort used to mount the attack; a "passive attack" is + any attack that accesses a flow but does not modify it, while an + "active attack" is any attack that modifies a flow. Some passive + attacks involve active interception and modifications of devices, + rather than simple access to the medium. The introduced terms are: + + Pervasive Attack: An attack on Internet communications that makes + use of access at a large number of points in the network, or + otherwise provides the attacker with access to a large amount of + Internet traffic; see [RFC7258] + + Passive Pervasive Attack: An eavesdropping attack undertaken by a + pervasive attacker, in which the packets in a traffic stream + between two endpoints are eavesdropped upon, but in which the + attacker does not modify the packets in the traffic stream between + two endpoints, modify the treatment of packets in the traffic + stream (e.g. delay, routing), or add or remove packets in the + traffic stream. Passive pervasive attacks are undetectable from + the endpoints. Equivalent to passive wiretapping as defined in + [RFC4949]; we use an alternate term here since the methods + employed are wider than those implied by the word "wiretapping", + including the active compromise of intermediate systems. + + Active Pervasive Attack: An attack undertaken by a pervasive + attacker, which in addition to the elements of a passive pervasive + attack, also includes modification, addition, or removal of + packets in a traffic stream, or modification of treatment of + packets in the traffic stream. Active pervasive attacks provide + more capabilities to the attacker at the cost of possible + detection at the endpoints. Equivalent to active wiretapping as + defined in [RFC4949]. + + Observation: Information collected directly from communications by + an eavesdropper or observer. For example, the knowledge that + sent a message to via SMTP + taken from the headers of an observed SMTP message would be an + observation. + + + + + +Barnes, et al. Expires September 12, 2015 [Page 3] + +Internet-Draft Confidentiality Threat Model March 2015 + + + Inference: Information extracted from analysis of information + collected directly from communications by an eavesdropper or + observer. For example, the knowledge that a given web page was + accessed by a given IP address, by comparing the size in octets of + measured network flow records to fingerprints derived from known + sizes of linked resources on the web servers involved, would be an + inference. + + Collaborator: An entity that is a legitimate participant in a + communication, but who deliberately provides information about + that interaction to an attacker. + + Unwitting Collaborator: An entity that is a legitimate participant + in a communication, and who is the source of information obtained + by the attacker without the entity's consent or intention, because + the attacker has exploited some technology used by the entity. + + Key Exfiltration: The transmission of keying material for an + encrypted communication from a collaborator, deliberately or + unwittingly, to an attacker + + Content Exfiltration: The transmission of the content of a + communication from a collaborator, deliberately or unwittingly, to + an attacker + +3. An Idealized Passive Pervasive Attacker + + In considering the threat posed by pervasive surveillance, we begin + by defining an idealized passive pervasive attacker. While this + attacker is less capable than those which we now know to have + compromised the Internet from press reports, as elaborated in + Section 4, it does set a lower bound on the capabilities of an + attacker interested in indiscriminate passive surveillance while + interested in remaining undetectable. We note that, prior to the + Snowden revelations in 2013, the assumptions of attacker capability + presented here would be considered on the border of paranoia outside + the network security community. + + Our idealized attacker is an indiscriminate eavesdropper on an + Internet-attached computer network that: + + o can observe every packet of all communications at any hop in any + network path between an initiator and a recipient; + + o can observe data at rest in any intermediate system between the + endpoints controlled by the initiator and recipient; and + + o can share information with other such attackers; but + + + +Barnes, et al. Expires September 12, 2015 [Page 4] + +Internet-Draft Confidentiality Threat Model March 2015 + + + o takes no other action with respect to these communications (i.e., + blocking, modification, injection, etc.). + + The techniques available to our ideal attacker are direct observation + and inference. Direct observation involves taking information + directly from eavesdropped communications - e.g., URLs identifying + content or email addresses identifying individuals from application- + layer headers. Inference, on the other hand, involves analyzing + eavesdropped information to derive new information from it; e.g., + searching for application or behavioral fingerprints in observed + traffic to derive information about the observed individual from + them, in absence of directly-observed sources of the same + information. The use of encryption to protect confidentiality is + generally enough to prevent direct observation of unencrypted + content, assuming uncompromised encryption implementations and key + material. However, it provides less complete protection against + inference, especially inference based only on unprotected portions of + communications (e.g. IP and TCP headers for TLS [RFC5246]). + +3.1. Information subject to direct observation + + Protocols which do not encrypt their payload make the entire content + of the communication available to the idealized attacker along their + path. Following the advice in [RFC3365], most such protocols have a + secure variant which encrypts payload for confidentiality, and these + secure variants are seeing ever-wider deployment. A noteworthy + exception is DNS [RFC1035], as DNSSEC [RFC4033] does not have + confidentiality as a requirement. + + This implies that, in the absence of changes to the protocol as + presently under development in the IETF's DNS Private Exchange + (DPRIVE) working group [I-D.ietf-dprive-problem-statement], all DNS + queries and answers generated by the activities of any protocol are + available to the attacker. + + Protocols which imply the storage of some data at rest in + intermediaries (e.g. SMTP [RFC5321]) leave this data subject to + observation by an attacker that has compromised these intermediaries, + unless the data is encrypted end-to-end by the application layer + protocol, or the implementation uses an encrypted store for this + data. + +3.2. Information useful for inference + + Inference is information extracted from later analysis of an observed + or eavesdropped communication, and/or correlation of observed or + eavesdropped information with information available from other + sources. Indeed, most useful inference performed by the attacker + + + +Barnes, et al. Expires September 12, 2015 [Page 5] + +Internet-Draft Confidentiality Threat Model March 2015 + + + falls under the rubric of correlation. The simplest example of this + is the observation of DNS queries and answers from and to a source + and correlating those with IP addresses with which that source + communicates. This can give access to information otherwise not + available from encrypted application payloads (e.g., the Host: + HTTP/1.1 request header when HTTP is used with TLS). + + Protocols which encrypt their payload using an application- or + transport-layer encryption scheme (e.g. TLS) still expose all the + information in their network and transport layer headers to the + attacker, including source and destination addresses and ports. + IPsec ESP[RFC4303] further encrypts the transport-layer headers, but + still leaves IP address information unencrypted; in tunnel mode, + these addresses correspond to the tunnel endpoints. Features of the + cryptographic protocols themselves, e.g. the TLS session identifier, + may leak information that can be used for correlation and inference. + While this information is much less semantically rich than the + application payload, it can still be useful for the inferring an + individual's activities. + + Inference can also leverage information obtained from sources other + than direct traffic observation. Geolocation databases, for example, + have been developed map IP addresses to a location, in order to + provide location-aware services such as targeted advertising. This + location information is often of sufficient resolution that it can be + used to draw further inferences toward identifying or profiling an + individual. + + Social media provide another source of more or less publicly + accessible information. This information can be extremely + semantically rich, including information about an individual's + location, associations with other individuals and groups, and + activities. Further, this information is generally contributed and + curated voluntarily by the individuals themselves: it represents + information which the individuals are not necessarily interested in + protecting for privacy reasons. However, correlation of this social + networking data with information available from direct observation of + network traffic allows the creation of a much richer picture of an + individual's activities than either alone. + + We note with some alarm that there is little that can be done at + protocol design time to limit such correlation by the attacker, and + that the existence of such data sources in many cases greatly + complicates the problem of protecting privacy by hardening protocols + alone. + + + + + + +Barnes, et al. Expires September 12, 2015 [Page 6] + +Internet-Draft Confidentiality Threat Model March 2015 + + +3.3. An illustration of an ideal passive pervasive attack + + To illustrate how capable the idealized attacker is even given its + limitations, we explore the non-anonymity of encrypted IP traffic in + this section. Here we examine in detail some inference techniques + for associating a set of addresses with an individual, in order to + illustrate the difficulty of defending communications against our + idealized attacker. Here, the basic problem is that information + radiated even from protocols which have no obvious connection with + personal data can be correlated with other information which can + paint a very rich behavioral picture, that only takes one unprotected + link in the chain to associate with an identity. + +3.3.1. Analysis of IP headers + + Internet traffic can be monitored by tapping Internet links, or by + installing monitoring tools in Internet routers. Of course, a single + link or a single router only provides access to a fraction of the + global Internet traffic. However, monitoring a number of high + capacity links or a set of routers placed at strategic locations + provides access to a good sampling of Internet traffic. + + Tools like IPFIX [RFC7011] allow administrators to acquire statistics + about sequences of packets with some common properties that pass + through a network device. The most common set of properties used in + flow measurement is the "five-tuple"of source and destination + addresses, protocol type, and source and destination ports. These + statistics are commonly used for network engineering, but could + certainly be used for other purposes. + + Let's assume for a moment that IP addresses can be correlated to + specific services or specific users. Analysis of the sequences of + packets will quickly reveal which users use what services, and also + which users engage in peer-to-peer connections with other users. + Analysis of traffic variations over time can be used to detect + increased activity by particular users, or in the case of peer-to- + peer connections increased activity within groups of users. + +3.3.2. Correlation of IP addresses to user identities + + The correlation of IP addresses with specific users can be done in + various ways. For example, tools like reverse DNS lookup can be used + to retrieve the DNS names of servers. Since the addresses of servers + tend to be quite stable and since servers are relatively less + numerous than users, an attacker could easily maintain its own copy + of the DNS for well-known or popular servers, to accelerate such + lookups. + + + + +Barnes, et al. Expires September 12, 2015 [Page 7] + +Internet-Draft Confidentiality Threat Model March 2015 + + + On the other hand, the reverse lookup of IP addresses of users is + generally less informative. For example, a lookup of the address + currently used by one author's home network returns a name of the + form "c-192-000-002-033.hsd1.wa.comcast.net". This particular type + of reverse DNS lookup generally reveals only coarse-grained location + or provider information, equivalent to that available from + geolocation databases. + + In many jurisdictions, Internet Service Providers (ISPs) are required + to provide identification on a case by case basis of the "owner" of a + specific IP address for law enforcement purposes. This is a + reasonably expedient process for targeted investigations, but + pervasive surveillance requires something more efficient. This + provides an incentive for the attacker to secure the cooperation of + the ISP in order to automate this correlation. + +3.3.3. Monitoring messaging clients for IP address correlation + + Even if the ISP does not cooperate, user identity can often be + obtained via inference. POP3 [RFC1939] and IMAP [RFC3501] are used + to retrieve mail from mail servers, while a variant of SMTP is used + to submit messages through mail servers. IMAP connections originate + from the client, and typically start with an authentication exchange + in which the client proves its identity by answering a password + challenge. The same holds for the SIP protocol [RFC3261] and many + instant messaging services operating over the Internet using + proprietary protocols. + + The username is directly observable if any of these protocols operate + in cleartext; the username can then be directly associated with the + source address. + +3.3.4. Retrieving IP addresses from mail headers + + SMTP [RFC5321] requires that each successive SMTP relay adds a + "Received" header to the mail headers. The purpose of these headers + is to enable audit of mail transmission, and perhaps to distinguish + between regular mail and spam. Here is an extract from the headers + of a message recently received from the "perpass" mailing list: + + "Received: from 192-000-002-044.zone13.example.org (HELO + ?192.168.1.100?) (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net + with ESMTPSA (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct + 2013 21:47:14 +0100 Message-ID: <526D7BD2.7070908@example.org> Date: + Sun, 27 Oct 2013 20:47:14 +0000 From: Some One + " + + + + + +Barnes, et al. Expires September 12, 2015 [Page 8] + +Internet-Draft Confidentiality Threat Model March 2015 + + + This is the first "Received" header attached to the message by the + first SMTP relay; for privacy reasons, the field values have been + anonymized. We learn here that the message was submitted by "Some + One" on October 27, from a host behind a NAT (192.168.1.100) + [RFC1918] that used the IP address 192.0.2.44. The information + remained in the message, and is accessible by all recipients of the + "perpass" mailing list, or indeed by any attacker that sees at least + one copy of the message. + + An attacker that can observe sufficient email traffic can regularly + update the mapping between public IP addresses and individual email + identities. Even if the SMTP traffic was encrypted on submission and + relaying, the attacker can still receive a copy of public mailing + lists like "perpass". + +3.3.5. Tracking address usage with web cookies + + Many web sites only encrypt a small fraction of their transactions. + A popular pattern is to use HTTPS for the login information, and then + use a "cookie" to associate following clear-text transactions with + the user's identity. Cookies are also used by various advertisement + services to quickly identify the users and serve them with + "personalized" advertisements. Such cookies are particularly useful + if the advertisement services want to keep tracking the user across + multiple sessions that may use different IP addresses. + + As cookies are sent in clear text, an attacker can build a database + that associates cookies to IP addresses for non-HTTPS traffic. If + the IP address is already identified, the cookie can be linked to the + user identify. After that, if the same cookie appears on a new IP + address, the new IP address can be immediately associated with the + pre-determined identity. + +3.3.6. Graph-based approaches to address correlation + + An attacker can track traffic from an IP address not yet associated + with an individual to various public services (e.g. websites, mail + servers, game servers), and exploit patterns in the observed traffic + to correlate this address with other addresses that show similar + patterns. For example, any two addresses that show connections to + the same IMAP or webmail services, the same set of favorite websites, + and game servers at similar times of day may be associated with the + same individual. Correlated addresses can then be tied to an + individual through one of the techniques above, walking the "network + graph" to expand the set of attributable traffic. + + + + + + +Barnes, et al. Expires September 12, 2015 [Page 9] + +Internet-Draft Confidentiality Threat Model March 2015 + + +3.3.7. Tracking of MAC Addresses + + Moving back down the stack, technologies like Ethernet or Wi-Fi use + MAC Addresses to identify link-level destinations. MAC Addresses + assigned according to IEEE-802 standards are unique to the device. + If the link is publicly accessible, an attacker can track it. For + example, the attacker can track the wireless traffic at public Wi-Fi + networks. Simple devices can monitor the traffic, and reveal which + MAC Addresses are present. If the network does not use some form of + Wi-Fi encryption, or if the attacker can access the decrypted + traffic, the analysis will also provide the correlation between MAC + Addresses and IP addresses. Additional monitoring using techniques + exposed in the previous sections will reveal the correlation between + MAC Addresses, IP Addresses, and user identity. + + Given that large-scale databases of the MAC addresses of wireless + access points for geolocation purposes have been known to exist for + some time, the attacker could easily build a database linking MAC + Addresses and device or user identities, and use it to track the + movement of devices and of their owners. + +4. Reported Instances of Large-Scale Attacks + + The situation in reality is more bleak than that suggested by an + analysis of our idealized attacker. Through revelations of sensitive + documents in several media outlets, the Internet community has been + made aware of several intelligence activities conducted by US and UK + national intelligence agencies, particularly the US National Security + Agency (NSA) and the UK Government Communications Headquarters + (GCHQ). These documents have revealed methods that these agencies + use to attack Internet applications and obtain sensitive user + information. We note that these reports are primarily useful as an + illustration of the types of capabilities fielded by pervasive + attackers as of the date of the Snowden leaks in 2013. + + First, they confirm the deployment of large-scale passive collection + of Internet traffic, which confirms the existence of pervasive + passive attackers with at least the capabilities of our idealized + attacker. For example [pass1][pass2][pass3][pass4]: + + o NSA's XKEYSCORE system accesses data from multiple access points + and searches for "selectors" such as email addresses, at the scale + of tens of terabytes of data per day. + + o GCHQ's Tempora system appears to have access to around 1,500 major + cables passing through the UK. + + + + + +Barnes, et al. Expires September 12, 2015 [Page 10] + +Internet-Draft Confidentiality Threat Model March 2015 + + + o NSA's MUSCULAR program has tapped cables between data centers + belonging to major service providers. + + o Several programs appear to perform wide-scale collection of + cookies in web traffic and location data from location-aware + portable devices such as smartphones. + + However, the capabilities described by these reports go beyond those + of our idealized attacker. They include the compromise of + cryptographic protocols, including decryption of TLS-protected + Internet sessions [dec1][dec2][dec3]. For example, the NSA BULLRUN + project worked to undermine encryption through multiple approaches, + including covert modifications to cryptographic software on end + systems. + + They also include the direct compromise of intermediate systems and + arrangements with service providers for bulk data and metadata access + [dir1][dir2][dir3], bypassing the need to capture traffic on the + wire. For example, the NSA PRISM program provides the agency with + access to many types of user data (e.g., email, chat, VoIP). + + The reported capabilities also include elements of active pervasive + attack, including: + + o Insertion of devices as a man-in-the-middle of Internet + transactions [TOR1][TOR2]. For example, NSA's QUANTUM system + appears to use several different techniques to hijack HTTP + connections, ranging from DNS response injection to HTTP 302 + redirects. + + o Use of implants on end systems to undermine security and anonymity + features [dec2][TOR1][TOR2]. For example, QUANTUM is used to + direct users to a FOXACID server, which in turn delivers an + implant to compromise browsers of Tor users. + + o Use of implants on network elements from many major equipment + providers, including Cisco, Juniper, Huawei, Dell, and HP, as + provided by the NSA's Advanced Network Technology group. + [spiegel1] + + o Use of botnet-scale collections of compromised hosts [spiegel3]. + + The scale of the compromise extends beyond the network to include + subversion of the technical standards process itself. For example, + there is suspicion that NSA modifications to the DUAL_EC_DRBG random + number generator were made to ensure that keys generated using that + generator could be predicted by NSA. This RNG was made part of + NIST's SP 800-90A, for which NIST acknowledges NSA's assistance. + + + +Barnes, et al. Expires September 12, 2015 [Page 11] + +Internet-Draft Confidentiality Threat Model March 2015 + + + There have also been reports that the NSA paid RSA Security for a + related contract with the result that the curve became the default in + the RSA BSAFE product line. + + We use the term "pervasive attack" [RFC7258] to collectively describe + these operations. The term "pervasive" is used because the attacks + are designed to indiscriminately gather as much data as possible and + to apply selective analysis on targets after the fact. This means + that all, or nearly all, Internet communications are targets for + these attacks. To achieve this scale, the attacks are physically + pervasive; they affect a large number of Internet communications. + They are pervasive in content, consuming and exploiting any + information revealed by the protocol. And they are pervasive in + technology, exploiting many different vulnerabilities in many + different protocols. + + It's important to note that although the attacks mentioned above were + executed by NSA and GCHQ, there are many other organizations that can + mount pervasive surveillance attacks. Because of the resources + required to achieve pervasive scale, these attacks are most commonly + undertaken by nation-state actors. For example, the Chinese Internet + filtering system known as the "Great Firewall of China" uses several + techniques that are similar to the QUANTUM program, and which have a + high degree of pervasiveness with regard to the Internet in China. + +5. Threat Model + + Given these disclosures, we must consider a broader threat model. + + Pervasive surveillance aims to collect information across a large + number of Internet communications, analyzing the collected + communications to identify information of interest within individual + communications, or inferring information from correlated + communications. his analysis sometimes benefits from decryption of + encrypted communications and deanonymization of anonymized + communications. As a result, these attackers desire both access to + the bulk of Internet traffic and to the keying material required to + decrypt any traffic that has been encrypted. Even if keys are not + available, note that the presence of a communication and the fact + that it is encrypted may both be inputs to an analysis, even if the + attacker cannot decrypt the communication. + + The attacks listed above highlight new avenues both for access to + traffic and for access to relevant encryption keys. They further + indicate that the scale of surveillance is sufficient to provide a + general capability to cross-correlate communications, a threat not + previously thought to be relevant at the scale of the Internet. + + + + +Barnes, et al. Expires September 12, 2015 [Page 12] + +Internet-Draft Confidentiality Threat Model March 2015 + + +5.1. Attacker Capabilities + + +--------------------------+-------------------------------------+ + | Attack Class | Capability | + +--------------------------+-------------------------------------+ + | Passive observation | Directly capture data in transit | + | | | + | Passive inference | Infer from reduced/encrypted data | + | | | + | Active | Manipulate / inject data in transit | + | | | + | Static key exfiltration | Obtain key material once / rarely | + | | | + | Dynamic key exfiltration | Obtain per-session key material | + | | | + | Content exfiltration | Access data at rest | + +--------------------------+-------------------------------------+ + + Security analyses of Internet protocols commonly consider two classes + of attacker: Passive pervasive attackers, who can simply listen in on + communications as they transit the network, and active pervasive + attackers, who can modify or delete packets in addition to simply + collecting them. + + In the context of pervasive passive surveillance, these attacks take + on an even greater significance. In the past, these attackers were + often assumed to operate near the edge of the network, where attacks + can be simpler. For example, in some LANs, it is simple for any node + to engage in passive listening to other nodes' traffic or inject + packets to accomplish active pervasive attacks. However, as we now + know, both passive and active pervasive attacks are undertaken by + pervasive attackers closer to the core of the network, greatly + expanding the scope and capability of the attacker. + + Eavesdropping and observation at a larger scale make passive + inference attacks easier to carry out: a passive pervasive attacker + with access to a large portion of the Internet can analyze collected + traffic to create a much more detailed view of individual behavior + than an attacker that collects at a single point. Even the usual + claim that encryption defeats passive pervasive attackers is + weakened, since a pervasive flow access attacker can infer + relationships from correlations over large numbers of sessions, e.g., + pairing encrypted sessions with unencrypted sessions from the same + host, or performing traffic fingerprinting between known and unknown + encrypted sessions. Reports on the NSA XKEYSCORE system would + indicate it is an example of such an attacker. + + + + + +Barnes, et al. Expires September 12, 2015 [Page 13] + +Internet-Draft Confidentiality Threat Model March 2015 + + + An active pervasive attacker likewise has capabilities beyond those + of a localized active attacker. flow modification attacks are often + limited by network topology, for example by a requirement that the + attacker be able to see a targeted session as well as inject packets + into it. A pervasive flow modification attacker with access at + multiple points within the core of the Internet is able to overcome + these topological limitations and perform attacks over a much broader + scope. Being positioned in the core of the network rather than the + edge can also enable an active pervasive attacker to reroute targeted + traffic, amplifying the ability to perform both eavesdropping and + traffic injection. Active pervasive attackers can also benefit from + passive pervasive collection to identify vulnerable hosts. + + While not directly related to pervasiveness, attackers that are in a + position to mount a active pervasive attack are also often in a + position to subvert authentication, a traditional protection against + such attacks. Authentication in the Internet is often achieved via + trusted third party authorities such as the Certificate Authorities + (CAs) that provide web sites with authentication credentials. An + attacker with sufficient resources may also be able to induce an + authority to grant credentials for an identity of the attacker's + choosing. If the parties to a communication will trust multiple + authorities to certify a specific identity, this attack may be + mounted by suborning any one of the authorities (the proverbial + "weakest link"). Subversion of authorities in this way can allow an + active attack to succeed in spite of an authentication check. + + Beyond these three classes (observation, inference, and active), + reports on the BULLRUN effort to defeat encryption and the PRISM + effort to obtain data from service providers suggest three more + classes of attack: + + o Static key exfiltration + + o Dynamic key exfiltration + + o Content exfiltration + + These attacks all rely on a collaborator providing the attacker with + some information, either keys or data. These attacks have not + traditionally been considered in scope for the Security + Considerations sections of IETF protocols, as they occur outside the + protocol. + + The term "key exfiltration" refers to the transfer of keying material + for an encrypted communication from the collaborator to the attacker. + By "static", we mean that the transfer of keys happens once, or + rarely, typically of a long-lived key. For example, this case would + + + +Barnes, et al. Expires September 12, 2015 [Page 14] + +Internet-Draft Confidentiality Threat Model March 2015 + + + cover a web site operator that provides the private key corresponding + to its HTTPS certificate to an intelligence agency. + + "Dynamic" key exfiltration, by contrast, refers to attacks in which + the collaborator delivers keying material to the attacker frequently, + e.g., on a per-session basis. This does not necessarily imply + frequent communications with the attacker; the transfer of keying + material may be virtual. For example, if an endpoint were modified + in such a way that the attacker could predict the state of its + psuedorandom number generator, then the attacker would be able to + derive per-session keys even without per-session communications. + + Finally, content exfiltration is the attack in which the collaborator + simply provides the attacker with the desired data or metadata. + Unlike the key exfiltration cases, this attack does not require the + attacker to capture the desired data as it flows through the network. + The risk is to data at rest as opposed to data in transit. This + increases the scope of data that the attacker can obtain, since the + attacker can access historical data - the attacker does not have to + be listening at the time the communication happens. + + Exfiltration attacks can be accomplished via attacks against one of + the parties to a communication, i.e., by the attacker stealing the + keys or content rather than the party providing them willingly. In + these cases, the party may not be aware that they are collaborating, + at least at a human level. Rather, the subverted technical assets + are "collaborating" with the attacker (by providing keys/content) + without their owner's knowledge or consent. + + Any party that has access to encryption keys or unencrypted data can + be a collaborator. While collaborators are typically the endpoints + of a communication (with encryption securing the links), + intermediaries in an unencrypted communication can also facilitate + content exfiltration attacks as collaborators by providing the + attacker access to those communications. For example, documents + describing the NSA PRISM program claim that NSA is able to access + user data directly from servers, where it is stored unencrypted. In + these cases, the operator of the server would be a collaborator, if + an unwitting one. By contrast, in the NSA MUSCULAR program, a set of + collaborators enabled attackers to access the cables connecting data + centers used by service providers such as Google and Yahoo. Because + communications among these data centers were not encrypted, the + collaboration by an intermediate entity allowed NSA to collect + unencrypted user data. + + + + + + + +Barnes, et al. Expires September 12, 2015 [Page 15] + +Internet-Draft Confidentiality Threat Model March 2015 + + +5.2. Attacker Costs + + +--------------------------+-----------------------------------+ + | Attack Class | Cost / Risk to Attacker | + +--------------------------+-----------------------------------+ + | Passive observation | Passive data access | + | | | + | Passive inference | Passive data access + processing | + | | | + | Active | Active data access + processing | + | | | + | Static key exfiltration | One-time interaction | + | | | + | Dynamic key exfiltration | Ongoing interaction / code change | + | | | + | Content exfiltration | Ongoing, bulk interaction | + +--------------------------+-----------------------------------+ + + Each of the attack types discussed in the previous section entails + certain costs and risks. These costs differ by attack, and can be + helpful in guiding response to pervasive attack. + + Depending on the attack, the attacker may be exposed to several types + of risk, ranging from simply losing access to arrest or prosecution. + In order for any of these negative consequences to occur, however, + the attacker must first be discovered and identified. So the primary + risk we focus on here is the risk of discovery and attribution. + + A passive pervasive attack is the simplest to mount in some ways. + The base requirement is that the attacker obtain physical access to a + communications medium and extract communications from it. For + example, the attacker might tap a fiber-optic cable, acquire a mirror + port on a switch, or listen to a wireless signal. The need for these + taps to have physical access or proximity to a link exposes the + attacker to the risk that the taps will be discovered. For example, + a fiber tap or mirror port might be discovered by network operators + noticing increased attenuation in the fiber or a change in switch + configuration. Of course, passive pervasive attacks may be + accomplished with the cooperation of the network operator, in which + case there is a risk that the attacker's interactions with the + network operator will be exposed. + + In many ways, the costs and risks for an active pervasive attack are + similar to those for a passive pervasive attack, with a few + additions. An active attacker requires more robust network access + than a passive attacker, since for example they will often need to + transmit data as well as receiving it. In the wireless example + above, the attacker would need to act as an transmitter as well as + + + +Barnes, et al. Expires September 12, 2015 [Page 16] + +Internet-Draft Confidentiality Threat Model March 2015 + + + receiver, greatly increasing the probability the attacker will be + discovered (e.g., using direction-finding technology). Active + attacks are also much more observable at higher layers of the + network. For example, an active attacker that attempts to use a mis- + issued certificate could be detected via Certificate Transparency + [RFC6962]. + + In terms of raw implementation complexity, passive pervasive attacks + require only enough processing to extract information from the + network and store it. Active pervasive attacks, by contrast, often + depend on winning race conditions to inject pakets into active + connections. So active pervasive attacks in the core of the network + require processing hardware to that can operate at line speed + (roughly 100Gbps to 1Tbps in the core) to identify opportunities for + attack and insert attack traffic in a high-volume traffic. Key + exfiltration attacks rely on passive pervasive attack for access to + encrypted data, with the collaborator providing keys to decrypt the + data. So the attacker undertakes the cost and risk of a passive + pervasive attack, as well as additional risk of discovery via the + interactions that the attacker has with the collaborator. + + In this sense, static exfiltration has a lower risk profile than + dynamic. In the static case, the attacker need only interact with + the collaborator a small number of times, possibly only once, say to + exchange a private key. In the dynamic case, the attacker must have + continuing interactions with the collaborator. As noted above these + interactions may real, such as in-person meetings, or virtual, such + as software modifications that render keys available to the attacker. + Both of these types of interactions introduce a risk that they will + be discovered, e.g., by employees of the collaborator organization + noticing suspicious meetings or suspicious code changes. + + Content exfiltration has a similar risk profile to dynamic key + exfiltration. In a content exfiltration attack, the attacker saves + the cost and risk of conducting a passive pervasive attack. The risk + of discovery through interactions with the collaborator, however, is + still present, and may be higher. The content of a communication is + obviously larger than the key used to encrypt it, often by several + orders of magnitude. So in the content exfiltration case, the + interactions between the collaborator and the attacker need to be + much higher-bandwidth than in the key exfiltration cases, with a + corresponding increase in the risk that this high-bandwidth channel + will be discovered. + + It should also be noted that in these latter three exfiltration + cases, the collaborator also undertakes a risk that his collaboration + with the attacker will be discovered. Thus the attacker may have to + incur additional cost in order to convince the collaborator to + + + +Barnes, et al. Expires September 12, 2015 [Page 17] + +Internet-Draft Confidentiality Threat Model March 2015 + + + participate in the attack. Likewise, the scope of these attacks is + limited to case where the attacker can convince a collaborator to + participate. If the attacker is a national government, for example, + it may be able to compel participation within its borders, but have a + much more difficult time recruiting foreign collaborators. + + As noted above, the collaborator in an exfiltration attack can be + unwitting; the attacker can steal keys or data to enable the attack. + In some ways, the risks of this approach are similar to the case of + an active collaborator. In the static case, the attacker needs to + steal information from the collaborator once; in the dynamic case, + the attacker needs to continued presence inside the collaborators + systems. The main difference is that the risk in this case is of + automated discovery (e.g., by intrusion detection systems) rather + than discovery by humans. + +6. Security Considerations + + This document describes a threat model for pervasive surveillance + attacks. Mitigations are to be given in a future document. + +7. IANA Considerations + + This document has no actions for IANA. + +8. Acknowledgements + + Thanks to Dave Thaler for the list of attacks and taxonomy; to + Security Area Directors Stephen Farrell, Sean Turner, and Kathleen + Moriarty for starting and managing the IETF's discussion on pervasive + attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, + Evangelos Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, Russ Housley, + and the IAB Privacy and Security Program for their input. + +9. References + +9.1. Normative References + + [RFC6973] Cooper, A., Tschofenig, H., Aboba, B., Peterson, J., + Morris, J., Hansen, M., and R. Smith, "Privacy + Considerations for Internet Protocols", RFC 6973, July + 2013. + +9.2. Informative References + + + + + + + +Barnes, et al. Expires September 12, 2015 [Page 18] + +Internet-Draft Confidentiality Threat Model March 2015 + + + [pass1] The Guardian, "How the NSA is still harvesting your online + data", 2013, + . + + [pass2] The Guardian, "NSA's Prism surveillance program: how it + works and what it can do", 2013, + . + + [pass3] The Guardian, "XKeyscore: NSA tool collects 'nearly + everything a user does on the internet'", 2013, + . + + [pass4] The Guardian, "How does GCHQ's internet surveillance + work?", n.d., . + + [dec1] The New York Times, "N.S.A. Able to Foil Basic Safeguards + of Privacy on Web", 2013, + . + + [dec2] The Guardian, "Project Bullrun - classification guide to + the NSA's decryption program", 2013, + . + + [dec3] The Guardian, "Revealed: how US and UK spy agencies defeat + internet privacy and security", 2013, + . + + [TOR] The Tor Project, "Tor", 2013, + . + + [TOR1] Schneier, B., "How the NSA Attacks Tor/Firefox Users With + QUANTUM and FOXACID", 2013, + . + + [TOR2] The Guardian, "'Tor Stinks' presentation - read the full + document", 2013, + . + + + + + +Barnes, et al. Expires September 12, 2015 [Page 19] + +Internet-Draft Confidentiality Threat Model March 2015 + + + [dir1] The Guardian, "NSA collecting phone records of millions of + Verizon customers daily", 2013, + . + + [dir2] The Guardian, "NSA Prism program taps in to user data of + Apple, Google and others", 2013, + . + + [dir3] The Guardian, "Sigint - how the NSA collaborates with + technology companies", 2013, + . + + [secure] Schneier, B., "NSA surveillance: A guide to staying + secure", 2013, + . + + [snowden] Technology Review, "NSA Leak Leaves Crypto-Math Intact but + Highlights Known Workarounds", 2013, + . + + [spiegel1] + C Stocker, ., "NSA's Secret Toolbox: Unit Offers Spy + Gadgets for Every Need", December 2013, + . + + [spiegel3] + H Schmundt, ., "The Digital Arms Race: NSA Preps America + for Future Battle", January 2014, + . + + [key-recovery] + Golle, P., "The Design and Implementation of Protocol- + Based Hidden Key Recovery", 2003, + . + + [RFC1035] Mockapetris, P., "Domain names - implementation and + specification", STD 13, RFC 1035, November 1987. + + + + +Barnes, et al. Expires September 12, 2015 [Page 20] + +Internet-Draft Confidentiality Threat Model March 2015 + + + [RFC1918] Rekhter, Y., Moskowitz, R., Karrenberg, D., Groot, G., and + E. Lear, "Address Allocation for Private Internets", BCP + 5, RFC 1918, February 1996. + + [RFC1939] Myers, J. and M. Rose, "Post Office Protocol - Version 3", + STD 53, RFC 1939, May 1996. + + [RFC2015] Elkins, M., "MIME Security with Pretty Good Privacy + (PGP)", RFC 2015, October 1996. + + [RFC2821] Klensin, J., "Simple Mail Transfer Protocol", RFC 2821, + April 2001. + + [RFC3261] Rosenberg, J., Schulzrinne, H., Camarillo, G., Johnston, + A., Peterson, J., Sparks, R., Handley, M., and E. + Schooler, "SIP: Session Initiation Protocol", RFC 3261, + June 2002. + + [RFC3365] Schiller, J., "Strong Security Requirements for Internet + Engineering Task Force Standard Protocols", BCP 61, RFC + 3365, August 2002. + + [RFC3501] Crispin, M., "INTERNET MESSAGE ACCESS PROTOCOL - VERSION + 4rev1", RFC 3501, March 2003. + + [RFC3851] Ramsdell, B., "Secure/Multipurpose Internet Mail + Extensions (S/MIME) Version 3.1 Message Specification", + RFC 3851, July 2004. + + [RFC4033] Arends, R., Austein, R., Larson, M., Massey, D., and S. + Rose, "DNS Security Introduction and Requirements", RFC + 4033, March 2005. + + [RFC4301] Kent, S. and K. Seo, "Security Architecture for the + Internet Protocol", RFC 4301, December 2005. + + [RFC4303] Kent, S., "IP Encapsulating Security Payload (ESP)", RFC + 4303, December 2005. + + [RFC4306] Kaufman, C., "Internet Key Exchange (IKEv2) Protocol", RFC + 4306, December 2005. + + [RFC4949] Shirey, R., "Internet Security Glossary, Version 2", RFC + 4949, August 2007. + + [RFC5246] Dierks, T. and E. Rescorla, "The Transport Layer Security + (TLS) Protocol Version 1.2", RFC 5246, August 2008. + + + + +Barnes, et al. Expires September 12, 2015 [Page 21] + +Internet-Draft Confidentiality Threat Model March 2015 + + + [RFC5321] Klensin, J., "Simple Mail Transfer Protocol", RFC 5321, + October 2008. + + [RFC5655] Trammell, B., Boschi, E., Mark, L., Zseby, T., and A. + Wagner, "Specification of the IP Flow Information Export + (IPFIX) File Format", RFC 5655, October 2009. + + [RFC5750] Ramsdell, B. and S. Turner, "Secure/Multipurpose Internet + Mail Extensions (S/MIME) Version 3.2 Certificate + Handling", RFC 5750, January 2010. + + [RFC6120] Saint-Andre, P., "Extensible Messaging and Presence + Protocol (XMPP): Core", RFC 6120, March 2011. + + [RFC6962] Laurie, B., Langley, A., and E. Kasper, "Certificate + Transparency", RFC 6962, June 2013. + + [RFC6698] Hoffman, P. and J. Schlyter, "The DNS-Based Authentication + of Named Entities (DANE) Transport Layer Security (TLS) + Protocol: TLSA", RFC 6698, August 2012. + + [RFC7011] Claise, B., Trammell, B., and P. Aitken, "Specification of + the IP Flow Information Export (IPFIX) Protocol for the + Exchange of Flow Information", STD 77, RFC 7011, September + 2013. + + [RFC7258] Farrell, S. and H. Tschofenig, "Pervasive Monitoring Is an + Attack", BCP 188, RFC 7258, May 2014. + + [I-D.ietf-dprive-problem-statement] + Bortzmeyer, S., "DNS privacy considerations", draft-ietf- + dprive-problem-statement-03 (work in progress), March + 2015. + +Authors' Addresses + + Richard Barnes + + Email: rlb@ipv.sx + + + Bruce Schneier + + Email: schneier@schneier.com + + + + + + + +Barnes, et al. Expires September 12, 2015 [Page 22] + +Internet-Draft Confidentiality Threat Model March 2015 + + + Cullen Jennings + + Email: fluffy@cisco.com + + + Ted Hardie + + Email: ted.ietf@gmail.com + + + Brian Trammell + + Email: ietf@trammell.ch + + + Christian Huitema + + Email: huitema@huitema.net + + + Daniel Borkmann + + Email: dborkman@redhat.com + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Barnes, et al. Expires September 12, 2015 [Page 23] diff --git a/draft-iab-privsec-confidentiality-threat-04.xml b/draft-iab-privsec-confidentiality-threat-04.xml new file mode 100644 index 0000000..fd694d2 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-04.xml @@ -0,0 +1,1093 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +]> + + + + + + Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement + + + +
+ rlb@ipv.sx +
+ + + +
+ schneier@schneier.com +
+ + + +
+ fluffy@cisco.com +
+ + + +
+ ted.ietf@gmail.com +
+ + + +
+ ietf@trammell.ch +
+ + + +
+ huitema@huitema.net +
+ + + +
+ dborkman@redhat.com +
+ + + + + + + + + + + +Documents published since initial revelations in 2013 have revealed +several classes of pervasive surveillance attack on Internet +communications. In this document we develop a threat model that +describes these pervasive attacks. We start by assuming an attacker +with an interest in undetected, indiscriminate eavesdropping, then +expand the threat model with a set of verified attacks that have been +published. + + + + + + + + + + + +
+ +Starting in June 2013, documents released to the press by Edward +Snowden have revealed several operations undertaken by intelligence +agencies to exploit Internet communications for intelligence purposes. +These attacks were largely based on protocol vulnerabilities that were +already known to exist. The attacks were nonetheless striking in +their pervasive nature, both in terms of the amount of Internet +communications targeted, and in terms of the diversity of attack +techniques employed. + +To ensure that the Internet can be trusted by users, it is necessary +for the Internet technical community to address the vulnerabilities +exploited in these attacks . The goal of this document is +to describe more precisely the threats posed by these pervasive +attacks, and based on those threats, lay out the problems that need to +be solved in order to secure the Internet in the face of those +threats. + +The remainder of this document is structured as follows. In +, we describe an idealized passive pervasive attacker, one which +could completely undetectably compromise communications at Internet +scale. In , we provide a brief summary of some attacks +that have been disclosed, and use these to expand the assumed +capabilities of our idealized attacker. Note that we do not attempt +to describe all possible attacks, but focus on those which result in +undetected eavesdropping. describes a threat model based on +these attacks, focusing on classes of attack that have not been a +focus of Internet engineering to date. + +
+
+ +This document makes extensive use of standard security and privacy +terminology; see and . Terms used from + include Eavesdropper, Observer, Initiator, Intermediary, +Recipient, Attack (in a privacy context), Correlation, Fingerprint, +Traffic Analysis, and Identifiability (and related terms). In +addition, we use a few terms that are specific to the attacks +discussed in this document. Note especially that “passive” and “active” below +do not refer to the effort used to mount the attack; a “passive attack” +is any attack that accesses a flow but does not modify it, while an +“active attack” is any attack that modifies a flow. Some passive attacks +involve active interception and modifications of devices, rather than simple +access to the medium. The introduced terms are: + + + + An attack on Internet communications that makes +use of access at a large number of points in the network, or otherwise +provides the attacker with access to a large amount of Internet +traffic; see + + An eavesdropping attack undertaken by a pervasive attacker, in which the +packets in a traffic stream between two endpoints are eavesdropped upon, but +in which the attacker does not modify the packets in the traffic +stream between two endpoints, modify the treatment of packets in the +traffic stream (e.g. delay, routing), or add or remove packets in the +traffic stream. Passive pervasive attacks are undetectable from the +endpoints. Equivalent to passive wiretapping as defined in ; +we use an alternate term here since the methods employed are wider +than those implied by the word “wiretapping”, including the active +compromise of intermediate systems. + + An attack undertaken by a pervasive attacker, which in addition to +the elements of a passive pervasive attack, also includes modification, +addition, or removal of +packets in a traffic stream, or modification of treatment of packets +in the traffic stream. Active pervasive attacks provide more +capabilities to the attacker at the cost of possible detection at the +endpoints. Equivalent to active wiretapping as defined in . + + Information collected directly from communications by an +eavesdropper or observer. For example, the knowledge that +<alice@example.com> sent a message to <bob@example.com> +via SMTP taken from the headers of an observed SMTP message would be +an observation. + + Information extracted from analysis of information collected +directly from communications by an eavesdropper or observer. For +example, the knowledge that a given web page was accessed by a given +IP address, by comparing the size in octets of measured network flow +records to fingerprints derived from known sizes of linked resources +on the web servers involved, would be an inference. + + An entity that is a legitimate participant in a communication, but +who deliberately provides information about that interaction to an +attacker. + + An entity that is a legitimate participant in a communication, and +who is the source of information obtained by the attacker without the +entity’s consent or intention, because the attacker has exploited some +technology used by the entity. + + The transmission of keying material for an encrypted communication +from a collaborator, deliberately or unwittingly, to an attacker + + The transmission of the content of a communication from a collaborator, deliberately or unwittingly, to an attacker + + +
+
+ +In considering the threat posed by pervasive surveillance, we begin by +defining an idealized passive pervasive attacker. While this attacker +is less capable than those which we now know to have compromised the +Internet from press reports, as elaborated in , it does +set a lower bound on the capabilities of an attacker interested in +indiscriminate passive surveillance while interested in remaining +undetectable. We note that, prior to the Snowden revelations in 2013, +the assumptions of attacker capability presented here would be +considered on the border of paranoia outside the network security +community. + +Our idealized attacker is an indiscriminate eavesdropper on an Internet-attached computer network that: + + + can observe every packet of all communications at any hop in any network path between an initiator and a recipient; + can observe data at rest in any intermediate system between the endpoints controlled by the initiator and recipient; and + can share information with other such attackers; but + takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.). + + +The techniques available to our ideal attacker are direct observation +and inference. Direct observation involves taking information directly +from eavesdropped communications - e.g., URLs identifying content or +email addresses identifying individuals from application-layer +headers. Inference, on the other hand, involves analyzing eavesdropped +information to derive new information from it; e.g., searching for +application or behavioral fingerprints in observed traffic to derive +information about the observed individual from them, in absence of +directly-observed sources of the same information. The use of +encryption to protect confidentiality is generally enough to prevent +direct observation of unencrypted content, assuming uncompromised +encryption implementations and key material. However, it provides less +complete protection against inference, especially inference based only +on unprotected portions of communications (e.g. IP and TCP headers for +TLS ). + +
+ +Protocols which do not encrypt their payload make the entire content +of the communication available to the idealized attacker along their +path. Following the advice in , most such protocols have a +secure variant which encrypts payload for confidentiality, and these +secure variants are seeing ever-wider deployment. A noteworthy +exception is DNS , as DNSSEC does not have +confidentiality as a requirement. + +This implies that, in the absence of +changes to the protocol as presently under development in the IETF’s +DNS Private Exchange (DPRIVE) +working group , all DNS queries and answers generated by the activities +of any protocol are available to the attacker. + +Protocols which imply the storage of some data at rest in +intermediaries (e.g. SMTP ) leave this data subject to +observation by an attacker that has compromised these intermediaries, +unless the data is encrypted end-to-end by the application layer +protocol, or the implementation uses an encrypted store for this data. + +
+
+ +Inference is information extracted from later analysis of an observed +or eavesdropped communication, and/or correlation of observed or +eavesdropped information with information available from other +sources. Indeed, most useful inference performed by the attacker falls +under the rubric of correlation. The simplest example of this is the +observation of DNS queries and answers from and to a source and +correlating those with IP addresses with which that source +communicates. This can give access to information otherwise not +available from encrypted application payloads (e.g., the Host: +HTTP/1.1 request header when HTTP is used with TLS). + +Protocols which encrypt their payload using an application- or +transport-layer encryption scheme (e.g. TLS) still expose all the +information in their network and transport layer headers to the +attacker, including source and destination addresses and ports. IPsec +ESP further encrypts the transport-layer headers, but still +leaves IP address information unencrypted; in tunnel mode, these +addresses correspond to the tunnel endpoints. Features of the +cryptographic protocols themselves, e.g. the TLS session identifier, +may leak information that can be used for correlation and +inference. While this information is much less semantically rich than +the application payload, it can still be useful for the inferring an +individual’s activities. + +Inference can also leverage information obtained from sources other +than direct traffic observation. Geolocation databases, for example, +have been developed map IP addresses to a location, in order to +provide location-aware services such as targeted advertising. This +location information is often of sufficient resolution that it can be +used to draw further inferences toward identifying or profiling an +individual. + +Social media provide another source of more or less publicly +accessible information. This information can be extremely semantically +rich, including information about an individual’s location, +associations with other individuals and groups, and +activities. Further, this information is generally contributed and +curated voluntarily by the individuals themselves: it represents +information which the individuals are not necessarily interested in +protecting for privacy reasons. However, correlation of this social +networking data with information available from direct observation of +network traffic allows the creation of a much richer picture of an +individual’s activities than either alone. + +We note with some alarm that there is little that can be done at +protocol design time to limit such correlation by the attacker, and +that the existence of such data sources in many cases greatly +complicates the problem of protecting privacy by hardening protocols +alone. + +
+
+ +To illustrate how capable the idealized attacker is even given its +limitations, we explore the non-anonymity of encrypted IP traffic in +this section. Here we examine in detail some inference techniques for +associating a set of addresses with an individual, in order to +illustrate the difficulty of defending communications against our +idealized attacker. Here, the basic problem is that information +radiated even from protocols which have no obvious connection with +personal data can be correlated with other information which can paint +a very rich behavioral picture, that only takes one unprotected link +in the chain to associate with an identity. + +
+ +Internet traffic can be monitored by tapping Internet links, or by +installing monitoring tools in Internet routers. Of course, a single +link or a single router only provides access to a fraction of the +global Internet traffic. However, monitoring a number of high capacity +links or a set of routers placed at strategic locations provides +access to a good sampling of Internet traffic. + +Tools like IPFIX allow administrators to acquire +statistics about sequences of packets with some common properties that +pass through a network device. The most common set of properties used +in flow measurement is the “five-tuple”of source and destination +addresses, protocol type, and source and destination ports. These +statistics are commonly used for network engineering, but could +certainly be used for other purposes. + +Let’s assume for a moment that IP addresses can be correlated to +specific services or specific users. Analysis of the sequences of +packets will quickly reveal which users use what services, and also +which users engage in peer-to-peer connections with other +users. Analysis of traffic variations over time can be used to detect +increased activity by particular users, or in the case of peer-to-peer +connections increased activity within groups of users. + +
+
+ +The correlation of IP addresses with specific users can be done in +various ways. For example, tools like reverse DNS lookup can be used +to retrieve the DNS names of servers. Since the addresses of servers +tend to be quite stable and since servers are relatively less numerous +than users, an attacker could easily maintain its own copy of the DNS +for well-known or popular servers, to accelerate such lookups. + +On the other hand, the reverse lookup of IP addresses of users is +generally less informative. For example, a lookup of the address +currently used by one author’s home network returns a name of the form +“c-192-000-002-033.hsd1.wa.comcast.net”. This particular type of +reverse DNS lookup generally reveals only coarse-grained location or +provider information, equivalent to that available from geolocation +databases. + +In many jurisdictions, Internet Service Providers (ISPs) are required +to provide identification on a case by case basis of the “owner” of a +specific IP address for law enforcement purposes. This is a reasonably +expedient process for targeted investigations, but pervasive +surveillance requires something more efficient. This provides an +incentive for the attacker to secure the cooperation of the ISP in +order to automate this correlation. + +
+
+ +Even if the ISP does not cooperate, user identity can often be +obtained via inference. POP3 and IMAP are used +to retrieve mail from mail servers, while a variant of SMTP is used to +submit messages through mail servers. IMAP connections originate from +the client, and typically start with an authentication exchange in +which the client proves its identity by answering a password +challenge. The same holds for the SIP protocol and many +instant messaging services operating over the Internet using +proprietary protocols. + +The username is directly observable if any of these protocols operate +in cleartext; the username can then be directly associated with the +source address. + +
+
+ +SMTP requires that each successive SMTP relay adds a +“Received” header to the mail headers. The purpose of these headers is +to enable audit of mail transmission, and perhaps to distinguish +between regular mail and spam. Here is an extract from the headers of +a message recently received from the “perpass” mailing list: + + + Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?) + (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA + (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100 + Message-ID: <526D7BD2.7070908@example.org> + Date: Sun, 27 Oct 2013 20:47:14 +0000 + From: Some One <some.one@example.org> + + +This is the first “Received” header attached to the message by the +first SMTP relay; for privacy reasons, the field values have been +anonymized. We learn here that the message was submitted by “Some One” +on October 27, from a host behind a NAT (192.168.1.100) +that used the IP address 192.0.2.44. The information remained in the +message, and is accessible by all recipients of the “perpass” mailing +list, or indeed by any attacker that sees at least one copy of the +message. + +An attacker that can observe sufficient email traffic can regularly +update the mapping between public IP addresses and individual email +identities. Even if the SMTP traffic was encrypted on submission and +relaying, the attacker can still receive a copy of public mailing +lists like “perpass”. + +
+
+ +Many web sites only encrypt a small fraction of their transactions. A +popular pattern is to use HTTPS for the login information, and then +use a “cookie” to associate following clear-text transactions with the +user’s identity. Cookies are also used by various advertisement +services to quickly identify the users and serve them with +“personalized” advertisements. Such cookies are particularly useful if +the advertisement services want to keep tracking the user across +multiple sessions that may use different IP addresses. + +As cookies are sent in clear text, an attacker can build a database +that associates cookies to IP addresses for non-HTTPS traffic. If the +IP address is already identified, the cookie can be linked to the user +identify. After that, if the same cookie appears on a new IP address, +the new IP address can be immediately associated with the +pre-determined identity. + +
+
+ +An attacker can track traffic from an IP address not yet associated +with an individual to various public services (e.g. websites, mail +servers, game servers), and exploit patterns in the observed traffic +to correlate this address with other addresses that show similar +patterns. For example, any two addresses that show connections to the +same IMAP or webmail services, the same set of favorite websites, and +game servers at similar times of day may be associated with the same +individual. Correlated addresses can then be tied to an individual +through one of the techniques above, walking the “network graph” to +expand the set of attributable traffic. + +
+
+ +Moving back down the stack, technologies like Ethernet or Wi-Fi use +MAC Addresses to identify link-level destinations. MAC Addresses +assigned according to IEEE-802 standards are unique to the device. If +the link is publicly accessible, an attacker can track it. For +example, the attacker can track the wireless traffic at public Wi-Fi +networks. Simple devices can monitor the traffic, and reveal which MAC +Addresses are present. If the network does not use some form of Wi-Fi +encryption, or if the attacker can access the decrypted traffic, the +analysis will also provide the correlation between MAC Addresses and +IP addresses. Additional monitoring using techniques exposed in the +previous sections will reveal the correlation between MAC Addresses, +IP Addresses, and user identity. + +Given that large-scale databases of the MAC addresses of wireless +access points for geolocation purposes have been known to exist for +some time, the attacker could easily build a database linking MAC +Addresses and device or user identities, and use it to track the +movement of devices and of their owners. + +
+
+
+
+ +The situation in reality is more bleak than that suggested by an +analysis of our idealized attacker. Through revelations of sensitive +documents in several media outlets, the Internet community has been +made aware of several intelligence activities conducted by US and UK +national intelligence agencies, particularly the US National Security +Agency (NSA) and the UK Government Communications Headquarters +(GCHQ). These documents have revealed methods that these agencies use +to attack Internet applications and obtain sensitive user information. +We note that these reports are primarily useful as an illustration of +the types of capabilities fielded by pervasive attackers as of the +date of the Snowden leaks in 2013. + +First, they confirm the deployment of large-scale passive +collection of Internet traffic, which confirms the existence of +pervasive passive attackers with at least the capabilities of our +idealized attacker. For example : + + + NSA’s XKEYSCORE system accesses data from multiple access points and +searches for “selectors” such as email addresses, at the scale of tens +of terabytes of data per day. + GCHQ’s Tempora system appears to have access to around 1,500 major cables +passing through the UK. + NSA’s MUSCULAR program has tapped cables between data centers +belonging to major service providers. + Several programs appear to perform wide-scale collection +of cookies in web traffic and location data from location-aware +portable devices such as smartphones. + + +However, the capabilities described by these reports go beyond those of our +idealized attacker. They include the compromise of cryptographic protocols, +including decryption of TLS-protected Internet sessions . +For example, the NSA BULLRUN project worked to undermine encryption through +multiple approaches, including covert modifications to cryptographic +software on end systems. + +They also include the direct compromise of intermediate systems +and arrangements with service providers for bulk data and metadata +access , bypassing the need to capture +traffic on the wire. For example, the NSA PRISM program provides the +agency with access to many types of user data (e.g., email, chat, VoIP). + +The reported capabilities also include elements of active pervasive attack, +including: + + + Insertion of devices as a man-in-the-middle of Internet +transactions . For example, NSA’s QUANTUM system +appears to use several different techniques to hijack HTTP +connections, ranging from DNS response injection to HTTP 302 +redirects. + Use of implants on end systems to undermine security and anonymity +features . For example, QUANTUM is used to +direct users to a FOXACID server, which in turn delivers an implant +to compromise browsers of Tor users. + Use of implants on network elements from many major equipment providers, +including Cisco, Juniper, Huawei, Dell, and HP, as provided by the NSA’s +Advanced Network Technology group. + Use of botnet-scale collections of compromised hosts . + + +The scale of the compromise extends beyond the network to include subversion of the technical standards process itself. For example, there is suspicion that NSA modifications to the DUAL_EC_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA. This RNG was made part of NIST’s SP 800-90A, for which NIST acknowledges NSA’s assistance. There have also been reports that the NSA paid RSA Security for a related contract with the result that the curve became the default in the RSA BSAFE product line. + +We use the term “pervasive attack” to collectively +describe these operations. The term “pervasive” is used because the +attacks are designed to indiscriminately gather as much data as +possible and to apply selective analysis on targets after the fact. +This means that all, or nearly all, Internet communications are +targets for these attacks. To achieve this scale, the attacks are +physically pervasive; they affect a large number of Internet +communications. They are pervasive in content, consuming and +exploiting any information revealed by the protocol. And they are +pervasive in technology, exploiting many different vulnerabilities in +many different protocols. + +It’s important to note that although the attacks mentioned above were +executed by NSA and GCHQ, there are many other organizations that can +mount pervasive surveillance attacks. Because of the resources +required to achieve pervasive scale, these attacks are most commonly +undertaken by nation-state actors. For example, the Chinese Internet +filtering system known as the “Great Firewall of China” uses several +techniques that are similar to the QUANTUM program, and which have a +high degree of pervasiveness with regard to the Internet in China. + +
+
+ +Given these disclosures, we must consider a broader threat model. + +Pervasive surveillance aims to collect information across a large +number of Internet communications, analyzing the collected +communications to identify information of interest within individual +communications, or inferring information from correlated +communications. his analysis sometimes benefits from decryption of +encrypted communications and deanonymization of anonymized +communications. As a result, these attackers desire both access to +the bulk of Internet traffic and to the keying material required to +decrypt any traffic that has been encrypted. Even if keys are not +available, note that the presence of a communication and the fact that +it is encrypted may both be inputs to an analysis, even if the +attacker cannot decrypt the communication. + +The attacks listed above highlight new avenues both for access to +traffic and for access to relevant encryption keys. They further +indicate that the scale of surveillance is sufficient to provide a +general capability to cross-correlate communications, a threat not +previously thought to be relevant at the scale of the Internet. + +
+ + + Attack Class + Capability + Passive observation + Directly capture data in transit + Passive inference + Infer from reduced/encrypted data + Active + Manipulate / inject data in transit + Static key exfiltration + Obtain key material once / rarely + Dynamic key exfiltration + Obtain per-session key material + Content exfiltration + Access data at rest + + +Security analyses of Internet protocols commonly consider two classes +of attacker: Passive pervasive attackers, who can simply listen in on +communications as they transit the network, and active pervasive +attackers, who can modify or delete packets in addition to simply +collecting them. + +In the context of pervasive passive surveillance, these attacks take +on an even greater significance. In the past, these attackers were +often assumed to operate near the edge of the network, where attacks +can be simpler. For example, in some LANs, it is simple for any node +to engage in passive listening to other nodes’ traffic or inject +packets to accomplish active pervasive attacks. However, as we now +know, both passive and active pervasive attacks are undertaken by +pervasive attackers closer to the core of the network, greatly +expanding the scope and capability of the attacker. + +Eavesdropping and observation at a larger scale make passive inference +attacks easier to carry out: a passive pervasive attacker with access to a +large portion of the Internet can analyze collected traffic to create +a much more detailed view of individual behavior than an attacker that +collects at a single point. Even the usual claim that encryption +defeats passive pervasive attackers is weakened, since a pervasive flow +access attacker can infer relationships from correlations over large +numbers of sessions, e.g., pairing encrypted sessions with unencrypted +sessions from the same host, or performing traffic fingerprinting +between known and unknown encrypted sessions. Reports on the NSA +XKEYSCORE system would indicate it is an example of such an attacker. + +An active pervasive attacker likewise has capabilities +beyond those of a localized active attacker. flow +modification attacks are often limited by network topology, for +example by a requirement that the attacker be able to see a targeted +session as well as inject packets into it. A pervasive flow +modification attacker with access at multiple points within the core +of the Internet is able to overcome these topological limitations and +perform attacks over a much broader scope. Being positioned in the +core of the network rather than the edge can also enable an active +pervasive attacker to reroute targeted traffic, amplifying the +ability to perform both eavesdropping and traffic injection. +Active pervasive attackers can also benefit from passive pervasive +collection to identify vulnerable hosts. + +While not directly related to pervasiveness, attackers that are in a +position to mount a active pervasive attack are also often +in a position to subvert authentication, a traditional protection +against such attacks. Authentication in the Internet is often +achieved via trusted third party authorities such as the Certificate +Authorities (CAs) that provide web sites with authentication +credentials. An attacker with sufficient resources may also be able to +induce an authority to grant credentials for an identity of the +attacker’s choosing. If the parties to a communication will trust +multiple authorities to certify a specific identity, this attack may +be mounted by suborning any one of the authorities (the proverbial +“weakest link”). Subversion of authorities in this way can allow an +active attack to succeed in spite of an authentication +check. + +Beyond these three classes (observation, inference, and active), +reports on the BULLRUN effort to defeat encryption and the PRISM +effort to obtain data from service providers suggest three more +classes of attack: + + + Static key exfiltration + Dynamic key exfiltration + Content exfiltration + + +These attacks all rely on a collaborator providing the attacker with +some information, either keys or data. These attacks have not +traditionally been considered in scope for the Security Considerations +sections of IETF protocols, as they occur outside the protocol. + +The term “key exfiltration” refers to the transfer of keying material +for an encrypted communication from the collaborator to the attacker. +By “static”, we mean that the transfer of keys happens once, or +rarely, typically of a long-lived key. For example, this case would +cover a web site operator that provides the private key corresponding +to its HTTPS certificate to an intelligence agency. + +“Dynamic” key exfiltration, by contrast, refers to attacks in which +the collaborator delivers keying material to the attacker frequently, +e.g., on a per-session basis. This does not necessarily imply +frequent communications with the attacker; the transfer of keying +material may be virtual. For example, if an endpoint were modified in +such a way that the attacker could predict the state of its +psuedorandom number generator, then the attacker would be able to +derive per-session keys even without per-session communications. + +Finally, content exfiltration is the attack in which the collaborator +simply provides the attacker with the desired data or metadata. Unlike +the key exfiltration cases, this attack does not require the attacker +to capture the desired data as it flows through the network. The risk +is to data at rest as opposed to data in transit. This increases the +scope of data that the attacker can obtain, since the attacker can +access historical data – the attacker does not have to be listening +at the time the communication happens. + +Exfiltration attacks can be accomplished via attacks against one of +the parties to a communication, i.e., by the attacker stealing the +keys or content rather than the party providing them willingly. In +these cases, the party may not be aware that they are collaborating, +at least at a human level. Rather, the subverted technical assets are +“collaborating” with the attacker (by providing keys/content) without +their owner’s knowledge or consent. + +Any party that has access to encryption keys or unencrypted data can +be a collaborator. While collaborators are typically the endpoints of +a communication (with encryption securing the links), intermediaries +in an unencrypted communication can also facilitate content +exfiltration attacks as collaborators by providing the attacker access +to those communications. For example, documents describing the NSA +PRISM program claim that NSA is able to access user data directly from +servers, where it is stored unencrypted. In these cases, the operator +of the server would be a collaborator, if an unwitting one. By +contrast, in the NSA MUSCULAR program, a set of collaborators enabled +attackers to access the cables connecting data centers used by service +providers such as Google and Yahoo. Because communications among +these data centers were not encrypted, the collaboration by an +intermediate entity allowed NSA to collect unencrypted user data. + +
+
+ + + Attack Class + Cost / Risk to Attacker + Passive observation + Passive data access + Passive inference + Passive data access + processing + Active + Active data access + processing + Static key exfiltration + One-time interaction + Dynamic key exfiltration + Ongoing interaction / code change + Content exfiltration + Ongoing, bulk interaction + + +Each of the attack types discussed in the previous section entails +certain costs and risks. These costs differ by attack, and can be +helpful in guiding response to pervasive attack. + +Depending on the attack, the attacker may be exposed to several types +of risk, ranging from simply losing access to arrest or prosecution. +In order for any of these negative consequences to occur, however, the +attacker must first be discovered and identified. So the primary risk +we focus on here is the risk of discovery and attribution. + +A passive pervasive attack is the simplest to mount in some ways. The base +requirement is that the attacker obtain physical access to a +communications medium and extract communications from it. For +example, the attacker might tap a fiber-optic cable, acquire a mirror +port on a switch, or listen to a wireless signal. The need for these +taps to have physical access or proximity to a link exposes the +attacker to the risk that the taps will be discovered. For example, a +fiber tap or mirror port might be discovered by network operators +noticing increased attenuation in the fiber or a change in switch +configuration. Of course, passive pervasive attacks may be accomplished +with the cooperation of the network operator, in which case there is a +risk that the attacker’s interactions with the network operator will +be exposed. + +In many ways, the costs and risks for an active pervasive attack are +similar to those for a passive pervasive attack, with a few additions. An +active attacker requires more robust network access than a +passive attacker, since for example they will often need to +transmit data as well as receiving it. In the wireless example above, +the attacker would need to act as an transmitter as well as receiver, +greatly increasing the probability the attacker will be discovered +(e.g., using direction-finding technology). Active attacks +are also much more observable at higher layers of the network. For +example, an active attacker that attempts to use a +mis-issued certificate could be detected via Certificate Transparency +. + +In terms of raw implementation complexity, passive pervasive attacks require +only enough processing to extract information from the network and +store it. Active pervasive attacks, by contrast, often depend on +winning race conditions to inject pakets into active connections. So +active pervasive attacks in the core of the network require +processing hardware to that can operate at line speed (roughly 100Gbps +to 1Tbps in the core) to identify opportunities for attack and insert +attack traffic in a high-volume traffic. Key exfiltration attacks +rely on passive pervasive attack for access to encrypted data, with the +collaborator providing keys to decrypt the data. So the attacker +undertakes the cost and risk of a passive pervasive attack, as well as +additional risk of discovery via the interactions that the attacker +has with the collaborator. + +In this sense, static exfiltration has a lower risk profile than +dynamic. In the static case, the attacker need only interact with the +collaborator a small number of times, possibly only once, say to +exchange a private key. In the dynamic case, the attacker must have +continuing interactions with the collaborator. As noted above these +interactions may real, such as in-person meetings, or virtual, such as +software modifications that render keys available to the attacker. +Both of these types of interactions introduce a risk that they will be +discovered, e.g., by employees of the collaborator organization +noticing suspicious meetings or suspicious code changes. + +Content exfiltration has a similar risk profile to dynamic key +exfiltration. In a content exfiltration attack, the attacker saves +the cost and risk of conducting a passive pervasive attack. The risk of +discovery through interactions with the collaborator, however, is +still present, and may be higher. The content of a communication is +obviously larger than the key used to encrypt it, often by several +orders of magnitude. So in the content exfiltration case, the +interactions between the collaborator and the attacker need to be much +higher-bandwidth than in the key exfiltration cases, with a +corresponding increase in the risk that this high-bandwidth channel +will be discovered. + +It should also be noted that in these latter three exfiltration cases, +the collaborator also undertakes a risk that his collaboration with +the attacker will be discovered. Thus the attacker may have to incur +additional cost in order to convince the collaborator to participate +in the attack. Likewise, the scope of these attacks is limited to +case where the attacker can convince a collaborator to participate. +If the attacker is a national government, for example, it may be able +to compel participation within its borders, but have a much more +difficult time recruiting foreign collaborators. + +As noted above, the collaborator in an exfiltration attack can be +unwitting; the attacker can steal keys or data to enable the attack. +In some ways, the risks of this approach are similar to the case of an +active collaborator. In the static case, the attacker needs to steal +information from the collaborator once; in the dynamic case, the +attacker needs to continued presence inside the collaborators systems. +The main difference is that the risk in this case is of automated +discovery (e.g., by intrusion detection systems) rather than discovery +by humans. + +
+
+
+ +This document describes a threat model for pervasive surveillance +attacks. Mitigations are to be given in a future document. + +
+
+ +This document has no actions for IANA. + +
+
+ +Thanks to Dave Thaler for the list of attacks and taxonomy; to +Security Area Directors Stephen Farrell, Sean Turner, and Kathleen +Moriarty for starting and managing the IETF’s discussion on pervasive +attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, Evangelos +Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, Russ Housley, and the IAB +Privacy and Security Program for their input. + +
+ + + + + + + + +&RFC6973; + + + + + + + + + How the NSA is still harvesting your online data + + The Guardian + + + + + + + NSA's Prism surveillance program: how it works and what it can do + + The Guardian + + + + + + + XKeyscore: NSA tool collects 'nearly everything a user does on the internet' + + The Guardian + + + + + + + How does GCHQ's internet surveillance work? + + The Guardian + + + + + + + N.S.A. Able to Foil Basic Safeguards of Privacy on Web + + The New York Times + + + + + + + Project Bullrun – classification guide to the NSA's decryption program + + The Guardian + + + + + + + Revealed: how US and UK spy agencies defeat internet privacy and security + + The Guardian + + + + + + + Tor + + The Tor Project + + + + + + + How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID + + + + + + + + + 'Tor Stinks' presentation – read the full document + + The Guardian + + + + + + + NSA collecting phone records of millions of Verizon customers daily + + The Guardian + + + + + + + NSA Prism program taps in to user data of Apple, Google and others + + The Guardian + + + + + + + Sigint – how the NSA collaborates with technology companies + + The Guardian + + + + + + + NSA surveillance: A guide to staying secure + + The Guardian + + + + + + + NSA Leak Leaves Crypto-Math Intact but Highlights Known Workarounds + + Technology Review + + + + + + + NSA's Secret Toolbox: Unit Offers Spy Gadgets for Every Need + + + + + + + + + The Digital Arms Race: NSA Preps America for Future Battle + + + + + + + + + The Design and Implementation of Protocol-Based Hidden Key Recovery + + + + + + +&RFC1035; +&RFC1918; +&RFC1939; +&RFC2015; +&RFC2821; +&RFC3261; +&RFC3365; +&RFC3501; +&RFC3851; +&RFC4033; +&RFC4301; +&RFC4303; +&RFC4306; +&RFC4949; +&RFC5246; +&RFC5321; +&RFC5655; +&RFC5750; +&RFC6120; +&RFC6962; +&RFC6698; +&RFC7011; +&RFC7258; +&I-D.ietf-dprive-problem-statement; + + + + + + + + + diff --git a/draft-iab-privsec-confidentiality-threat-05.md b/draft-iab-privsec-confidentiality-threat-05.md new file mode 100644 index 0000000..18b6fe2 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-05.md @@ -0,0 +1,1026 @@ +--- +title: "Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement" +abbrev: Confidentiality Threat Model +docname: draft-iab-privsec-confidentiality-threat-05 +date: 2015-04-29 +category: info +ipr: trust200902 + +author: + - + ins: R. Barnes + name: Richard Barnes + email: rlb@ipv.sx + - + ins: B. Schneier + name: Bruce Schneier + email: schneier@schneier.com + - + ins: C. Jennings + name: Cullen Jennings + email: fluffy@cisco.com + - + ins: T. Hardie + name: Ted Hardie + email: ted.ietf@gmail.com + - + ins: B. Trammell + name: Brian Trammell + email: ietf@trammell.ch + - + ins: C. Huitema + name: Christian Huitema + email: huitema@huitema.net + - + ins: D. Borkmann + name: Daniel Borkmann + email: dborkman@iogearbox.net + +normative: + RFC6973: + +informative: + pass1: + target: http://www.theguardian.com/world/2013/jun/27/nsa-online-metadata-collection + title: "How the NSA is still harvesting your online data" + author: + organization: The Guardian + date: 2013 + pass2: + target: http://www.theguardian.com/world/2013/jun/08/nsa-prism-server-collection-facebook-google + title: "NSA's Prism surveillance program: how it works and what it can do" + author: + organization: The Guardian + date: 2013 + pass3: + target: http://www.theguardian.com/world/2013/jul/31/nsa-top-secret-program-online-data + title: "XKeyscore: NSA tool collects 'nearly everything a user does on the internet'" + author: + organization: The Guardian + date: 2013 + pass4: + target: http://www.theguardian.com/uk/2013/jun/21/how-does-gchq-internet-surveillance-work + title: "How does GCHQ's internet surveillance work?" + author: + organization: The Guardian + dec1: + target: http://www.nytimes.com/2013/09/06/us/nsa-foils-much-internet-encryption.html + title: "N.S.A. Able to Foil Basic Safeguards of Privacy on Web" + author: + organization: The New York Times + date: 2013 + dec2: + target: http://www.theguardian.com/world/interactive/2013/sep/05/nsa-project-bullrun-classification-guide + title: "Project Bullrun – classification guide to the NSA's decryption program" + author: + organization: The Guardian + date: 2013 + dec3: + target: http://www.theguardian.com/world/2013/sep/05/nsa-gchq-encryption-codes-security + title: "Revealed: how US and UK spy agencies defeat internet privacy and security" + author: + organization: The Guardian + date: 2013 + TOR: + target: https://www.torproject.org/ + title: "Tor" + author: + organization: The Tor Project + date: 2013 + TOR1: + target: https://www.schneier.com/blog/archives/2013/10/how_the_nsa_att.html + title: "How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID" + author: + name: Bruce Schneier + ins: B. Schneier + date: 2013 + TOR2: + target: http://www.theguardian.com/world/interactive/2013/oct/04/tor-stinks-nsa-presentation-document + title: "'Tor Stinks' presentation – read the full document" + author: + organization: The Guardian + date: 2013 + dir1: + target: http://www.theguardian.com/world/2013/jun/06/nsa-phone-records-verizon-court-order + title: "NSA collecting phone records of millions of Verizon customers daily" + author: + organization: The Guardian + date: 2013 + dir2: + target: http://www.theguardian.com/world/2013/jun/06/us-tech-giants-nsa-data + title: "NSA Prism program taps in to user data of Apple, Google and others" + author: + organization: The Guardian + date: 2013 + dir3: + target: http://www.theguardian.com/world/interactive/2013/sep/05/sigint-nsa-collaborates-technology-companies + title: "Sigint – how the NSA collaborates with technology companies" + author: + organization: The Guardian + date: 2013 + secure: + target: http://www.theguardian.com/world/2013/sep/05/nsa-how-to-remain-secure-surveillance + title: "NSA surveillance: A guide to staying secure" + author: + name: Bruce Schneier + ins: B. Schneier + organization: The Guardian + date: 2013 + snowden: + target: http://www.technologyreview.com/news/519171/nsa-leak-leaves-crypto-math-intact-but-highlights-known-workarounds/ + title: "NSA Leak Leaves Crypto-Math Intact but Highlights Known Workarounds" + author: + organization: Technology Review + date: 2013 + spiegel1: + target: http://www.spiegel.de/international/world/nsa-secret-toolbox-ant-unit-offers-spy-gadgets-for-every-need-a-941006.html + title: "NSA's Secret Toolbox: Unit Offers Spy Gadgets for Every Need" + author: + ins: J Applebaum + name: Jacob Applebaum + author: + ins: J Horchert + name: Judith Horchert + author: + ins: O Reissmann + name: Ole Reissmann + author: + ins: M Rosenbach + name: Marcel Rosenbach + author: + ins: J Schindler + name: Jorg Schindler + author: + ins: C Stocker + name: Christian Stocker + date: 2013-12-30 + spiegel3: + target: http://www.spiegel.de/international/world/new-snowden-docs-indicate-scope-of-nsa-preparations-for-cyber-battle-a-1013409.html + title: "The Digital Arms Race: NSA Preps America for Future Battle" + author: + ins: J Appelbaum + name: Jacob Appelbaum + author: + ins: A Gibson + name: Aaron Gibson + author: + ins: C Guarnieri + name: Claudio Guarnieri + author: + ins: A Muller-Maguhn + name: Andy Muller-Maguhn + author: + ins: M Sontheimer + name: Michael Sontheimer + author: + ins: L Poitras + name: Laura Poitras + author: + ins: M Rosenbach + name: Marcel Rosenbach + author: + ins: L Ryge + name: Leif Ryge + author: + ins: H Schmundt + name: Hilmar Schmundt + date: 2014-01-17 + key-recovery: + target: http://crypto.stanford.edu/~pgolle/papers/escrow.pdf + title: The Design and Implementation of Protocol-Based Hidden Key Recovery + author: + ins: E.-J. Goh + name: Eu-Jin Goh + author: + ins: D. Boneh + name: Dan Boneh + author: + ins: B. Pinkas + name: Benny Pinkas + author: + ins: P. Golle + name: Phillippe Golle + date: 2003 + great-cannon: + target: https://citizenlab.org/2015/04/chinas-great-cannon/ + title: "China's Great Cannon" + author: + name: Bill Marczak + ins: B. Marczak + author: + name: Nicholas Weaver + ins: N. Weaver + author: + name: Jakub Dalek + ins: J. Dalek + author: + name: Roya Ensafi + ins: R. Ensafi + author: + name: David Fifield + ins: D. Fifield + author: + name: Sarah McKune + ins: S. McKune + author: + name: Arn Rey + ins: A. Rey + author: + name: John Scott-Railton + ins: J. Scott-Railton + author: + name: Ronald Deibert + ins: R. Deibert + author: + name: Vern Paxson + ins: V. Paxson + date: 2015 + RFC1035: + RFC1918: + RFC1939: + RFC2015: + RFC2821: + RFC3261: + RFC3365: + RFC3501: + RFC3851: + RFC4033: + RFC4301: + RFC4303: + RFC4306: + RFC4949: + RFC5246: + RFC5321: + RFC5655: + RFC5750: + RFC6120: + RFC6962: + RFC6698: + RFC7011: + RFC7258: + I-D.ietf-dprive-problem-statement: + +--- abstract + + Since the initial revelations of pervasive surveillance in 2013, + several classes of attacks on Internet communications have been + discovered. In this document we develop a threat model that + describes these attacks on Internet confidentiality. We assume an + attacker that is interested in undetected, indiscriminate + eavesdropping. The threat model is based on published, verified + attacks. + + +--- middle + +# Introduction + +Starting in June 2013, documents released to the press by Edward +Snowden have revealed several operations undertaken by intelligence +agencies to exploit Internet communications for intelligence purposes. +These attacks were largely based on protocol vulnerabilities that were +already known to exist. The attacks were nonetheless striking in +their pervasive nature, both in terms of the amount of Internet +communications targeted, and in terms of the diversity of attack +techniques employed. + +To ensure that the Internet can be trusted by users, it is necessary +for the Internet technical community to address the vulnerabilities +exploited in these attacks {{RFC7258}}. The goal of this document is +to describe more precisely the threats posed by these pervasive +attacks, and based on those threats, lay out the problems that need to +be solved in order to secure the Internet in the face of those +threats. + +The remainder of this document is structured as follows. In +{{adversary}}, we describe an idealized passive pervasive attacker, one which +could completely undetectably compromise communications at Internet +scale. In {{reported}}, we provide a brief summary of some attacks +that have been disclosed, and use these to expand the assumed +capabilities of our idealized attacker. Note that we do not attempt +to describe all possible attacks, but focus on those which result in +undetected eavesdropping. {{model}} describes a threat model based on +these attacks, focusing on classes of attack that have not been a +focus of Internet engineering to date. + +# Terminology {#terminology} + +This document makes extensive use of standard security and privacy +terminology; see {{RFC4949}} and {{RFC6973}}. Terms used from +{{RFC6973}} include Eavesdropper, Observer, Initiator, Intermediary, +Recipient, Attack (in a privacy context), Correlation, Fingerprint, +Traffic Analysis, and Identifiability (and related terms). In +addition, we use a few terms that are specific to the attacks +discussed in this document. Note especially that "passive" and "active" below +do not refer to the effort used to mount the attack; a "passive attack" +is any attack that accesses a flow but does not modify it, while an +"active attack" is any attack that modifies a flow. Some passive attacks +involve active interception and modifications of devices, rather than simple +access to the medium. The introduced terms are: + +Pervasive Attack: +: An attack on Internet communications that makes +use of access at a large number of points in the network, or otherwise +provides the attacker with access to a large amount of Internet +traffic; see {{RFC7258}}. + +Passive Pervasive Attack: +: An eavesdropping attack undertaken by a pervasive attacker, in which the +packets in a traffic stream between two endpoints are intercepted, but +in which the attacker does not modify the packets in the traffic +stream between two endpoints, modify the treatment of packets in the +traffic stream (e.g. delay, routing), or add or remove packets in the +traffic stream. Passive pervasive attacks are undetectable from the +endpoints. Equivalent to passive wiretapping as defined in {{RFC4949}}; +we use an alternate term here since the methods employed are wider +than those implied by the word "wiretapping", including the active +compromise of intermediate systems. + +Active Pervasive Attack: +: An attack undertaken by a pervasive attacker, which in addition to +the elements of a passive pervasive attack, also includes modification, +addition, or removal of +packets in a traffic stream, or modification of treatment of packets +in the traffic stream. Active pervasive attacks provide more +capabilities to the attacker at the risk of possible detection at the +endpoints. Equivalent to active wiretapping as defined in {{RFC4949}}. + +Observation: +: Information collected directly from communications by an +eavesdropper or observer. For example, the knowledge that +<alice@example.com> sent a message to <bob@example.com> +via SMTP taken from the headers of an observed SMTP message would be +an observation. + +Inference: +: Information extracted from analysis of information collected +directly from communications by an eavesdropper or observer. For +example, the knowledge that a given web page was accessed by a given +IP address, by comparing the size in octets of measured network flow +records to fingerprints derived from known sizes of linked resources +on the web servers involved, would be an inference. + +Collaborator: +: An entity that is a legitimate participant in a communication, but +who deliberately provides information about that interaction to an +attacker. + +Unwitting Collaborator: +: An entity that is a legitimate participant in a communication, and +who is the source of information obtained by the attacker without the +entity's consent or intention, because the attacker has exploited some +technology used by the entity. + +Key Exfiltration: +: The transmission of cryptographic keying material for an encrypted communication +from a collaborator, deliberately or unwittingly, to an attacker. + +Content Exfiltration: +: The transmission of the content of a communication from a collaborator, deliberately or unwittingly, to an attacker + +# An Idealized Passive Pervasive Attacker {#adversary} + +In considering the threat posed by pervasive surveillance, we begin by +defining an idealized passive pervasive attacker. While this attacker +is less capable than those which we now know to have compromised the +Internet from press reports, as elaborated in {{reported}}, it does +set a lower bound on the capabilities of an attacker interested in +indiscriminate passive surveillance while interested in remaining +undetectable. We note that, prior to the Snowden revelations in 2013, +the assumptions of attacker capability presented here would be +considered on the border of paranoia outside the network security +community. + +Our idealized attacker is an indiscriminate eavesdropper on an Internet-attached computer network that: + +- can observe every packet of all communications at any hop in any network path between an initiator and a recipient; +- can observe data at rest in any intermediate system between the endpoints controlled by the initiator and recipient; and +- can share information with other such attackers; but +- takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.). + + The techniques available to our ideal attacker are direct observation + and inference. Direct observation involves taking information + directly from eavesdropped communications, such as URLs identifying + content or email addresses identifying individuals from application- + layer headers. Inference, on the other hand, involves analyzing + observed information to derive new information, such as searching for + application or behavioral fingerprints in observed traffic to derive + information about the observed individual. The use of encryption is + generally sufficient to provide confidentiality by preventing direct + observation of content, assuming of course, uncompromised encryption + implementations and cryptographic keying material. However, + encryption provides less complete protection against inference, + especially inferences based only on plaintext portions of + communications, such as IP and TCP headers for TLS-protected traffic + [RFC5246]). + +## Information subject to direct observation + +Protocols which do not encrypt their payload make the entire content +of the communication available to the idealized attacker along their +path. Following the advice in {{RFC3365}}, most such protocols have a +secure variant which encrypts payload for confidentiality, and these +secure variants are seeing ever-wider deployment. A noteworthy +exception is DNS {{RFC1035}}, as DNSSEC {{RFC4033}} does not have +confidentiality as a requirement. + +This implies that, in the absence of +changes to the protocol as presently under development in the IETF's +DNS Private Exchange (DPRIVE) +working group {{I-D.ietf-dprive-problem-statement}}, all DNS queries and answers generated by the activities +of any protocol are available to the attacker. + +When store-and-forward protocols are used, (e.g. SMTP {{RFC5321}}) +intermediaries leave this data subject to observation by an attacker that +has compromised these intermediaries, +unless the data is encrypted end-to-end by the application layer +protocol, or the implementation uses an encrypted store for this data. + +## Information useful for inference + +Inference is information extracted from later analysis of an observed +or eavesdropped communication, and/or correlation of observed or +eavesdropped information with information available from other +sources. Indeed, most useful inference performed by the attacker falls +under the rubric of correlation. The simplest example of this is the +observation of DNS queries and answers from and to a source and +correlating those with IP addresses with which that source +communicates. This can give access to information otherwise not +available from encrypted application payloads (e.g., the Host: +HTTP/1.1 request header when HTTP is used with TLS). + +Protocols which encrypt their payload using an application- or +transport-layer encryption scheme (e.g. TLS) still expose all the +information in their network and transport layer headers to the +attacker, including source and destination addresses and ports. IPsec +ESP{{RFC4303}} further encrypts the transport-layer headers, but still +leaves IP address information unencrypted; in tunnel mode, these +addresses correspond to the tunnel endpoints. Features of the +security protocols themselves, e.g. the TLS session identifier, +may leak information that can be used for correlation and +inference. While this information is much less semantically rich than +the application payload, it can still be useful for the inferring an +individual's activities. + +Inference can also leverage information obtained from sources other +than direct traffic observation. Geolocation databases, for example, +have been developed that map IP addresses to a location, in order to +provide location-aware services such as targeted advertising. This +location information is often of sufficient resolution that it can be +used to draw further inferences toward identifying or profiling an +individual. + +Social media provide another source of more or less publicly +accessible information. This information can be extremely semantically +rich, including information about an individual's location, +associations with other individuals and groups, and +activities. Further, this information is generally contributed and +curated voluntarily by the individuals themselves: it represents +information which the individuals are not necessarily interested in +protecting for privacy reasons. However, correlation of this social +networking data with information available from direct observation of +network traffic allows the creation of a much richer picture of an +individual's activities than either alone. + +We note with some alarm that there is little that can be done at +protocol design time to limit such correlation by the attacker, and +that the existence of such data sources in many cases greatly +complicates the problem of protecting privacy by hardening protocols +alone. + +## An illustration of an ideal passive pervasive attack + +To illustrate how capable the idealized attacker is even given its +limitations, we explore the non-anonymity of encrypted IP traffic in +this section. Here we examine in detail some inference techniques for +associating a set of addresses with an individual, in order to +illustrate the difficulty of defending communications against our +idealized attacker. Here, the basic problem is that information +radiated even from protocols which have no obvious connection with +personal data can be correlated with other information which can paint +a very rich behavioral picture, that only takes one unprotected link +in the chain to associate with an identity. + +### Analysis of IP headers + +Internet traffic can be monitored by tapping Internet links, or by +installing monitoring tools in Internet routers. Of course, a single +link or a single router only provides access to a fraction of the +global Internet traffic. However, monitoring a number of high capacity +links or a set of routers placed at strategic locations provides +access to a good sampling of Internet traffic. + +Tools like IPFIX {{RFC7011}} allow administrators to acquire +statistics about sequences of packets with some common properties that +pass through a network device. The most common set of properties used +in flow measurement is the "five-tuple"of source and destination +addresses, protocol type, and source and destination ports. These +statistics are commonly used for network engineering, but could +certainly be used for other purposes. + +Let's assume for a moment that IP addresses can be correlated to +specific services or specific users. Analysis of the sequences of +packets will quickly reveal which users use what services, and also +which users engage in peer-to-peer connections with other +users. Analysis of traffic variations over time can be used to detect +increased activity by particular users, or in the case of peer-to-peer +connections increased activity within groups of users. + +### Correlation of IP addresses to user identities + +The correlation of IP addresses with specific users can be done in +various ways. For example, tools like reverse DNS lookup can be used +to retrieve the DNS names of servers. Since the addresses of servers +tend to be quite stable and since servers are relatively less numerous +than users, an attacker could easily maintain its own copy of the DNS +for well-known or popular servers, to accelerate such lookups. + +On the other hand, the reverse lookup of IP addresses of users is +generally less informative. For example, a lookup of the address +currently used by one author's home network returns a name of the form +"c-192-000-002-033.hsd1.wa.comcast.net". This particular type of +reverse DNS lookup generally reveals only coarse-grained location or +provider information, equivalent to that available from geolocation +databases. + +In many jurisdictions, Internet Service Providers (ISPs) are required +to provide identification on a case by case basis of the "owner" of a +specific IP address for law enforcement purposes. This is a reasonably +expedient process for targeted investigations, but pervasive +surveillance requires something more efficient. This provides an +incentive for the attacker to secure the cooperation of the ISP in +order to automate this correlation. + +### Monitoring messaging clients for IP address correlation + +Even if the ISP does not cooperate, user identity can often be +obtained via inference. POP3 {{RFC1939}} and IMAP {{RFC3501}} are used +to retrieve mail from mail servers, while a variant of SMTP is used to +submit messages through mail servers. IMAP connections originate from +the client, and typically start with an authentication exchange in +which the client proves its identity by answering a password +challenge. The same holds for the SIP protocol {{RFC3261}} and many +instant messaging services operating over the Internet using +proprietary protocols. + +The username is directly observable if any of these protocols operate +in cleartext; the username can then be directly associated with the +source address. + +### Retrieving IP addresses from mail headers + +SMTP {{RFC5321}} requires that each successive SMTP relay adds a +"Received" header to the mail headers. The purpose of these headers is +to enable audit of mail transmission, and perhaps to distinguish +between regular mail and spam. Here is an extract from the headers of +a message recently received from the "perpass" mailing list: + +``` + Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?) + (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA + (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100 + Message-ID: <526D7BD2.7070908@example.org> + Date: Sun, 27 Oct 2013 20:47:14 +0000 + From: Some One +``` + +This is the first "Received" header attached to the message by the +first SMTP relay; for privacy reasons, the field values have been +anonymized. We learn here that the message was submitted by "Some One" +on October 27, from a host behind a NAT (192.168.1.100) {{RFC1918}} +that used the IP address 192.0.2.44. The information remained in the +message, and is accessible by all recipients of the "perpass" mailing +list, or indeed by any attacker that sees at least one copy of the +message. + +An attacker that can observe sufficient email traffic can regularly +update the mapping between public IP addresses and individual email +identities. Even if the SMTP traffic was encrypted on submission and +relaying, the attacker can still receive a copy of public mailing +lists like "perpass". + +### Tracking address usage with web cookies + +Many web sites only encrypt a small fraction of their transactions. A +popular pattern is to use HTTPS for the login information, and then +use a "cookie" to associate following clear-text transactions with the +user's identity. Cookies are also used by various advertisement +services to quickly identify the users and serve them with +"personalized" advertisements. Such cookies are particularly useful if +the advertisement services want to keep tracking the user across +multiple sessions that may use different IP addresses. + +As cookies are sent in clear text, an attacker can build a database +that associates cookies to IP addresses for non-HTTPS traffic. If the +IP address is already identified, the cookie can be linked to the user +identify. After that, if the same cookie appears on a new IP address, +the new IP address can be immediately associated with the +pre-determined identity. + +### Graph-based approaches to address correlation + +An attacker can track traffic from an IP address not yet associated +with an individual to various public services (e.g. websites, mail +servers, game servers), and exploit patterns in the observed traffic +to correlate this address with other addresses that show similar +patterns. For example, any two addresses that show connections to the +same IMAP or webmail services, the same set of favorite websites, and +game servers at similar times of day may be associated with the same +individual. Correlated addresses can then be tied to an individual +through one of the techniques above, walking the "network graph" to +expand the set of attributable traffic. + +### Tracking of Link Layer Identifiers + +Moving back down the stack, technologies like Ethernet or Wi-Fi use MAC Addresses to identify link-level destinations. MAC Addresses assigned according to IEEE-802 standards are globally-unique identifiers for the device. If the link is publicly accessible, an attacker can eavesdrop and perform tracking. For example, the attacker can track the wireless traffic at publicly accessible Wi-Fi networks. Simple devices can monitor the traffic, and reveal which MAC Addresses are present. +Also, devices do not need to be connected to a network to expose link-layer identifiers. Active service discovery always discloses the MAC address of the user, and sometimes the SSIDs of previously visited networks. For instance, certain techniques such as the use of “hidden SSIDs” require the mobile device to broadcast the network identifier together with the device identifier. This combination can further expose the user to inference attacks, as more information can be derived from the combination of MAC address, SSID being probed, time and current location. For example, a user actively probing for a semi-unique SSID on a flight out of a certain city can imply that the user is no longer at the physical location of the corresponding AP. +Given that large-scale databases of the MAC addresses of wireless access points for geolocation purposes have been known to exist for some time, the attacker could easily build a database linking link-layer identifiers, time and device or user identities, and use it to track the movement of devices and of their owners. +On the other hand, if the network does not use some form of Wi-Fi encryption, or if the attacker can access the decrypted traffic, the analysis will also provide the correlation between link-layer identifiers such as MAC Addresses and IP addresses. Additional monitoring using techniques exposed in the previous sections will reveal the correlation between MAC addresses, IP addresses, and user identity. For instance, similarly to the use of web cookies, MAC addresses provide identity information that can be used to associate a user to different IP addresses. + +# Reported Instances of Large-Scale Attacks {#reported} + +The situation in reality is more bleak than that suggested by an +analysis of our idealized attacker. Through revelations of sensitive +documents in several media outlets, the Internet community has been +made aware of several intelligence activities conducted by US and UK +national intelligence agencies, particularly the US National Security +Agency (NSA) and the UK Government Communications Headquarters +(GCHQ). These documents have revealed methods that these agencies use +to attack Internet applications and obtain sensitive user information. +We note that these reports are primarily useful as an illustration of +the types of capabilities fielded by pervasive attackers as of the +date of the Snowden leaks in 2013. + +First, they confirm the deployment of large-scale passive +collection of Internet traffic, which confirms the existence of +pervasive passive attackers with at least the capabilities of our +idealized attacker. For example {{pass1}}{{pass2}}{{pass3}}{{pass4}}: + +- NSA's XKEYSCORE system accesses data from multiple access points and +searches for "selectors" such as email addresses, at the scale of tens +of terabytes of data per day. + +- GCHQ's Tempora system appears to have access to around 1,500 major cables +passing through the UK. + +- NSA's MUSCULAR program has tapped cables between data centers +belonging to major service providers. + +- Several programs appear to perform wide-scale collection +of cookies in web traffic and location data from location-aware +portable devices such as smartphones. + +However, the capabilities described by these reports go beyond those of our +idealized attacker. They include the compromise of cryptographic protocols, +including decryption of TLS-protected Internet sessions {{dec1}}{{dec2}}{{dec3}}. +For example, the NSA BULLRUN project worked to undermine encryption through +multiple approaches, including covert modifications to cryptographic +software on end systems. + +Reported capabilities include the direct compromise of intermediate systems +and arrangements with service providers for bulk data and metadata +access {{dir1}}{{dir2}}{{dir3}}, bypassing the need to capture +traffic on the wire. For example, the NSA PRISM program provides the +agency with access to many types of user data (e.g., email, chat, VoIP). + +The reported capabilities also include elements of active pervasive attack, +including: + +* Insertion of devices as a man-in-the-middle of Internet + transactions {{TOR1}}{{TOR2}}. For example, NSA's QUANTUM system + appears to use several different techniques to hijack HTTP + connections, ranging from DNS response injection to HTTP 302 + redirects. + +* Use of implants on end systems to undermine security and anonymity + features {{dec2}}{{TOR1}}{{TOR2}}. For example, QUANTUM is used to + direct users to a FOXACID server, which in turn delivers an implant + to compromise browsers of Tor users. + +* Use of implants on network elements from many major equipment providers, + including Cisco, Juniper, Huawei, Dell, and HP, as provided by the NSA's + Advanced Network Technology group. {{spiegel1}} + +* Use of botnet-scale collections of compromised hosts {{spiegel3}}. + +The scale of the compromise extends beyond the network to include subversion of the technical standards process itself. For example, there is suspicion that NSA modifications to the DUAL_EC_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA. This RNG was made part of NIST's SP 800-90A, for which NIST acknowledges NSA's assistance. There have also been reports that the NSA paid RSA Security for a related contract with the result that the curve became the default in the RSA BSAFE product line. + +We use the term "pervasive attack" {{RFC7258}} to collectively +describe these operations. The term "pervasive" is used because the +attacks are designed to indiscriminately gather as much data as +possible and to apply selective analysis on targets after the fact. +This means that all, or nearly all, Internet communications are +targets for these attacks. To achieve this scale, the attacks are +physically pervasive; they affect a large number of Internet +communications. They are pervasive in content, consuming and +exploiting any information revealed by the protocol. And they are +pervasive in technology, exploiting many different vulnerabilities in +many different protocols. + +It's important to note that although the attacks mentioned above were +executed by NSA and GCHQ, there are many other organizations that can +mount pervasive surveillance attacks. Because of the resources +required to achieve pervasive scale, these attacks are most commonly +undertaken by nation-state actors. For example, the Chinese Internet +filtering system known as the "Great Firewall of China" uses several +techniques that are similar to the QUANTUM program, and which have a +high degree of pervasiveness with regard to the Internet in China. + +# Threat Model {#model} + +Given these disclosures, we must consider a broader threat model. + +Pervasive surveillance aims to collect information across a large +number of Internet communications, analyzing the collected +communications to identify information of interest within individual +communications, or inferring information from correlated +communications. This analysis sometimes benefits from decryption of +encrypted communications and deanonymization of anonymized +communications. As a result, these attackers desire both access to +the bulk of Internet traffic and to the keying material required to +decrypt any traffic that has been encrypted. Even if keys are not +available, note that the presence of a communication and the fact that +it is encrypted may both be inputs to an analysis, even if the +attacker cannot decrypt the communication. + +The attacks listed above highlight new avenues both for access to +traffic and for access to relevant encryption keys. They further +indicate that the scale of surveillance is sufficient to provide a +general capability to cross-correlate communications, a threat not +previously thought to be relevant at the scale of the Internet. + +## Attacker Capabilities + +| Attack Class | Capability | +|:--------------------------|:------------------------------------------| +| Passive observation | Directly capture data in transit | +| Passive inference | Infer from reduced/encrypted data | +| Active | Manipulate / inject data in transit | +| Static key exfiltration | Obtain key material once / rarely | +| Dynamic key exfiltration | Obtain per-session key material | +| Content exfiltration | Access data at rest | + +Security analyses of Internet protocols commonly consider two classes +of attacker: Passive pervasive attackers, who can simply listen in on +communications as they transit the network, and active pervasive +attackers, who can modify or delete packets in addition to simply +collecting them. + +In the context of pervasive passive surveillance, these attacks take +on an even greater significance. In the past, these attackers were +often assumed to operate near the edge of the network, where attacks +can be simpler. For example, in some LANs, it is simple for any node +to engage in passive listening to other nodes' traffic or inject +packets to accomplish active pervasive attacks. However, as we now +know, both passive and active pervasive attacks are undertaken by +pervasive attackers closer to the core of the network, greatly +expanding the scope and capability of the attacker. + +Eavesdropping and observation at a larger scale make passive inference +attacks easier to carry out: a passive pervasive attacker with access to a +large portion of the Internet can analyze collected traffic to create +a much more detailed view of individual behavior than an attacker that +collects at a single point. Even the usual claim that encryption +defeats passive pervasive attackers is weakened, since a pervasive flow +access attacker can infer relationships from correlations over large +numbers of sessions, e.g., pairing encrypted sessions with unencrypted +sessions from the same host, or performing traffic fingerprinting +between known and unknown encrypted sessions. Reports on the NSA +XKEYSCORE system would indicate it is an example of such an attacker. + +An active pervasive attacker likewise has capabilities +beyond those of a localized active attacker. Flow +modification attacks are often limited by network topology, for +example by a requirement that the attacker be able to see a targeted +session as well as inject packets into it. A pervasive flow +modification attacker with access at multiple points within the core +of the Internet is able to overcome these topological limitations and +perform attacks over a much broader scope. Being positioned in the +core of the network rather than the edge can also enable an active +pervasive attacker to reroute targeted traffic, amplifying the +ability to perform both eavesdropping and traffic injection. +Active pervasive attackers can also benefit from passive pervasive +collection to identify vulnerable hosts. + +While not directly related to pervasiveness, attackers that are in a +position to mount a active pervasive attack are also often +in a position to subvert authentication, a traditional protection +against such attacks. Authentication in the Internet is often +achieved via trusted third party authorities such as the Certificate +Authorities (CAs) that provide web sites with authentication +credentials. An attacker with sufficient resources may also be able to +induce an authority to grant credentials for an identity of the +attacker’s choosing. If the parties to a communication will trust +multiple authorities to certify a specific identity, this attack may +be mounted by suborning any one of the authorities (the proverbial +"weakest link"). Subversion of authorities in this way can allow an +active attack to succeed in spite of an authentication +check. + +Beyond these three classes (observation, inference, and active), +reports on the BULLRUN effort to defeat encryption and the PRISM +effort to obtain data from service providers suggest three more +classes of attack: + +* Static key exfiltration +* Dynamic key exfiltration +* Content exfiltration + +These attacks all rely on a collaborator providing the attacker with +some information, either keys or data. These attacks have not +traditionally been considered in scope for the Security Considerations +sections of IETF protocols, as they occur outside the protocol. + +The term "key exfiltration" refers to the transfer of keying material +for an encrypted communication from the collaborator to the attacker. +By "static", we mean that the transfer of keys happens once, or +rarely, typically of a long-lived key. For example, this case would +cover a web site operator that provides the private key corresponding +to its HTTPS certificate to an intelligence agency. + +"Dynamic" key exfiltration, by contrast, refers to attacks in which +the collaborator delivers keying material to the attacker frequently, +e.g., on a per-session basis. This does not necessarily imply +frequent communications with the attacker; the transfer of keying +material may be virtual. For example, if an endpoint were modified in +such a way that the attacker could predict the state of its +psuedorandom number generator, then the attacker would be able to +derive per-session keys even without per-session communications. + +Finally, content exfiltration is the attack in which the collaborator +simply provides the attacker with the desired data or metadata. Unlike +the key exfiltration cases, this attack does not require the attacker +to capture the desired data as it flows through the network. The exfiltration +is of data at rest, rather than data in transit. This increases the scope of data +that the attacker can obtain, since the attacker can access historical +data -- the attacker does not have to be listening +at the time the communication happens. + +Exfiltration attacks can be accomplished via attacks against one of +the parties to a communication, i.e., by the attacker stealing the +keys or content rather than the party providing them willingly. In +these cases, the party may not be aware that they are collaborating, +at least at a human level. Rather, the subverted technical assets are +"collaborating" with the attacker (by providing keys/content) without +their owner's knowledge or consent. + +Any party that has access to encryption keys or unencrypted data can +be a collaborator. While collaborators are typically the endpoints of +a communication (with encryption securing the links), intermediaries +in an unencrypted communication can also facilitate content +exfiltration attacks as collaborators by providing the attacker access +to those communications. For example, documents describing the NSA +PRISM program claim that NSA is able to access user data directly from +servers, where it is stored unencrypted. In these cases, the operator +of the server would be a collaborator, if an unwitting one. By +contrast, in the NSA MUSCULAR program, a set of collaborators enabled +attackers to access the cables connecting data centers used by service +providers such as Google and Yahoo. Because communications among +these data centers were not encrypted, the collaboration by an +intermediate entity allowed NSA to collect unencrypted user data. + +## Attacker Costs + +| Attack Class | Cost / Risk to Attacker | +|:--------------------------|:----------------------------------| +| Passive observation | Passive data access | +| Passive inference | Passive data access + processing | +| Active | Active data access + processing | +| Static key exfiltration | One-time interaction | +| Dynamic key exfiltration | Ongoing interaction / code change | +| Content exfiltration | Ongoing, bulk interaction | + +Each of the attack types discussed in the previous section entails +certain costs and risks. These costs differ by attack, and can be +helpful in guiding response to pervasive attack. + +Depending on the attack, the attacker may be exposed to several types +of risk, ranging from simply losing access to arrest or prosecution. +In order for any of these negative consequences to occur, however, the +attacker must first be discovered and identified. So the primary risk +we focus on here is the risk of discovery and attribution. + +A passive pervasive attack is the simplest to mount in some ways. The base +requirement is that the attacker obtain physical access to a +communications medium and extract communications from it. For +example, the attacker might tap a fiber-optic cable, acquire a mirror +port on a switch, or listen to a wireless signal. The need for these +taps to have physical access or proximity to a link exposes the +attacker to the risk that the taps will be discovered. For example, a +fiber tap or mirror port might be discovered by network operators +noticing increased attenuation in the fiber or a change in switch +configuration. Of course, passive pervasive attacks may be accomplished +with the cooperation of the network operator, in which case there is a +risk that the attacker's interactions with the network operator will +be exposed. + +In many ways, the costs and risks for an active pervasive attack are +similar to those for a passive pervasive attack, with a few additions. An +active attacker requires more robust network access than a +passive attacker, since for example they will often need to +transmit data as well as receiving it. In the wireless example above, +the attacker would need to act as an transmitter as well as receiver, +greatly increasing the probability the attacker will be discovered +(e.g., using direction-finding technology). Active attacks +are also much more observable at higher layers of the network. For +example, an active attacker that attempts to use a +mis-issued certificate could be detected via Certificate Transparency +{{RFC6962}}. + +In terms of raw implementation complexity, passive pervasive attacks require +only enough processing to extract information from the network and +store it. Active pervasive attacks, by contrast, often depend on +winning race conditions to inject packets into active connections. So +active pervasive attacks in the core of the network require +processing hardware to that can operate at line speed (roughly 100Gbps +to 1Tbps in the core) to identify opportunities for attack and insert +attack traffic in a high-volume traffic. Key exfiltration attacks +rely on passive pervasive attack for access to encrypted data, with the +collaborator providing keys to decrypt the data. So the attacker +undertakes the cost and risk of a passive pervasive attack, as well as +additional risk of discovery via the interactions that the attacker +has with the collaborator. + +Some active attacks are more expensive than others. For example, +active man-in-the-middle (MITM) attacks require access to the entire +network session and path in order to intercept and potentially modify, +as well as drop, legitimate packets in favor of the attacker's +packets. A similar but weaker form of attack, called an active +man-on-the-side (MOTS), does not require access to the entire session +and only part of the path. In an active MOTS attack, the attacker need +only be able to inject or modify traffic on the network element the +attacker has access to. While this may not allow for full control of a +communication session (as in an MITM attack), the attacker can perform +a number of powerful attacks, including but not limited to: injecting +packets that could terminate the session (e.g., TCP RST packets), +sending a fake DNS reply to redirect ensuing TCP connections to an +address of the attacker's choice (i.e., winning a "DNS response +race"), and mounting an HTTP Redirect attack by observing a TCP/HTTP +connection to a target address and injecting a TCP data packet +containing an HTTP redirect. For example, the system dubbed by +researchers as China's "Great Cannon" {{great-cannon}} can operate in +ful MITM mode to accomplish very complex attacks that can modify +content in transit while the well-known Great Firewall of China is a +MOTS system that focuses on blocking access to certain kinds of +traffic and destinations via TCP RST packet injection. + +In this sense, static exfiltration has a lower risk profile than +dynamic. In the static case, the attacker need only interact with the +collaborator a small number of times, possibly only once, say to +exchange a private key. In the dynamic case, the attacker must have +continuing interactions with the collaborator. As noted above these +interactions may be real, such as in-person meetings, or virtual, such as +software modifications that render keys available to the attacker. +Both of these types of interactions introduce a risk that they will be +discovered, e.g., by employees of the collaborator organization +noticing suspicious meetings or suspicious code changes. + +Content exfiltration has a similar risk profile to dynamic key +exfiltration. In a content exfiltration attack, the attacker saves +the cost and risk of conducting a passive pervasive attack. The risk of +discovery through interactions with the collaborator, however, is +still present, and may be higher. The content of a communication is +obviously larger than the key used to encrypt it, often by several +orders of magnitude. So in the content exfiltration case, the +interactions between the collaborator and the attacker need to be much +higher-bandwidth than in the key exfiltration cases, with a +corresponding increase in the risk that this high-bandwidth channel +will be discovered. + +It should also be noted that in these latter three exfiltration cases, +the collaborator also undertakes a risk that his collaboration with +the attacker will be discovered. Thus the attacker may have to incur +additional cost in order to convince the collaborator to participate +in the attack. Likewise, the scope of these attacks is limited to +case where the attacker can convince a collaborator to participate. +If the attacker is a national government, for example, it may be able +to compel participation within its borders, but have a much more +difficult time recruiting foreign collaborators. + +As noted above, the collaborator in an exfiltration attack can be +unwitting; the attacker can steal keys or data to enable the attack. +In some ways, the risks of this approach are similar to the case of an +active collaborator. In the static case, the attacker needs to steal +information from the collaborator once; in the dynamic case, the +attacker needs to continued presence inside the collaborators systems. +The main difference is that the risk in this case is of automated +discovery (e.g., by intrusion detection systems) rather than discovery +by humans. + +# Security Considerations + +This document describes a threat model for pervasive surveillance +attacks. Mitigations are to be given in a future document. + +# IANA Considerations + +This document has no actions for IANA. + +# Acknowledgements + +Thanks to Dave Thaler for the list of attacks and taxonomy; to +Security Area Directors Stephen Farrell, Sean Turner, and Kathleen +Moriarty for starting and managing the IETF's discussion on pervasive +attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, Evangelos +Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, Russ Housley, and the IAB +Privacy and Security Program for their input. diff --git a/draft-iab-privsec-confidentiality-threat-05.pdf b/draft-iab-privsec-confidentiality-threat-05.pdf new file mode 100644 index 0000000..a5145ec Binary files /dev/null and b/draft-iab-privsec-confidentiality-threat-05.pdf differ diff --git a/draft-iab-privsec-confidentiality-threat-05.txt b/draft-iab-privsec-confidentiality-threat-05.txt new file mode 100644 index 0000000..f35eb6a --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-05.txt @@ -0,0 +1,1344 @@ + + + + +Network Working Group R. Barnes +Internet-Draft +Intended status: Informational B. Schneier +Expires: October 31, 2015 + C. Jennings + + T. Hardie + + B. Trammell + + C. Huitema + + D. Borkmann + April 29, 2015 + + + Confidentiality in the Face of Pervasive Surveillance: A Threat Model + and Problem Statement + draft-iab-privsec-confidentiality-threat-05 + +Abstract + + Since the initial revelations of pervasive surveillance in 2013, + several classes of attacks on Internet communications have been + discovered. In this document we develop a threat model that + describes these attacks on Internet confidentiality. We assume an + attacker that is interested in undetected, indiscriminate + eavesdropping. The threat model is based on published, verified + attacks. + +Status of This Memo + + This Internet-Draft is submitted in full conformance with the + provisions of BCP 78 and BCP 79. + + Internet-Drafts are working documents of the Internet Engineering + Task Force (IETF). Note that other groups may also distribute + working documents as Internet-Drafts. The list of current Internet- + Drafts is at http://datatracker.ietf.org/drafts/current/. + + Internet-Drafts are draft documents valid for a maximum of six months + and may be updated, replaced, or obsoleted by other documents at any + time. It is inappropriate to use Internet-Drafts as reference + material or to cite them other than as "work in progress." + + This Internet-Draft will expire on October 31, 2015. + + + + + +Barnes, et al. Expires October 31, 2015 [Page 1] + +Internet-Draft Confidentiality Threat Model April 2015 + + +Copyright Notice + + Copyright (c) 2015 IETF Trust and the persons identified as the + document authors. All rights reserved. + + This document is subject to BCP 78 and the IETF Trust's Legal + Provisions Relating to IETF Documents + (http://trustee.ietf.org/license-info) in effect on the date of + publication of this document. Please review these documents + carefully, as they describe your rights and restrictions with respect + to this document. Code Components extracted from this document must + include Simplified BSD License text as described in Section 4.e of + the Trust Legal Provisions and are provided without warranty as + described in the Simplified BSD License. + +1. Introduction + + Starting in June 2013, documents released to the press by Edward + Snowden have revealed several operations undertaken by intelligence + agencies to exploit Internet communications for intelligence + purposes. These attacks were largely based on protocol + vulnerabilities that were already known to exist. The attacks were + nonetheless striking in their pervasive nature, both in terms of the + amount of Internet communications targeted, and in terms of the + diversity of attack techniques employed. + + To ensure that the Internet can be trusted by users, it is necessary + for the Internet technical community to address the vulnerabilities + exploited in these attacks [RFC7258]. The goal of this document is + to describe more precisely the threats posed by these pervasive + attacks, and based on those threats, lay out the problems that need + to be solved in order to secure the Internet in the face of those + threats. + + The remainder of this document is structured as follows. In + Section 3, we describe an idealized passive pervasive attacker, one + which could completely undetectably compromise communications at + Internet scale. In Section 4, we provide a brief summary of some + attacks that have been disclosed, and use these to expand the assumed + capabilities of our idealized attacker. Note that we do not attempt + to describe all possible attacks, but focus on those which result in + undetected eavesdropping. Section 5 describes a threat model based + on these attacks, focusing on classes of attack that have not been a + focus of Internet engineering to date. + + + + + + + +Barnes, et al. Expires October 31, 2015 [Page 2] + +Internet-Draft Confidentiality Threat Model April 2015 + + +2. Terminology + + This document makes extensive use of standard security and privacy + terminology; see [RFC4949] and [RFC6973]. Terms used from [RFC6973] + include Eavesdropper, Observer, Initiator, Intermediary, Recipient, + Attack (in a privacy context), Correlation, Fingerprint, Traffic + Analysis, and Identifiability (and related terms). In addition, we + use a few terms that are specific to the attacks discussed in this + document. Note especially that "passive" and "active" below do not + refer to the effort used to mount the attack; a "passive attack" is + any attack that accesses a flow but does not modify it, while an + "active attack" is any attack that modifies a flow. Some passive + attacks involve active interception and modifications of devices, + rather than simple access to the medium. The introduced terms are: + + Pervasive Attack: An attack on Internet communications that makes + use of access at a large number of points in the network, or + otherwise provides the attacker with access to a large amount of + Internet traffic; see [RFC7258]. + + Passive Pervasive Attack: An eavesdropping attack undertaken by a + pervasive attacker, in which the packets in a traffic stream + between two endpoints are intercepted, but in which the attacker + does not modify the packets in the traffic stream between two + endpoints, modify the treatment of packets in the traffic stream + (e.g. delay, routing), or add or remove packets in the traffic + stream. Passive pervasive attacks are undetectable from the + endpoints. Equivalent to passive wiretapping as defined in + [RFC4949]; we use an alternate term here since the methods + employed are wider than those implied by the word "wiretapping", + including the active compromise of intermediate systems. + + Active Pervasive Attack: An attack undertaken by a pervasive + attacker, which in addition to the elements of a passive pervasive + attack, also includes modification, addition, or removal of + packets in a traffic stream, or modification of treatment of + packets in the traffic stream. Active pervasive attacks provide + more capabilities to the attacker at the risk of possible + detection at the endpoints. Equivalent to active wiretapping as + defined in [RFC4949]. + + Observation: Information collected directly from communications by + an eavesdropper or observer. For example, the knowledge that + sent a message to via SMTP + taken from the headers of an observed SMTP message would be an + observation. + + + + + +Barnes, et al. Expires October 31, 2015 [Page 3] + +Internet-Draft Confidentiality Threat Model April 2015 + + + Inference: Information extracted from analysis of information + collected directly from communications by an eavesdropper or + observer. For example, the knowledge that a given web page was + accessed by a given IP address, by comparing the size in octets of + measured network flow records to fingerprints derived from known + sizes of linked resources on the web servers involved, would be an + inference. + + Collaborator: An entity that is a legitimate participant in a + communication, but who deliberately provides information about + that interaction to an attacker. + + Unwitting Collaborator: An entity that is a legitimate participant + in a communication, and who is the source of information obtained + by the attacker without the entity's consent or intention, because + the attacker has exploited some technology used by the entity. + + Key Exfiltration: The transmission of cryptographic keying material + for an encrypted communication from a collaborator, deliberately + or unwittingly, to an attacker. + + Content Exfiltration: The transmission of the content of a + communication from a collaborator, deliberately or unwittingly, to + an attacker + +3. An Idealized Passive Pervasive Attacker + + In considering the threat posed by pervasive surveillance, we begin + by defining an idealized passive pervasive attacker. While this + attacker is less capable than those which we now know to have + compromised the Internet from press reports, as elaborated in + Section 4, it does set a lower bound on the capabilities of an + attacker interested in indiscriminate passive surveillance while + interested in remaining undetectable. We note that, prior to the + Snowden revelations in 2013, the assumptions of attacker capability + presented here would be considered on the border of paranoia outside + the network security community. + + Our idealized attacker is an indiscriminate eavesdropper on an + Internet-attached computer network that: + + o can observe every packet of all communications at any hop in any + network path between an initiator and a recipient; + + o can observe data at rest in any intermediate system between the + endpoints controlled by the initiator and recipient; and + + o can share information with other such attackers; but + + + +Barnes, et al. Expires October 31, 2015 [Page 4] + +Internet-Draft Confidentiality Threat Model April 2015 + + + o takes no other action with respect to these communications (i.e., + blocking, modification, injection, etc.). + + The techniques available to our ideal attacker are direct + observation and inference. Direct observation involves taking + information directly from eavesdropped communications, such as + URLs identifying content or email addresses identifying + individuals from application- layer headers. Inference, on the + other hand, involves analyzing observed information to derive new + information, such as searching for application or behavioral + fingerprints in observed traffic to derive information about the + observed individual. The use of encryption is generally + sufficient to provide confidentiality by preventing direct + observation of content, assuming of course, uncompromised + encryption implementations and cryptographic keying material. + However, encryption provides less complete protection against + inference, especially inferences based only on plaintext portions + of communications, such as IP and TCP headers for TLS-protected + traffic [RFC5246]). + +3.1. Information subject to direct observation + + Protocols which do not encrypt their payload make the entire content + of the communication available to the idealized attacker along their + path. Following the advice in [RFC3365], most such protocols have a + secure variant which encrypts payload for confidentiality, and these + secure variants are seeing ever-wider deployment. A noteworthy + exception is DNS [RFC1035], as DNSSEC [RFC4033] does not have + confidentiality as a requirement. + + This implies that, in the absence of changes to the protocol as + presently under development in the IETF's DNS Private Exchange + (DPRIVE) working group [I-D.ietf-dprive-problem-statement], all DNS + queries and answers generated by the activities of any protocol are + available to the attacker. + + When store-and-forward protocols are used, (e.g. SMTP [RFC5321]) + intermediaries leave this data subject to observation by an attacker + that has compromised these intermediaries, unless the data is + encrypted end-to-end by the application layer protocol, or the + implementation uses an encrypted store for this data. + +3.2. Information useful for inference + + Inference is information extracted from later analysis of an observed + or eavesdropped communication, and/or correlation of observed or + eavesdropped information with information available from other + sources. Indeed, most useful inference performed by the attacker + + + +Barnes, et al. Expires October 31, 2015 [Page 5] + +Internet-Draft Confidentiality Threat Model April 2015 + + + falls under the rubric of correlation. The simplest example of this + is the observation of DNS queries and answers from and to a source + and correlating those with IP addresses with which that source + communicates. This can give access to information otherwise not + available from encrypted application payloads (e.g., the Host: + HTTP/1.1 request header when HTTP is used with TLS). + + Protocols which encrypt their payload using an application- or + transport-layer encryption scheme (e.g. TLS) still expose all the + information in their network and transport layer headers to the + attacker, including source and destination addresses and ports. + IPsec ESP[RFC4303] further encrypts the transport-layer headers, but + still leaves IP address information unencrypted; in tunnel mode, + these addresses correspond to the tunnel endpoints. Features of the + security protocols themselves, e.g. the TLS session identifier, may + leak information that can be used for correlation and inference. + While this information is much less semantically rich than the + application payload, it can still be useful for the inferring an + individual's activities. + + Inference can also leverage information obtained from sources other + than direct traffic observation. Geolocation databases, for example, + have been developed that map IP addresses to a location, in order to + provide location-aware services such as targeted advertising. This + location information is often of sufficient resolution that it can be + used to draw further inferences toward identifying or profiling an + individual. + + Social media provide another source of more or less publicly + accessible information. This information can be extremely + semantically rich, including information about an individual's + location, associations with other individuals and groups, and + activities. Further, this information is generally contributed and + curated voluntarily by the individuals themselves: it represents + information which the individuals are not necessarily interested in + protecting for privacy reasons. However, correlation of this social + networking data with information available from direct observation of + network traffic allows the creation of a much richer picture of an + individual's activities than either alone. + + We note with some alarm that there is little that can be done at + protocol design time to limit such correlation by the attacker, and + that the existence of such data sources in many cases greatly + complicates the problem of protecting privacy by hardening protocols + alone. + + + + + + +Barnes, et al. Expires October 31, 2015 [Page 6] + +Internet-Draft Confidentiality Threat Model April 2015 + + +3.3. An illustration of an ideal passive pervasive attack + + To illustrate how capable the idealized attacker is even given its + limitations, we explore the non-anonymity of encrypted IP traffic in + this section. Here we examine in detail some inference techniques + for associating a set of addresses with an individual, in order to + illustrate the difficulty of defending communications against our + idealized attacker. Here, the basic problem is that information + radiated even from protocols which have no obvious connection with + personal data can be correlated with other information which can + paint a very rich behavioral picture, that only takes one unprotected + link in the chain to associate with an identity. + +3.3.1. Analysis of IP headers + + Internet traffic can be monitored by tapping Internet links, or by + installing monitoring tools in Internet routers. Of course, a single + link or a single router only provides access to a fraction of the + global Internet traffic. However, monitoring a number of high + capacity links or a set of routers placed at strategic locations + provides access to a good sampling of Internet traffic. + + Tools like IPFIX [RFC7011] allow administrators to acquire statistics + about sequences of packets with some common properties that pass + through a network device. The most common set of properties used in + flow measurement is the "five-tuple"of source and destination + addresses, protocol type, and source and destination ports. These + statistics are commonly used for network engineering, but could + certainly be used for other purposes. + + Let's assume for a moment that IP addresses can be correlated to + specific services or specific users. Analysis of the sequences of + packets will quickly reveal which users use what services, and also + which users engage in peer-to-peer connections with other users. + Analysis of traffic variations over time can be used to detect + increased activity by particular users, or in the case of peer-to- + peer connections increased activity within groups of users. + +3.3.2. Correlation of IP addresses to user identities + + The correlation of IP addresses with specific users can be done in + various ways. For example, tools like reverse DNS lookup can be used + to retrieve the DNS names of servers. Since the addresses of servers + tend to be quite stable and since servers are relatively less + numerous than users, an attacker could easily maintain its own copy + of the DNS for well-known or popular servers, to accelerate such + lookups. + + + + +Barnes, et al. Expires October 31, 2015 [Page 7] + +Internet-Draft Confidentiality Threat Model April 2015 + + + On the other hand, the reverse lookup of IP addresses of users is + generally less informative. For example, a lookup of the address + currently used by one author's home network returns a name of the + form "c-192-000-002-033.hsd1.wa.comcast.net". This particular type + of reverse DNS lookup generally reveals only coarse-grained location + or provider information, equivalent to that available from + geolocation databases. + + In many jurisdictions, Internet Service Providers (ISPs) are required + to provide identification on a case by case basis of the "owner" of a + specific IP address for law enforcement purposes. This is a + reasonably expedient process for targeted investigations, but + pervasive surveillance requires something more efficient. This + provides an incentive for the attacker to secure the cooperation of + the ISP in order to automate this correlation. + +3.3.3. Monitoring messaging clients for IP address correlation + + Even if the ISP does not cooperate, user identity can often be + obtained via inference. POP3 [RFC1939] and IMAP [RFC3501] are used + to retrieve mail from mail servers, while a variant of SMTP is used + to submit messages through mail servers. IMAP connections originate + from the client, and typically start with an authentication exchange + in which the client proves its identity by answering a password + challenge. The same holds for the SIP protocol [RFC3261] and many + instant messaging services operating over the Internet using + proprietary protocols. + + The username is directly observable if any of these protocols operate + in cleartext; the username can then be directly associated with the + source address. + +3.3.4. Retrieving IP addresses from mail headers + + SMTP [RFC5321] requires that each successive SMTP relay adds a + "Received" header to the mail headers. The purpose of these headers + is to enable audit of mail transmission, and perhaps to distinguish + between regular mail and spam. Here is an extract from the headers + of a message recently received from the "perpass" mailing list: + + "Received: from 192-000-002-044.zone13.example.org (HELO + ?192.168.1.100?) (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net + with ESMTPSA (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct + 2013 21:47:14 +0100 Message-ID: <526D7BD2.7070908@example.org> Date: + Sun, 27 Oct 2013 20:47:14 +0000 From: Some One + " + + + + + +Barnes, et al. Expires October 31, 2015 [Page 8] + +Internet-Draft Confidentiality Threat Model April 2015 + + + This is the first "Received" header attached to the message by the + first SMTP relay; for privacy reasons, the field values have been + anonymized. We learn here that the message was submitted by "Some + One" on October 27, from a host behind a NAT (192.168.1.100) + [RFC1918] that used the IP address 192.0.2.44. The information + remained in the message, and is accessible by all recipients of the + "perpass" mailing list, or indeed by any attacker that sees at least + one copy of the message. + + An attacker that can observe sufficient email traffic can regularly + update the mapping between public IP addresses and individual email + identities. Even if the SMTP traffic was encrypted on submission and + relaying, the attacker can still receive a copy of public mailing + lists like "perpass". + +3.3.5. Tracking address usage with web cookies + + Many web sites only encrypt a small fraction of their transactions. + A popular pattern is to use HTTPS for the login information, and then + use a "cookie" to associate following clear-text transactions with + the user's identity. Cookies are also used by various advertisement + services to quickly identify the users and serve them with + "personalized" advertisements. Such cookies are particularly useful + if the advertisement services want to keep tracking the user across + multiple sessions that may use different IP addresses. + + As cookies are sent in clear text, an attacker can build a database + that associates cookies to IP addresses for non-HTTPS traffic. If + the IP address is already identified, the cookie can be linked to the + user identify. After that, if the same cookie appears on a new IP + address, the new IP address can be immediately associated with the + pre-determined identity. + +3.3.6. Graph-based approaches to address correlation + + An attacker can track traffic from an IP address not yet associated + with an individual to various public services (e.g. websites, mail + servers, game servers), and exploit patterns in the observed traffic + to correlate this address with other addresses that show similar + patterns. For example, any two addresses that show connections to + the same IMAP or webmail services, the same set of favorite websites, + and game servers at similar times of day may be associated with the + same individual. Correlated addresses can then be tied to an + individual through one of the techniques above, walking the "network + graph" to expand the set of attributable traffic. + + + + + + +Barnes, et al. Expires October 31, 2015 [Page 9] + +Internet-Draft Confidentiality Threat Model April 2015 + + +3.3.7. Tracking of Link Layer Identifiers + + Moving back down the stack, technologies like Ethernet or Wi-Fi use + MAC Addresses to identify link-level destinations. MAC Addresses + assigned according to IEEE-802 standards are globally-unique + identifiers for the device. If the link is publicly accessible, an + attacker can eavesdrop and perform tracking. For example, the + attacker can track the wireless traffic at publicly accessible Wi-Fi + networks. Simple devices can monitor the traffic, and reveal which + MAC Addresses are present. Also, devices do not need to be connected + to a network to expose link-layer identifiers. Active service + discovery always discloses the MAC address of the user, and sometimes + the SSIDs of previously visited networks. For instance, certain + techniques such as the use of "hidden SSIDs" require the mobile + device to broadcast the network identifier together with the device + identifier. This combination can further expose the user to + inference attacks, as more information can be derived from the + combination of MAC address, SSID being probed, time and current + location. For example, a user actively probing for a semi-unique + SSID on a flight out of a certain city can imply that the user is no + longer at the physical location of the corresponding AP. Given that + large-scale databases of the MAC addresses of wireless access points + for geolocation purposes have been known to exist for some time, the + attacker could easily build a database linking link-layer + identifiers, time and device or user identities, and use it to track + the movement of devices and of their owners. On the other hand, if + the network does not use some form of Wi-Fi encryption, or if the + attacker can access the decrypted traffic, the analysis will also + provide the correlation between link-layer identifiers such as MAC + Addresses and IP addresses. Additional monitoring using techniques + exposed in the previous sections will reveal the correlation between + MAC addresses, IP addresses, and user identity. For instance, + similarly to the use of web cookies, MAC addresses provide identity + information that can be used to associate a user to different IP + addresses. + +4. Reported Instances of Large-Scale Attacks + + The situation in reality is more bleak than that suggested by an + analysis of our idealized attacker. Through revelations of sensitive + documents in several media outlets, the Internet community has been + made aware of several intelligence activities conducted by US and UK + national intelligence agencies, particularly the US National Security + Agency (NSA) and the UK Government Communications Headquarters + (GCHQ). These documents have revealed methods that these agencies + use to attack Internet applications and obtain sensitive user + information. We note that these reports are primarily useful as an + + + + +Barnes, et al. Expires October 31, 2015 [Page 10] + +Internet-Draft Confidentiality Threat Model April 2015 + + + illustration of the types of capabilities fielded by pervasive + attackers as of the date of the Snowden leaks in 2013. + + First, they confirm the deployment of large-scale passive collection + of Internet traffic, which confirms the existence of pervasive + passive attackers with at least the capabilities of our idealized + attacker. For example [pass1][pass2][pass3][pass4]: + + o NSA's XKEYSCORE system accesses data from multiple access points + and searches for "selectors" such as email addresses, at the scale + of tens of terabytes of data per day. + + o GCHQ's Tempora system appears to have access to around 1,500 major + cables passing through the UK. + + o NSA's MUSCULAR program has tapped cables between data centers + belonging to major service providers. + + o Several programs appear to perform wide-scale collection of + cookies in web traffic and location data from location-aware + portable devices such as smartphones. + + However, the capabilities described by these reports go beyond those + of our idealized attacker. They include the compromise of + cryptographic protocols, including decryption of TLS-protected + Internet sessions [dec1][dec2][dec3]. For example, the NSA BULLRUN + project worked to undermine encryption through multiple approaches, + including covert modifications to cryptographic software on end + systems. + + Reported capabilities include the direct compromise of intermediate + systems and arrangements with service providers for bulk data and + metadata access [dir1][dir2][dir3], bypassing the need to capture + traffic on the wire. For example, the NSA PRISM program provides the + agency with access to many types of user data (e.g., email, chat, + VoIP). + + The reported capabilities also include elements of active pervasive + attack, including: + + o Insertion of devices as a man-in-the-middle of Internet + transactions [TOR1][TOR2]. For example, NSA's QUANTUM system + appears to use several different techniques to hijack HTTP + connections, ranging from DNS response injection to HTTP 302 + redirects. + + o Use of implants on end systems to undermine security and anonymity + features [dec2][TOR1][TOR2]. For example, QUANTUM is used to + + + +Barnes, et al. Expires October 31, 2015 [Page 11] + +Internet-Draft Confidentiality Threat Model April 2015 + + + direct users to a FOXACID server, which in turn delivers an + implant to compromise browsers of Tor users. + + o Use of implants on network elements from many major equipment + providers, including Cisco, Juniper, Huawei, Dell, and HP, as + provided by the NSA's Advanced Network Technology group. + [spiegel1] + + o Use of botnet-scale collections of compromised hosts [spiegel3]. + + The scale of the compromise extends beyond the network to include + subversion of the technical standards process itself. For example, + there is suspicion that NSA modifications to the DUAL_EC_DRBG random + number generator were made to ensure that keys generated using that + generator could be predicted by NSA. This RNG was made part of + NIST's SP 800-90A, for which NIST acknowledges NSA's assistance. + There have also been reports that the NSA paid RSA Security for a + related contract with the result that the curve became the default in + the RSA BSAFE product line. + + We use the term "pervasive attack" [RFC7258] to collectively describe + these operations. The term "pervasive" is used because the attacks + are designed to indiscriminately gather as much data as possible and + to apply selective analysis on targets after the fact. This means + that all, or nearly all, Internet communications are targets for + these attacks. To achieve this scale, the attacks are physically + pervasive; they affect a large number of Internet communications. + They are pervasive in content, consuming and exploiting any + information revealed by the protocol. And they are pervasive in + technology, exploiting many different vulnerabilities in many + different protocols. + + It's important to note that although the attacks mentioned above were + executed by NSA and GCHQ, there are many other organizations that can + mount pervasive surveillance attacks. Because of the resources + required to achieve pervasive scale, these attacks are most commonly + undertaken by nation-state actors. For example, the Chinese Internet + filtering system known as the "Great Firewall of China" uses several + techniques that are similar to the QUANTUM program, and which have a + high degree of pervasiveness with regard to the Internet in China. + +5. Threat Model + + Given these disclosures, we must consider a broader threat model. + + Pervasive surveillance aims to collect information across a large + number of Internet communications, analyzing the collected + communications to identify information of interest within individual + + + +Barnes, et al. Expires October 31, 2015 [Page 12] + +Internet-Draft Confidentiality Threat Model April 2015 + + + communications, or inferring information from correlated + communications. This analysis sometimes benefits from decryption of + encrypted communications and deanonymization of anonymized + communications. As a result, these attackers desire both access to + the bulk of Internet traffic and to the keying material required to + decrypt any traffic that has been encrypted. Even if keys are not + available, note that the presence of a communication and the fact + that it is encrypted may both be inputs to an analysis, even if the + attacker cannot decrypt the communication. + + The attacks listed above highlight new avenues both for access to + traffic and for access to relevant encryption keys. They further + indicate that the scale of surveillance is sufficient to provide a + general capability to cross-correlate communications, a threat not + previously thought to be relevant at the scale of the Internet. + +5.1. Attacker Capabilities + + +--------------------------+-------------------------------------+ + | Attack Class | Capability | + +--------------------------+-------------------------------------+ + | Passive observation | Directly capture data in transit | + | | | + | Passive inference | Infer from reduced/encrypted data | + | | | + | Active | Manipulate / inject data in transit | + | | | + | Static key exfiltration | Obtain key material once / rarely | + | | | + | Dynamic key exfiltration | Obtain per-session key material | + | | | + | Content exfiltration | Access data at rest | + +--------------------------+-------------------------------------+ + + Security analyses of Internet protocols commonly consider two classes + of attacker: Passive pervasive attackers, who can simply listen in on + communications as they transit the network, and active pervasive + attackers, who can modify or delete packets in addition to simply + collecting them. + + In the context of pervasive passive surveillance, these attacks take + on an even greater significance. In the past, these attackers were + often assumed to operate near the edge of the network, where attacks + can be simpler. For example, in some LANs, it is simple for any node + to engage in passive listening to other nodes' traffic or inject + packets to accomplish active pervasive attacks. However, as we now + know, both passive and active pervasive attacks are undertaken by + + + + +Barnes, et al. Expires October 31, 2015 [Page 13] + +Internet-Draft Confidentiality Threat Model April 2015 + + + pervasive attackers closer to the core of the network, greatly + expanding the scope and capability of the attacker. + + Eavesdropping and observation at a larger scale make passive + inference attacks easier to carry out: a passive pervasive attacker + with access to a large portion of the Internet can analyze collected + traffic to create a much more detailed view of individual behavior + than an attacker that collects at a single point. Even the usual + claim that encryption defeats passive pervasive attackers is + weakened, since a pervasive flow access attacker can infer + relationships from correlations over large numbers of sessions, e.g., + pairing encrypted sessions with unencrypted sessions from the same + host, or performing traffic fingerprinting between known and unknown + encrypted sessions. Reports on the NSA XKEYSCORE system would + indicate it is an example of such an attacker. + + An active pervasive attacker likewise has capabilities beyond those + of a localized active attacker. Flow modification attacks are often + limited by network topology, for example by a requirement that the + attacker be able to see a targeted session as well as inject packets + into it. A pervasive flow modification attacker with access at + multiple points within the core of the Internet is able to overcome + these topological limitations and perform attacks over a much broader + scope. Being positioned in the core of the network rather than the + edge can also enable an active pervasive attacker to reroute targeted + traffic, amplifying the ability to perform both eavesdropping and + traffic injection. Active pervasive attackers can also benefit from + passive pervasive collection to identify vulnerable hosts. + + While not directly related to pervasiveness, attackers that are in a + position to mount a active pervasive attack are also often in a + position to subvert authentication, a traditional protection against + such attacks. Authentication in the Internet is often achieved via + trusted third party authorities such as the Certificate Authorities + (CAs) that provide web sites with authentication credentials. An + attacker with sufficient resources may also be able to induce an + authority to grant credentials for an identity of the attacker's + choosing. If the parties to a communication will trust multiple + authorities to certify a specific identity, this attack may be + mounted by suborning any one of the authorities (the proverbial + "weakest link"). Subversion of authorities in this way can allow an + active attack to succeed in spite of an authentication check. + + Beyond these three classes (observation, inference, and active), + reports on the BULLRUN effort to defeat encryption and the PRISM + effort to obtain data from service providers suggest three more + classes of attack: + + + + +Barnes, et al. Expires October 31, 2015 [Page 14] + +Internet-Draft Confidentiality Threat Model April 2015 + + + o Static key exfiltration + + o Dynamic key exfiltration + + o Content exfiltration + + These attacks all rely on a collaborator providing the attacker with + some information, either keys or data. These attacks have not + traditionally been considered in scope for the Security + Considerations sections of IETF protocols, as they occur outside the + protocol. + + The term "key exfiltration" refers to the transfer of keying material + for an encrypted communication from the collaborator to the attacker. + By "static", we mean that the transfer of keys happens once, or + rarely, typically of a long-lived key. For example, this case would + cover a web site operator that provides the private key corresponding + to its HTTPS certificate to an intelligence agency. + + "Dynamic" key exfiltration, by contrast, refers to attacks in which + the collaborator delivers keying material to the attacker frequently, + e.g., on a per-session basis. This does not necessarily imply + frequent communications with the attacker; the transfer of keying + material may be virtual. For example, if an endpoint were modified + in such a way that the attacker could predict the state of its + psuedorandom number generator, then the attacker would be able to + derive per-session keys even without per-session communications. + + Finally, content exfiltration is the attack in which the collaborator + simply provides the attacker with the desired data or metadata. + Unlike the key exfiltration cases, this attack does not require the + attacker to capture the desired data as it flows through the network. + The exfiltration is of data at rest, rather than data in transit. + This increases the scope of data that the attacker can obtain, since + the attacker can access historical data - the attacker does not have + to be listening at the time the communication happens. + + Exfiltration attacks can be accomplished via attacks against one of + the parties to a communication, i.e., by the attacker stealing the + keys or content rather than the party providing them willingly. In + these cases, the party may not be aware that they are collaborating, + at least at a human level. Rather, the subverted technical assets + are "collaborating" with the attacker (by providing keys/content) + without their owner's knowledge or consent. + + Any party that has access to encryption keys or unencrypted data can + be a collaborator. While collaborators are typically the endpoints + of a communication (with encryption securing the links), + + + +Barnes, et al. Expires October 31, 2015 [Page 15] + +Internet-Draft Confidentiality Threat Model April 2015 + + + intermediaries in an unencrypted communication can also facilitate + content exfiltration attacks as collaborators by providing the + attacker access to those communications. For example, documents + describing the NSA PRISM program claim that NSA is able to access + user data directly from servers, where it is stored unencrypted. In + these cases, the operator of the server would be a collaborator, if + an unwitting one. By contrast, in the NSA MUSCULAR program, a set of + collaborators enabled attackers to access the cables connecting data + centers used by service providers such as Google and Yahoo. Because + communications among these data centers were not encrypted, the + collaboration by an intermediate entity allowed NSA to collect + unencrypted user data. + +5.2. Attacker Costs + + +--------------------------+-----------------------------------+ + | Attack Class | Cost / Risk to Attacker | + +--------------------------+-----------------------------------+ + | Passive observation | Passive data access | + | | | + | Passive inference | Passive data access + processing | + | | | + | Active | Active data access + processing | + | | | + | Static key exfiltration | One-time interaction | + | | | + | Dynamic key exfiltration | Ongoing interaction / code change | + | | | + | Content exfiltration | Ongoing, bulk interaction | + +--------------------------+-----------------------------------+ + + Each of the attack types discussed in the previous section entails + certain costs and risks. These costs differ by attack, and can be + helpful in guiding response to pervasive attack. + + Depending on the attack, the attacker may be exposed to several types + of risk, ranging from simply losing access to arrest or prosecution. + In order for any of these negative consequences to occur, however, + the attacker must first be discovered and identified. So the primary + risk we focus on here is the risk of discovery and attribution. + + A passive pervasive attack is the simplest to mount in some ways. + The base requirement is that the attacker obtain physical access to a + communications medium and extract communications from it. For + example, the attacker might tap a fiber-optic cable, acquire a mirror + port on a switch, or listen to a wireless signal. The need for these + taps to have physical access or proximity to a link exposes the + attacker to the risk that the taps will be discovered. For example, + + + +Barnes, et al. Expires October 31, 2015 [Page 16] + +Internet-Draft Confidentiality Threat Model April 2015 + + + a fiber tap or mirror port might be discovered by network operators + noticing increased attenuation in the fiber or a change in switch + configuration. Of course, passive pervasive attacks may be + accomplished with the cooperation of the network operator, in which + case there is a risk that the attacker's interactions with the + network operator will be exposed. + + In many ways, the costs and risks for an active pervasive attack are + similar to those for a passive pervasive attack, with a few + additions. An active attacker requires more robust network access + than a passive attacker, since for example they will often need to + transmit data as well as receiving it. In the wireless example + above, the attacker would need to act as an transmitter as well as + receiver, greatly increasing the probability the attacker will be + discovered (e.g., using direction-finding technology). Active + attacks are also much more observable at higher layers of the + network. For example, an active attacker that attempts to use a mis- + issued certificate could be detected via Certificate Transparency + [RFC6962]. + + In terms of raw implementation complexity, passive pervasive attacks + require only enough processing to extract information from the + network and store it. Active pervasive attacks, by contrast, often + depend on winning race conditions to inject packets into active + connections. So active pervasive attacks in the core of the network + require processing hardware to that can operate at line speed + (roughly 100Gbps to 1Tbps in the core) to identify opportunities for + attack and insert attack traffic in a high-volume traffic. Key + exfiltration attacks rely on passive pervasive attack for access to + encrypted data, with the collaborator providing keys to decrypt the + data. So the attacker undertakes the cost and risk of a passive + pervasive attack, as well as additional risk of discovery via the + interactions that the attacker has with the collaborator. + + Some active attacks are more expensive than others. For example, + active man-in-the-middle (MITM) attacks require access to the entire + network session and path in order to intercept and potentially + modify, as well as drop, legitimate packets in favor of the + attacker's packets. A similar but weaker form of attack, called an + active man-on-the-side (MOTS), does not require access to the entire + session and only part of the path. In an active MOTS attack, the + attacker need only be able to inject or modify traffic on the network + element the attacker has access to. While this may not allow for + full control of a communication session (as in an MITM attack), the + attacker can perform a number of powerful attacks, including but not + limited to: injecting packets that could terminate the session (e.g., + TCP RST packets), sending a fake DNS reply to redirect ensuing TCP + connections to an address of the attacker's choice (i.e., winning a + + + +Barnes, et al. Expires October 31, 2015 [Page 17] + +Internet-Draft Confidentiality Threat Model April 2015 + + + "DNS response race"), and mounting an HTTP Redirect attack by + observing a TCP/HTTP connection to a target address and injecting a + TCP data packet containing an HTTP redirect. For example, the system + dubbed by researchers as China's "Great Cannon" [great-cannon] can + operate in ful MITM mode to accomplish very complex attacks that can + modify content in transit while the well-known Great Firewall of + China is a MOTS system that focuses on blocking access to certain + kinds of traffic and destinations via TCP RST packet injection. + + In this sense, static exfiltration has a lower risk profile than + dynamic. In the static case, the attacker need only interact with + the collaborator a small number of times, possibly only once, say to + exchange a private key. In the dynamic case, the attacker must have + continuing interactions with the collaborator. As noted above these + interactions may be real, such as in-person meetings, or virtual, + such as software modifications that render keys available to the + attacker. Both of these types of interactions introduce a risk that + they will be discovered, e.g., by employees of the collaborator + organization noticing suspicious meetings or suspicious code changes. + + Content exfiltration has a similar risk profile to dynamic key + exfiltration. In a content exfiltration attack, the attacker saves + the cost and risk of conducting a passive pervasive attack. The risk + of discovery through interactions with the collaborator, however, is + still present, and may be higher. The content of a communication is + obviously larger than the key used to encrypt it, often by several + orders of magnitude. So in the content exfiltration case, the + interactions between the collaborator and the attacker need to be + much higher-bandwidth than in the key exfiltration cases, with a + corresponding increase in the risk that this high-bandwidth channel + will be discovered. + + It should also be noted that in these latter three exfiltration + cases, the collaborator also undertakes a risk that his collaboration + with the attacker will be discovered. Thus the attacker may have to + incur additional cost in order to convince the collaborator to + participate in the attack. Likewise, the scope of these attacks is + limited to case where the attacker can convince a collaborator to + participate. If the attacker is a national government, for example, + it may be able to compel participation within its borders, but have a + much more difficult time recruiting foreign collaborators. + + As noted above, the collaborator in an exfiltration attack can be + unwitting; the attacker can steal keys or data to enable the attack. + In some ways, the risks of this approach are similar to the case of + an active collaborator. In the static case, the attacker needs to + steal information from the collaborator once; in the dynamic case, + the attacker needs to continued presence inside the collaborators + + + +Barnes, et al. Expires October 31, 2015 [Page 18] + +Internet-Draft Confidentiality Threat Model April 2015 + + + systems. The main difference is that the risk in this case is of + automated discovery (e.g., by intrusion detection systems) rather + than discovery by humans. + +6. Security Considerations + + This document describes a threat model for pervasive surveillance + attacks. Mitigations are to be given in a future document. + +7. IANA Considerations + + This document has no actions for IANA. + +8. Acknowledgements + + Thanks to Dave Thaler for the list of attacks and taxonomy; to + Security Area Directors Stephen Farrell, Sean Turner, and Kathleen + Moriarty for starting and managing the IETF's discussion on pervasive + attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, + Evangelos Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, Russ Housley, + and the IAB Privacy and Security Program for their input. + +9. References + +9.1. Normative References + + [RFC6973] Cooper, A., Tschofenig, H., Aboba, B., Peterson, J., + Morris, J., Hansen, M., and R. Smith, "Privacy + Considerations for Internet Protocols", RFC 6973, July + 2013. + +9.2. Informative References + + [pass1] The Guardian, "How the NSA is still harvesting your online + data", 2013, + . + + [pass2] The Guardian, "NSA's Prism surveillance program: how it + works and what it can do", 2013, + . + + [pass3] The Guardian, "XKeyscore: NSA tool collects 'nearly + everything a user does on the internet'", 2013, + . + + + + +Barnes, et al. Expires October 31, 2015 [Page 19] + +Internet-Draft Confidentiality Threat Model April 2015 + + + [pass4] The Guardian, "How does GCHQ's internet surveillance + work?", n.d., . + + [dec1] The New York Times, "N.S.A. Able to Foil Basic Safeguards + of Privacy on Web", 2013, + . + + [dec2] The Guardian, "Project Bullrun - classification guide to + the NSA's decryption program", 2013, + . + + [dec3] The Guardian, "Revealed: how US and UK spy agencies defeat + internet privacy and security", 2013, + . + + [TOR] The Tor Project, "Tor", 2013, + . + + [TOR1] Schneier, B., "How the NSA Attacks Tor/Firefox Users With + QUANTUM and FOXACID", 2013, + . + + [TOR2] The Guardian, "'Tor Stinks' presentation - read the full + document", 2013, + . + + [dir1] The Guardian, "NSA collecting phone records of millions of + Verizon customers daily", 2013, + . + + [dir2] The Guardian, "NSA Prism program taps in to user data of + Apple, Google and others", 2013, + . + + [dir3] The Guardian, "Sigint - how the NSA collaborates with + technology companies", 2013, + . + + + + + +Barnes, et al. Expires October 31, 2015 [Page 20] + +Internet-Draft Confidentiality Threat Model April 2015 + + + [secure] Schneier, B., "NSA surveillance: A guide to staying + secure", 2013, + . + + [snowden] Technology Review, "NSA Leak Leaves Crypto-Math Intact but + Highlights Known Workarounds", 2013, + . + + [spiegel1] + C Stocker, ., "NSA's Secret Toolbox: Unit Offers Spy + Gadgets for Every Need", December 2013, + . + + [spiegel3] + H Schmundt, ., "The Digital Arms Race: NSA Preps America + for Future Battle", January 2014, + . + + [key-recovery] + Golle, P., "The Design and Implementation of Protocol- + Based Hidden Key Recovery", 2003, + . + + [great-cannon] + Paxson, V., "China's Great Cannon", 2015, + . + + [RFC1035] Mockapetris, P., "Domain names - implementation and + specification", STD 13, RFC 1035, November 1987. + + [RFC1918] Rekhter, Y., Moskowitz, R., Karrenberg, D., Groot, G., and + E. Lear, "Address Allocation for Private Internets", BCP + 5, RFC 1918, February 1996. + + [RFC1939] Myers, J. and M. Rose, "Post Office Protocol - Version 3", + STD 53, RFC 1939, May 1996. + + [RFC2015] Elkins, M., "MIME Security with Pretty Good Privacy + (PGP)", RFC 2015, October 1996. + + + + + +Barnes, et al. Expires October 31, 2015 [Page 21] + +Internet-Draft Confidentiality Threat Model April 2015 + + + [RFC2821] Klensin, J., "Simple Mail Transfer Protocol", RFC 2821, + April 2001. + + [RFC3261] Rosenberg, J., Schulzrinne, H., Camarillo, G., Johnston, + A., Peterson, J., Sparks, R., Handley, M., and E. + Schooler, "SIP: Session Initiation Protocol", RFC 3261, + June 2002. + + [RFC3365] Schiller, J., "Strong Security Requirements for Internet + Engineering Task Force Standard Protocols", BCP 61, RFC + 3365, August 2002. + + [RFC3501] Crispin, M., "INTERNET MESSAGE ACCESS PROTOCOL - VERSION + 4rev1", RFC 3501, March 2003. + + [RFC3851] Ramsdell, B., "Secure/Multipurpose Internet Mail + Extensions (S/MIME) Version 3.1 Message Specification", + RFC 3851, July 2004. + + [RFC4033] Arends, R., Austein, R., Larson, M., Massey, D., and S. + Rose, "DNS Security Introduction and Requirements", RFC + 4033, March 2005. + + [RFC4301] Kent, S. and K. Seo, "Security Architecture for the + Internet Protocol", RFC 4301, December 2005. + + [RFC4303] Kent, S., "IP Encapsulating Security Payload (ESP)", RFC + 4303, December 2005. + + [RFC4306] Kaufman, C., "Internet Key Exchange (IKEv2) Protocol", RFC + 4306, December 2005. + + [RFC4949] Shirey, R., "Internet Security Glossary, Version 2", RFC + 4949, August 2007. + + [RFC5246] Dierks, T. and E. Rescorla, "The Transport Layer Security + (TLS) Protocol Version 1.2", RFC 5246, August 2008. + + [RFC5321] Klensin, J., "Simple Mail Transfer Protocol", RFC 5321, + October 2008. + + [RFC5655] Trammell, B., Boschi, E., Mark, L., Zseby, T., and A. + Wagner, "Specification of the IP Flow Information Export + (IPFIX) File Format", RFC 5655, October 2009. + + [RFC5750] Ramsdell, B. and S. Turner, "Secure/Multipurpose Internet + Mail Extensions (S/MIME) Version 3.2 Certificate + Handling", RFC 5750, January 2010. + + + +Barnes, et al. Expires October 31, 2015 [Page 22] + +Internet-Draft Confidentiality Threat Model April 2015 + + + [RFC6120] Saint-Andre, P., "Extensible Messaging and Presence + Protocol (XMPP): Core", RFC 6120, March 2011. + + [RFC6962] Laurie, B., Langley, A., and E. Kasper, "Certificate + Transparency", RFC 6962, June 2013. + + [RFC6698] Hoffman, P. and J. Schlyter, "The DNS-Based Authentication + of Named Entities (DANE) Transport Layer Security (TLS) + Protocol: TLSA", RFC 6698, August 2012. + + [RFC7011] Claise, B., Trammell, B., and P. Aitken, "Specification of + the IP Flow Information Export (IPFIX) Protocol for the + Exchange of Flow Information", STD 77, RFC 7011, September + 2013. + + [RFC7258] Farrell, S. and H. Tschofenig, "Pervasive Monitoring Is an + Attack", BCP 188, RFC 7258, May 2014. + + [I-D.ietf-dprive-problem-statement] + Bortzmeyer, S., "DNS privacy considerations", draft-ietf- + dprive-problem-statement-02 (work in progress), February + 2015. + +Authors' Addresses + + Richard Barnes + + Email: rlb@ipv.sx + + + Bruce Schneier + + Email: schneier@schneier.com + + + Cullen Jennings + + Email: fluffy@cisco.com + + + Ted Hardie + + Email: ted.ietf@gmail.com + + + Brian Trammell + + Email: ietf@trammell.ch + + + +Barnes, et al. Expires October 31, 2015 [Page 23] + +Internet-Draft Confidentiality Threat Model April 2015 + + + Christian Huitema + + Email: huitema@huitema.net + + + Daniel Borkmann + + Email: dborkman@iogearbox.net + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Barnes, et al. Expires October 31, 2015 [Page 24] diff --git a/draft-iab-privsec-confidentiality-threat-05.xml b/draft-iab-privsec-confidentiality-threat-05.xml new file mode 100644 index 0000000..764cda1 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-05.xml @@ -0,0 +1,1110 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +]> + + + + + + Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement + + + +
+ rlb@ipv.sx +
+ + + +
+ schneier@schneier.com +
+ + + +
+ fluffy@cisco.com +
+ + + +
+ ted.ietf@gmail.com +
+ + + +
+ ietf@trammell.ch +
+ + + +
+ huitema@huitema.net +
+ + + +
+ dborkman@iogearbox.net +
+ + + + + + + + + + + +Since the initial revelations of pervasive surveillance in 2013, + several classes of attacks on Internet communications have been + discovered. In this document we develop a threat model that + describes these attacks on Internet confidentiality. We assume an + attacker that is interested in undetected, indiscriminate + eavesdropping. The threat model is based on published, verified + attacks. + + + + + + + + + + + +
+ +Starting in June 2013, documents released to the press by Edward +Snowden have revealed several operations undertaken by intelligence +agencies to exploit Internet communications for intelligence purposes. +These attacks were largely based on protocol vulnerabilities that were +already known to exist. The attacks were nonetheless striking in +their pervasive nature, both in terms of the amount of Internet +communications targeted, and in terms of the diversity of attack +techniques employed. + +To ensure that the Internet can be trusted by users, it is necessary +for the Internet technical community to address the vulnerabilities +exploited in these attacks . The goal of this document is +to describe more precisely the threats posed by these pervasive +attacks, and based on those threats, lay out the problems that need to +be solved in order to secure the Internet in the face of those +threats. + +The remainder of this document is structured as follows. In +, we describe an idealized passive pervasive attacker, one which +could completely undetectably compromise communications at Internet +scale. In , we provide a brief summary of some attacks +that have been disclosed, and use these to expand the assumed +capabilities of our idealized attacker. Note that we do not attempt +to describe all possible attacks, but focus on those which result in +undetected eavesdropping. describes a threat model based on +these attacks, focusing on classes of attack that have not been a +focus of Internet engineering to date. + +
+
+ +This document makes extensive use of standard security and privacy +terminology; see and . Terms used from + include Eavesdropper, Observer, Initiator, Intermediary, +Recipient, Attack (in a privacy context), Correlation, Fingerprint, +Traffic Analysis, and Identifiability (and related terms). In +addition, we use a few terms that are specific to the attacks +discussed in this document. Note especially that “passive” and “active” below +do not refer to the effort used to mount the attack; a “passive attack” +is any attack that accesses a flow but does not modify it, while an +“active attack” is any attack that modifies a flow. Some passive attacks +involve active interception and modifications of devices, rather than simple +access to the medium. The introduced terms are: + + + + An attack on Internet communications that makes +use of access at a large number of points in the network, or otherwise +provides the attacker with access to a large amount of Internet +traffic; see . + + An eavesdropping attack undertaken by a pervasive attacker, in which the +packets in a traffic stream between two endpoints are intercepted, but +in which the attacker does not modify the packets in the traffic +stream between two endpoints, modify the treatment of packets in the +traffic stream (e.g. delay, routing), or add or remove packets in the +traffic stream. Passive pervasive attacks are undetectable from the +endpoints. Equivalent to passive wiretapping as defined in ; +we use an alternate term here since the methods employed are wider +than those implied by the word “wiretapping”, including the active +compromise of intermediate systems. + + An attack undertaken by a pervasive attacker, which in addition to +the elements of a passive pervasive attack, also includes modification, +addition, or removal of +packets in a traffic stream, or modification of treatment of packets +in the traffic stream. Active pervasive attacks provide more +capabilities to the attacker at the risk of possible detection at the +endpoints. Equivalent to active wiretapping as defined in . + + Information collected directly from communications by an +eavesdropper or observer. For example, the knowledge that +<alice@example.com> sent a message to <bob@example.com> +via SMTP taken from the headers of an observed SMTP message would be +an observation. + + Information extracted from analysis of information collected +directly from communications by an eavesdropper or observer. For +example, the knowledge that a given web page was accessed by a given +IP address, by comparing the size in octets of measured network flow +records to fingerprints derived from known sizes of linked resources +on the web servers involved, would be an inference. + + An entity that is a legitimate participant in a communication, but +who deliberately provides information about that interaction to an +attacker. + + An entity that is a legitimate participant in a communication, and +who is the source of information obtained by the attacker without the +entity’s consent or intention, because the attacker has exploited some +technology used by the entity. + + The transmission of cryptographic keying material for an encrypted communication +from a collaborator, deliberately or unwittingly, to an attacker. + + The transmission of the content of a communication from a collaborator, deliberately or unwittingly, to an attacker + + +
+
+ +In considering the threat posed by pervasive surveillance, we begin by +defining an idealized passive pervasive attacker. While this attacker +is less capable than those which we now know to have compromised the +Internet from press reports, as elaborated in , it does +set a lower bound on the capabilities of an attacker interested in +indiscriminate passive surveillance while interested in remaining +undetectable. We note that, prior to the Snowden revelations in 2013, +the assumptions of attacker capability presented here would be +considered on the border of paranoia outside the network security +community. + +Our idealized attacker is an indiscriminate eavesdropper on an Internet-attached computer network that: + + + can observe every packet of all communications at any hop in any network path between an initiator and a recipient; + can observe data at rest in any intermediate system between the endpoints controlled by the initiator and recipient; and + can share information with other such attackers; but + takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.). +The techniques available to our ideal attacker are direct observation +and inference. Direct observation involves taking information +directly from eavesdropped communications, such as URLs identifying +content or email addresses identifying individuals from application- +layer headers. Inference, on the other hand, involves analyzing +observed information to derive new information, such as searching for +application or behavioral fingerprints in observed traffic to derive +information about the observed individual. The use of encryption is +generally sufficient to provide confidentiality by preventing direct +observation of content, assuming of course, uncompromised encryption +implementations and cryptographic keying material. However, +encryption provides less complete protection against inference, +especially inferences based only on plaintext portions of +communications, such as IP and TCP headers for TLS-protected traffic +). + + +
+ +Protocols which do not encrypt their payload make the entire content +of the communication available to the idealized attacker along their +path. Following the advice in , most such protocols have a +secure variant which encrypts payload for confidentiality, and these +secure variants are seeing ever-wider deployment. A noteworthy +exception is DNS , as DNSSEC does not have +confidentiality as a requirement. + +This implies that, in the absence of +changes to the protocol as presently under development in the IETF’s +DNS Private Exchange (DPRIVE) +working group , all DNS queries and answers generated by the activities +of any protocol are available to the attacker. + +When store-and-forward protocols are used, (e.g. SMTP ) +intermediaries leave this data subject to observation by an attacker that +has compromised these intermediaries, +unless the data is encrypted end-to-end by the application layer +protocol, or the implementation uses an encrypted store for this data. + +
+
+ +Inference is information extracted from later analysis of an observed +or eavesdropped communication, and/or correlation of observed or +eavesdropped information with information available from other +sources. Indeed, most useful inference performed by the attacker falls +under the rubric of correlation. The simplest example of this is the +observation of DNS queries and answers from and to a source and +correlating those with IP addresses with which that source +communicates. This can give access to information otherwise not +available from encrypted application payloads (e.g., the Host: +HTTP/1.1 request header when HTTP is used with TLS). + +Protocols which encrypt their payload using an application- or +transport-layer encryption scheme (e.g. TLS) still expose all the +information in their network and transport layer headers to the +attacker, including source and destination addresses and ports. IPsec +ESP further encrypts the transport-layer headers, but still +leaves IP address information unencrypted; in tunnel mode, these +addresses correspond to the tunnel endpoints. Features of the +security protocols themselves, e.g. the TLS session identifier, +may leak information that can be used for correlation and +inference. While this information is much less semantically rich than +the application payload, it can still be useful for the inferring an +individual’s activities. + +Inference can also leverage information obtained from sources other +than direct traffic observation. Geolocation databases, for example, +have been developed that map IP addresses to a location, in order to +provide location-aware services such as targeted advertising. This +location information is often of sufficient resolution that it can be +used to draw further inferences toward identifying or profiling an +individual. + +Social media provide another source of more or less publicly +accessible information. This information can be extremely semantically +rich, including information about an individual’s location, +associations with other individuals and groups, and +activities. Further, this information is generally contributed and +curated voluntarily by the individuals themselves: it represents +information which the individuals are not necessarily interested in +protecting for privacy reasons. However, correlation of this social +networking data with information available from direct observation of +network traffic allows the creation of a much richer picture of an +individual’s activities than either alone. + +We note with some alarm that there is little that can be done at +protocol design time to limit such correlation by the attacker, and +that the existence of such data sources in many cases greatly +complicates the problem of protecting privacy by hardening protocols +alone. + +
+
+ +To illustrate how capable the idealized attacker is even given its +limitations, we explore the non-anonymity of encrypted IP traffic in +this section. Here we examine in detail some inference techniques for +associating a set of addresses with an individual, in order to +illustrate the difficulty of defending communications against our +idealized attacker. Here, the basic problem is that information +radiated even from protocols which have no obvious connection with +personal data can be correlated with other information which can paint +a very rich behavioral picture, that only takes one unprotected link +in the chain to associate with an identity. + +
+ +Internet traffic can be monitored by tapping Internet links, or by +installing monitoring tools in Internet routers. Of course, a single +link or a single router only provides access to a fraction of the +global Internet traffic. However, monitoring a number of high capacity +links or a set of routers placed at strategic locations provides +access to a good sampling of Internet traffic. + +Tools like IPFIX allow administrators to acquire +statistics about sequences of packets with some common properties that +pass through a network device. The most common set of properties used +in flow measurement is the “five-tuple”of source and destination +addresses, protocol type, and source and destination ports. These +statistics are commonly used for network engineering, but could +certainly be used for other purposes. + +Let’s assume for a moment that IP addresses can be correlated to +specific services or specific users. Analysis of the sequences of +packets will quickly reveal which users use what services, and also +which users engage in peer-to-peer connections with other +users. Analysis of traffic variations over time can be used to detect +increased activity by particular users, or in the case of peer-to-peer +connections increased activity within groups of users. + +
+
+ +The correlation of IP addresses with specific users can be done in +various ways. For example, tools like reverse DNS lookup can be used +to retrieve the DNS names of servers. Since the addresses of servers +tend to be quite stable and since servers are relatively less numerous +than users, an attacker could easily maintain its own copy of the DNS +for well-known or popular servers, to accelerate such lookups. + +On the other hand, the reverse lookup of IP addresses of users is +generally less informative. For example, a lookup of the address +currently used by one author’s home network returns a name of the form +“c-192-000-002-033.hsd1.wa.comcast.net”. This particular type of +reverse DNS lookup generally reveals only coarse-grained location or +provider information, equivalent to that available from geolocation +databases. + +In many jurisdictions, Internet Service Providers (ISPs) are required +to provide identification on a case by case basis of the “owner” of a +specific IP address for law enforcement purposes. This is a reasonably +expedient process for targeted investigations, but pervasive +surveillance requires something more efficient. This provides an +incentive for the attacker to secure the cooperation of the ISP in +order to automate this correlation. + +
+
+ +Even if the ISP does not cooperate, user identity can often be +obtained via inference. POP3 and IMAP are used +to retrieve mail from mail servers, while a variant of SMTP is used to +submit messages through mail servers. IMAP connections originate from +the client, and typically start with an authentication exchange in +which the client proves its identity by answering a password +challenge. The same holds for the SIP protocol and many +instant messaging services operating over the Internet using +proprietary protocols. + +The username is directly observable if any of these protocols operate +in cleartext; the username can then be directly associated with the +source address. + +
+
+ +SMTP requires that each successive SMTP relay adds a +“Received” header to the mail headers. The purpose of these headers is +to enable audit of mail transmission, and perhaps to distinguish +between regular mail and spam. Here is an extract from the headers of +a message recently received from the “perpass” mailing list: + + + Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?) + (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA + (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100 + Message-ID: <526D7BD2.7070908@example.org> + Date: Sun, 27 Oct 2013 20:47:14 +0000 + From: Some One <some.one@example.org> + + +This is the first “Received” header attached to the message by the +first SMTP relay; for privacy reasons, the field values have been +anonymized. We learn here that the message was submitted by “Some One” +on October 27, from a host behind a NAT (192.168.1.100) +that used the IP address 192.0.2.44. The information remained in the +message, and is accessible by all recipients of the “perpass” mailing +list, or indeed by any attacker that sees at least one copy of the +message. + +An attacker that can observe sufficient email traffic can regularly +update the mapping between public IP addresses and individual email +identities. Even if the SMTP traffic was encrypted on submission and +relaying, the attacker can still receive a copy of public mailing +lists like “perpass”. + +
+
+ +Many web sites only encrypt a small fraction of their transactions. A +popular pattern is to use HTTPS for the login information, and then +use a “cookie” to associate following clear-text transactions with the +user’s identity. Cookies are also used by various advertisement +services to quickly identify the users and serve them with +“personalized” advertisements. Such cookies are particularly useful if +the advertisement services want to keep tracking the user across +multiple sessions that may use different IP addresses. + +As cookies are sent in clear text, an attacker can build a database +that associates cookies to IP addresses for non-HTTPS traffic. If the +IP address is already identified, the cookie can be linked to the user +identify. After that, if the same cookie appears on a new IP address, +the new IP address can be immediately associated with the +pre-determined identity. + +
+
+ +An attacker can track traffic from an IP address not yet associated +with an individual to various public services (e.g. websites, mail +servers, game servers), and exploit patterns in the observed traffic +to correlate this address with other addresses that show similar +patterns. For example, any two addresses that show connections to the +same IMAP or webmail services, the same set of favorite websites, and +game servers at similar times of day may be associated with the same +individual. Correlated addresses can then be tied to an individual +through one of the techniques above, walking the “network graph” to +expand the set of attributable traffic. + +
+
+ +Moving back down the stack, technologies like Ethernet or Wi-Fi use MAC Addresses to identify link-level destinations. MAC Addresses assigned according to IEEE-802 standards are globally-unique identifiers for the device. If the link is publicly accessible, an attacker can eavesdrop and perform tracking. For example, the attacker can track the wireless traffic at publicly accessible Wi-Fi networks. Simple devices can monitor the traffic, and reveal which MAC Addresses are present. +Also, devices do not need to be connected to a network to expose link-layer identifiers. Active service discovery always discloses the MAC address of the user, and sometimes the SSIDs of previously visited networks. For instance, certain techniques such as the use of “hidden SSIDs” require the mobile device to broadcast the network identifier together with the device identifier. This combination can further expose the user to inference attacks, as more information can be derived from the combination of MAC address, SSID being probed, time and current location. For example, a user actively probing for a semi-unique SSID on a flight out of a certain city can imply that the user is no longer at the physical location of the corresponding AP. +Given that large-scale databases of the MAC addresses of wireless access points for geolocation purposes have been known to exist for some time, the attacker could easily build a database linking link-layer identifiers, time and device or user identities, and use it to track the movement of devices and of their owners. +On the other hand, if the network does not use some form of Wi-Fi encryption, or if the attacker can access the decrypted traffic, the analysis will also provide the correlation between link-layer identifiers such as MAC Addresses and IP addresses. Additional monitoring using techniques exposed in the previous sections will reveal the correlation between MAC addresses, IP addresses, and user identity. For instance, similarly to the use of web cookies, MAC addresses provide identity information that can be used to associate a user to different IP addresses. + +
+
+
+
+ +The situation in reality is more bleak than that suggested by an +analysis of our idealized attacker. Through revelations of sensitive +documents in several media outlets, the Internet community has been +made aware of several intelligence activities conducted by US and UK +national intelligence agencies, particularly the US National Security +Agency (NSA) and the UK Government Communications Headquarters +(GCHQ). These documents have revealed methods that these agencies use +to attack Internet applications and obtain sensitive user information. +We note that these reports are primarily useful as an illustration of +the types of capabilities fielded by pervasive attackers as of the +date of the Snowden leaks in 2013. + +First, they confirm the deployment of large-scale passive +collection of Internet traffic, which confirms the existence of +pervasive passive attackers with at least the capabilities of our +idealized attacker. For example : + + + NSA’s XKEYSCORE system accesses data from multiple access points and +searches for “selectors” such as email addresses, at the scale of tens +of terabytes of data per day. + GCHQ’s Tempora system appears to have access to around 1,500 major cables +passing through the UK. + NSA’s MUSCULAR program has tapped cables between data centers +belonging to major service providers. + Several programs appear to perform wide-scale collection +of cookies in web traffic and location data from location-aware +portable devices such as smartphones. + + +However, the capabilities described by these reports go beyond those of our +idealized attacker. They include the compromise of cryptographic protocols, +including decryption of TLS-protected Internet sessions . +For example, the NSA BULLRUN project worked to undermine encryption through +multiple approaches, including covert modifications to cryptographic +software on end systems. + +Reported capabilities include the direct compromise of intermediate systems +and arrangements with service providers for bulk data and metadata +access , bypassing the need to capture +traffic on the wire. For example, the NSA PRISM program provides the +agency with access to many types of user data (e.g., email, chat, VoIP). + +The reported capabilities also include elements of active pervasive attack, +including: + + + Insertion of devices as a man-in-the-middle of Internet +transactions . For example, NSA’s QUANTUM system +appears to use several different techniques to hijack HTTP +connections, ranging from DNS response injection to HTTP 302 +redirects. + Use of implants on end systems to undermine security and anonymity +features . For example, QUANTUM is used to +direct users to a FOXACID server, which in turn delivers an implant +to compromise browsers of Tor users. + Use of implants on network elements from many major equipment providers, +including Cisco, Juniper, Huawei, Dell, and HP, as provided by the NSA’s +Advanced Network Technology group. + Use of botnet-scale collections of compromised hosts . + + +The scale of the compromise extends beyond the network to include subversion of the technical standards process itself. For example, there is suspicion that NSA modifications to the DUAL_EC_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA. This RNG was made part of NIST’s SP 800-90A, for which NIST acknowledges NSA’s assistance. There have also been reports that the NSA paid RSA Security for a related contract with the result that the curve became the default in the RSA BSAFE product line. + +We use the term “pervasive attack” to collectively +describe these operations. The term “pervasive” is used because the +attacks are designed to indiscriminately gather as much data as +possible and to apply selective analysis on targets after the fact. +This means that all, or nearly all, Internet communications are +targets for these attacks. To achieve this scale, the attacks are +physically pervasive; they affect a large number of Internet +communications. They are pervasive in content, consuming and +exploiting any information revealed by the protocol. And they are +pervasive in technology, exploiting many different vulnerabilities in +many different protocols. + +It’s important to note that although the attacks mentioned above were +executed by NSA and GCHQ, there are many other organizations that can +mount pervasive surveillance attacks. Because of the resources +required to achieve pervasive scale, these attacks are most commonly +undertaken by nation-state actors. For example, the Chinese Internet +filtering system known as the “Great Firewall of China” uses several +techniques that are similar to the QUANTUM program, and which have a +high degree of pervasiveness with regard to the Internet in China. + +
+
+ +Given these disclosures, we must consider a broader threat model. + +Pervasive surveillance aims to collect information across a large +number of Internet communications, analyzing the collected +communications to identify information of interest within individual +communications, or inferring information from correlated +communications. This analysis sometimes benefits from decryption of +encrypted communications and deanonymization of anonymized +communications. As a result, these attackers desire both access to +the bulk of Internet traffic and to the keying material required to +decrypt any traffic that has been encrypted. Even if keys are not +available, note that the presence of a communication and the fact that +it is encrypted may both be inputs to an analysis, even if the +attacker cannot decrypt the communication. + +The attacks listed above highlight new avenues both for access to +traffic and for access to relevant encryption keys. They further +indicate that the scale of surveillance is sufficient to provide a +general capability to cross-correlate communications, a threat not +previously thought to be relevant at the scale of the Internet. + +
+ + + Attack Class + Capability + Passive observation + Directly capture data in transit + Passive inference + Infer from reduced/encrypted data + Active + Manipulate / inject data in transit + Static key exfiltration + Obtain key material once / rarely + Dynamic key exfiltration + Obtain per-session key material + Content exfiltration + Access data at rest + + +Security analyses of Internet protocols commonly consider two classes +of attacker: Passive pervasive attackers, who can simply listen in on +communications as they transit the network, and active pervasive +attackers, who can modify or delete packets in addition to simply +collecting them. + +In the context of pervasive passive surveillance, these attacks take +on an even greater significance. In the past, these attackers were +often assumed to operate near the edge of the network, where attacks +can be simpler. For example, in some LANs, it is simple for any node +to engage in passive listening to other nodes’ traffic or inject +packets to accomplish active pervasive attacks. However, as we now +know, both passive and active pervasive attacks are undertaken by +pervasive attackers closer to the core of the network, greatly +expanding the scope and capability of the attacker. + +Eavesdropping and observation at a larger scale make passive inference +attacks easier to carry out: a passive pervasive attacker with access to a +large portion of the Internet can analyze collected traffic to create +a much more detailed view of individual behavior than an attacker that +collects at a single point. Even the usual claim that encryption +defeats passive pervasive attackers is weakened, since a pervasive flow +access attacker can infer relationships from correlations over large +numbers of sessions, e.g., pairing encrypted sessions with unencrypted +sessions from the same host, or performing traffic fingerprinting +between known and unknown encrypted sessions. Reports on the NSA +XKEYSCORE system would indicate it is an example of such an attacker. + +An active pervasive attacker likewise has capabilities +beyond those of a localized active attacker. Flow +modification attacks are often limited by network topology, for +example by a requirement that the attacker be able to see a targeted +session as well as inject packets into it. A pervasive flow +modification attacker with access at multiple points within the core +of the Internet is able to overcome these topological limitations and +perform attacks over a much broader scope. Being positioned in the +core of the network rather than the edge can also enable an active +pervasive attacker to reroute targeted traffic, amplifying the +ability to perform both eavesdropping and traffic injection. +Active pervasive attackers can also benefit from passive pervasive +collection to identify vulnerable hosts. + +While not directly related to pervasiveness, attackers that are in a +position to mount a active pervasive attack are also often +in a position to subvert authentication, a traditional protection +against such attacks. Authentication in the Internet is often +achieved via trusted third party authorities such as the Certificate +Authorities (CAs) that provide web sites with authentication +credentials. An attacker with sufficient resources may also be able to +induce an authority to grant credentials for an identity of the +attacker’s choosing. If the parties to a communication will trust +multiple authorities to certify a specific identity, this attack may +be mounted by suborning any one of the authorities (the proverbial +“weakest link”). Subversion of authorities in this way can allow an +active attack to succeed in spite of an authentication +check. + +Beyond these three classes (observation, inference, and active), +reports on the BULLRUN effort to defeat encryption and the PRISM +effort to obtain data from service providers suggest three more +classes of attack: + + + Static key exfiltration + Dynamic key exfiltration + Content exfiltration + + +These attacks all rely on a collaborator providing the attacker with +some information, either keys or data. These attacks have not +traditionally been considered in scope for the Security Considerations +sections of IETF protocols, as they occur outside the protocol. + +The term “key exfiltration” refers to the transfer of keying material +for an encrypted communication from the collaborator to the attacker. +By “static”, we mean that the transfer of keys happens once, or +rarely, typically of a long-lived key. For example, this case would +cover a web site operator that provides the private key corresponding +to its HTTPS certificate to an intelligence agency. + +“Dynamic” key exfiltration, by contrast, refers to attacks in which +the collaborator delivers keying material to the attacker frequently, +e.g., on a per-session basis. This does not necessarily imply +frequent communications with the attacker; the transfer of keying +material may be virtual. For example, if an endpoint were modified in +such a way that the attacker could predict the state of its +psuedorandom number generator, then the attacker would be able to +derive per-session keys even without per-session communications. + +Finally, content exfiltration is the attack in which the collaborator +simply provides the attacker with the desired data or metadata. Unlike +the key exfiltration cases, this attack does not require the attacker +to capture the desired data as it flows through the network. The exfiltration +is of data at rest, rather than data in transit. This increases the scope of data +that the attacker can obtain, since the attacker can access historical +data – the attacker does not have to be listening +at the time the communication happens. + +Exfiltration attacks can be accomplished via attacks against one of +the parties to a communication, i.e., by the attacker stealing the +keys or content rather than the party providing them willingly. In +these cases, the party may not be aware that they are collaborating, +at least at a human level. Rather, the subverted technical assets are +“collaborating” with the attacker (by providing keys/content) without +their owner’s knowledge or consent. + +Any party that has access to encryption keys or unencrypted data can +be a collaborator. While collaborators are typically the endpoints of +a communication (with encryption securing the links), intermediaries +in an unencrypted communication can also facilitate content +exfiltration attacks as collaborators by providing the attacker access +to those communications. For example, documents describing the NSA +PRISM program claim that NSA is able to access user data directly from +servers, where it is stored unencrypted. In these cases, the operator +of the server would be a collaborator, if an unwitting one. By +contrast, in the NSA MUSCULAR program, a set of collaborators enabled +attackers to access the cables connecting data centers used by service +providers such as Google and Yahoo. Because communications among +these data centers were not encrypted, the collaboration by an +intermediate entity allowed NSA to collect unencrypted user data. + +
+
+ + + Attack Class + Cost / Risk to Attacker + Passive observation + Passive data access + Passive inference + Passive data access + processing + Active + Active data access + processing + Static key exfiltration + One-time interaction + Dynamic key exfiltration + Ongoing interaction / code change + Content exfiltration + Ongoing, bulk interaction + + +Each of the attack types discussed in the previous section entails +certain costs and risks. These costs differ by attack, and can be +helpful in guiding response to pervasive attack. + +Depending on the attack, the attacker may be exposed to several types +of risk, ranging from simply losing access to arrest or prosecution. +In order for any of these negative consequences to occur, however, the +attacker must first be discovered and identified. So the primary risk +we focus on here is the risk of discovery and attribution. + +A passive pervasive attack is the simplest to mount in some ways. The base +requirement is that the attacker obtain physical access to a +communications medium and extract communications from it. For +example, the attacker might tap a fiber-optic cable, acquire a mirror +port on a switch, or listen to a wireless signal. The need for these +taps to have physical access or proximity to a link exposes the +attacker to the risk that the taps will be discovered. For example, a +fiber tap or mirror port might be discovered by network operators +noticing increased attenuation in the fiber or a change in switch +configuration. Of course, passive pervasive attacks may be accomplished +with the cooperation of the network operator, in which case there is a +risk that the attacker’s interactions with the network operator will +be exposed. + +In many ways, the costs and risks for an active pervasive attack are +similar to those for a passive pervasive attack, with a few additions. An +active attacker requires more robust network access than a +passive attacker, since for example they will often need to +transmit data as well as receiving it. In the wireless example above, +the attacker would need to act as an transmitter as well as receiver, +greatly increasing the probability the attacker will be discovered +(e.g., using direction-finding technology). Active attacks +are also much more observable at higher layers of the network. For +example, an active attacker that attempts to use a +mis-issued certificate could be detected via Certificate Transparency +. + +In terms of raw implementation complexity, passive pervasive attacks require +only enough processing to extract information from the network and +store it. Active pervasive attacks, by contrast, often depend on +winning race conditions to inject packets into active connections. So +active pervasive attacks in the core of the network require +processing hardware to that can operate at line speed (roughly 100Gbps +to 1Tbps in the core) to identify opportunities for attack and insert +attack traffic in a high-volume traffic. Key exfiltration attacks +rely on passive pervasive attack for access to encrypted data, with the +collaborator providing keys to decrypt the data. So the attacker +undertakes the cost and risk of a passive pervasive attack, as well as +additional risk of discovery via the interactions that the attacker +has with the collaborator. + +Some active attacks are more expensive than others. For example, +active man-in-the-middle (MITM) attacks require access to the entire +network session and path in order to intercept and potentially modify, +as well as drop, legitimate packets in favor of the attacker’s +packets. A similar but weaker form of attack, called an active +man-on-the-side (MOTS), does not require access to the entire session +and only part of the path. In an active MOTS attack, the attacker need +only be able to inject or modify traffic on the network element the +attacker has access to. While this may not allow for full control of a +communication session (as in an MITM attack), the attacker can perform +a number of powerful attacks, including but not limited to: injecting +packets that could terminate the session (e.g., TCP RST packets), +sending a fake DNS reply to redirect ensuing TCP connections to an +address of the attacker’s choice (i.e., winning a “DNS response +race”), and mounting an HTTP Redirect attack by observing a TCP/HTTP +connection to a target address and injecting a TCP data packet +containing an HTTP redirect. For example, the system dubbed by +researchers as China’s “Great Cannon” can operate in +ful MITM mode to accomplish very complex attacks that can modify +content in transit while the well-known Great Firewall of China is a +MOTS system that focuses on blocking access to certain kinds of +traffic and destinations via TCP RST packet injection. + +In this sense, static exfiltration has a lower risk profile than +dynamic. In the static case, the attacker need only interact with the +collaborator a small number of times, possibly only once, say to +exchange a private key. In the dynamic case, the attacker must have +continuing interactions with the collaborator. As noted above these +interactions may be real, such as in-person meetings, or virtual, such as +software modifications that render keys available to the attacker. +Both of these types of interactions introduce a risk that they will be +discovered, e.g., by employees of the collaborator organization +noticing suspicious meetings or suspicious code changes. + +Content exfiltration has a similar risk profile to dynamic key +exfiltration. In a content exfiltration attack, the attacker saves +the cost and risk of conducting a passive pervasive attack. The risk of +discovery through interactions with the collaborator, however, is +still present, and may be higher. The content of a communication is +obviously larger than the key used to encrypt it, often by several +orders of magnitude. So in the content exfiltration case, the +interactions between the collaborator and the attacker need to be much +higher-bandwidth than in the key exfiltration cases, with a +corresponding increase in the risk that this high-bandwidth channel +will be discovered. + +It should also be noted that in these latter three exfiltration cases, +the collaborator also undertakes a risk that his collaboration with +the attacker will be discovered. Thus the attacker may have to incur +additional cost in order to convince the collaborator to participate +in the attack. Likewise, the scope of these attacks is limited to +case where the attacker can convince a collaborator to participate. +If the attacker is a national government, for example, it may be able +to compel participation within its borders, but have a much more +difficult time recruiting foreign collaborators. + +As noted above, the collaborator in an exfiltration attack can be +unwitting; the attacker can steal keys or data to enable the attack. +In some ways, the risks of this approach are similar to the case of an +active collaborator. In the static case, the attacker needs to steal +information from the collaborator once; in the dynamic case, the +attacker needs to continued presence inside the collaborators systems. +The main difference is that the risk in this case is of automated +discovery (e.g., by intrusion detection systems) rather than discovery +by humans. + +
+
+
+ +This document describes a threat model for pervasive surveillance +attacks. Mitigations are to be given in a future document. + +
+
+ +This document has no actions for IANA. + +
+
+ +Thanks to Dave Thaler for the list of attacks and taxonomy; to +Security Area Directors Stephen Farrell, Sean Turner, and Kathleen +Moriarty for starting and managing the IETF’s discussion on pervasive +attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, Evangelos +Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, Russ Housley, and the IAB +Privacy and Security Program for their input. + +
+ + + + + + + + +&RFC6973; + + + + + + + + + How the NSA is still harvesting your online data + + The Guardian + + + + + + + NSA's Prism surveillance program: how it works and what it can do + + The Guardian + + + + + + + XKeyscore: NSA tool collects 'nearly everything a user does on the internet' + + The Guardian + + + + + + + How does GCHQ's internet surveillance work? + + The Guardian + + + + + + + N.S.A. Able to Foil Basic Safeguards of Privacy on Web + + The New York Times + + + + + + + Project Bullrun – classification guide to the NSA's decryption program + + The Guardian + + + + + + + Revealed: how US and UK spy agencies defeat internet privacy and security + + The Guardian + + + + + + + Tor + + The Tor Project + + + + + + + How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID + + + + + + + + + 'Tor Stinks' presentation – read the full document + + The Guardian + + + + + + + NSA collecting phone records of millions of Verizon customers daily + + The Guardian + + + + + + + NSA Prism program taps in to user data of Apple, Google and others + + The Guardian + + + + + + + Sigint – how the NSA collaborates with technology companies + + The Guardian + + + + + + + NSA surveillance: A guide to staying secure + + The Guardian + + + + + + + NSA Leak Leaves Crypto-Math Intact but Highlights Known Workarounds + + Technology Review + + + + + + + NSA's Secret Toolbox: Unit Offers Spy Gadgets for Every Need + + + + + + + + + The Digital Arms Race: NSA Preps America for Future Battle + + + + + + + + + The Design and Implementation of Protocol-Based Hidden Key Recovery + + + + + + + + + China's Great Cannon + + + + + + +&RFC1035; +&RFC1918; +&RFC1939; +&RFC2015; +&RFC2821; +&RFC3261; +&RFC3365; +&RFC3501; +&RFC3851; +&RFC4033; +&RFC4301; +&RFC4303; +&RFC4306; +&RFC4949; +&RFC5246; +&RFC5321; +&RFC5655; +&RFC5750; +&RFC6120; +&RFC6962; +&RFC6698; +&RFC7011; +&RFC7258; +&I-D.ietf-dprive-problem-statement; + + + + + + + + + diff --git a/draft-iab-privsec-confidentiality-threat-06.md b/draft-iab-privsec-confidentiality-threat-06.md new file mode 100644 index 0000000..2de04a2 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-06.md @@ -0,0 +1,1024 @@ +--- +title: "Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement" +abbrev: Confidentiality Threat Model +docname: draft-iab-privsec-confidentiality-threat-06 +date: 2015-05-11 +category: info +ipr: trust200902 + +author: + - + ins: R. Barnes + name: Richard Barnes + email: rlb@ipv.sx + - + ins: B. Schneier + name: Bruce Schneier + email: schneier@schneier.com + - + ins: C. Jennings + name: Cullen Jennings + email: fluffy@cisco.com + - + ins: T. Hardie + name: Ted Hardie + email: ted.ietf@gmail.com + - + ins: B. Trammell + name: Brian Trammell + email: ietf@trammell.ch + - + ins: C. Huitema + name: Christian Huitema + email: huitema@huitema.net + - + ins: D. Borkmann + name: Daniel Borkmann + email: dborkman@iogearbox.net + +normative: + RFC6973: + +informative: + pass1: + target: http://www.theguardian.com/world/2013/jun/27/nsa-online-metadata-collection + title: "How the NSA is still harvesting your online data" + author: + organization: The Guardian + date: 2013 + pass2: + target: http://www.theguardian.com/world/2013/jun/08/nsa-prism-server-collection-facebook-google + title: "NSA's Prism surveillance program: how it works and what it can do" + author: + organization: The Guardian + date: 2013 + pass3: + target: http://www.theguardian.com/world/2013/jul/31/nsa-top-secret-program-online-data + title: "XKeyscore: NSA tool collects 'nearly everything a user does on the internet'" + author: + organization: The Guardian + date: 2013 + pass4: + target: http://www.theguardian.com/uk/2013/jun/21/how-does-gchq-internet-surveillance-work + title: "How does GCHQ's internet surveillance work?" + author: + organization: The Guardian + dec1: + target: http://www.nytimes.com/2013/09/06/us/nsa-foils-much-internet-encryption.html + title: "N.S.A. Able to Foil Basic Safeguards of Privacy on Web" + author: + organization: The New York Times + date: 2013 + dec2: + target: http://www.theguardian.com/world/interactive/2013/sep/05/nsa-project-bullrun-classification-guide + title: "Project Bullrun – classification guide to the NSA's decryption program" + author: + organization: The Guardian + date: 2013 + dec3: + target: http://www.theguardian.com/world/2013/sep/05/nsa-gchq-encryption-codes-security + title: "Revealed: how US and UK spy agencies defeat internet privacy and security" + author: + organization: The Guardian + date: 2013 + TOR: + target: https://www.torproject.org/ + title: "Tor" + author: + organization: The Tor Project + date: 2013 + TOR1: + target: https://www.schneier.com/blog/archives/2013/10/how_the_nsa_att.html + title: "How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID" + author: + name: Bruce Schneier + ins: B. Schneier + date: 2013 + TOR2: + target: http://www.theguardian.com/world/interactive/2013/oct/04/tor-stinks-nsa-presentation-document + title: "'Tor Stinks' presentation – read the full document" + author: + organization: The Guardian + date: 2013 + dir1: + target: http://www.theguardian.com/world/2013/jun/06/nsa-phone-records-verizon-court-order + title: "NSA collecting phone records of millions of Verizon customers daily" + author: + organization: The Guardian + date: 2013 + dir2: + target: http://www.theguardian.com/world/2013/jun/06/us-tech-giants-nsa-data + title: "NSA Prism program taps in to user data of Apple, Google and others" + author: + organization: The Guardian + date: 2013 + dir3: + target: http://www.theguardian.com/world/interactive/2013/sep/05/sigint-nsa-collaborates-technology-companies + title: "Sigint – how the NSA collaborates with technology companies" + author: + organization: The Guardian + date: 2013 + secure: + target: http://www.theguardian.com/world/2013/sep/05/nsa-how-to-remain-secure-surveillance + title: "NSA surveillance: A guide to staying secure" + author: + name: Bruce Schneier + ins: B. Schneier + organization: The Guardian + date: 2013 + snowden: + target: http://www.technologyreview.com/news/519171/nsa-leak-leaves-crypto-math-intact-but-highlights-known-workarounds/ + title: "NSA Leak Leaves Crypto-Math Intact but Highlights Known Workarounds" + author: + organization: Technology Review + date: 2013 + spiegel1: + target: http://www.spiegel.de/international/world/nsa-secret-toolbox-ant-unit-offers-spy-gadgets-for-every-need-a-941006.html + title: "NSA's Secret Toolbox: Unit Offers Spy Gadgets for Every Need" + author: + ins: J Applebaum + name: Jacob Applebaum + author: + ins: J Horchert + name: Judith Horchert + author: + ins: O Reissmann + name: Ole Reissmann + author: + ins: M Rosenbach + name: Marcel Rosenbach + author: + ins: J Schindler + name: Jorg Schindler + author: + ins: C Stocker + name: Christian Stocker + date: 2013-12-30 + spiegel3: + target: http://www.spiegel.de/international/world/new-snowden-docs-indicate-scope-of-nsa-preparations-for-cyber-battle-a-1013409.html + title: "The Digital Arms Race: NSA Preps America for Future Battle" + author: + ins: J Appelbaum + name: Jacob Appelbaum + author: + ins: A Gibson + name: Aaron Gibson + author: + ins: C Guarnieri + name: Claudio Guarnieri + author: + ins: A Muller-Maguhn + name: Andy Muller-Maguhn + author: + ins: M Sontheimer + name: Michael Sontheimer + author: + ins: L Poitras + name: Laura Poitras + author: + ins: M Rosenbach + name: Marcel Rosenbach + author: + ins: L Ryge + name: Leif Ryge + author: + ins: H Schmundt + name: Hilmar Schmundt + date: 2014-01-17 + key-recovery: + target: http://crypto.stanford.edu/~pgolle/papers/escrow.pdf + title: The Design and Implementation of Protocol-Based Hidden Key Recovery + author: + ins: E.-J. Goh + name: Eu-Jin Goh + author: + ins: D. Boneh + name: Dan Boneh + author: + ins: B. Pinkas + name: Benny Pinkas + author: + ins: P. Golle + name: Phillippe Golle + date: 2003 + great-cannon: + target: https://citizenlab.org/2015/04/chinas-great-cannon/ + title: "China's Great Cannon" + author: + name: Bill Marczak + ins: B. Marczak + author: + name: Nicholas Weaver + ins: N. Weaver + author: + name: Jakub Dalek + ins: J. Dalek + author: + name: Roya Ensafi + ins: R. Ensafi + author: + name: David Fifield + ins: D. Fifield + author: + name: Sarah McKune + ins: S. McKune + author: + name: Arn Rey + ins: A. Rey + author: + name: John Scott-Railton + ins: J. Scott-Railton + author: + name: Ronald Deibert + ins: R. Deibert + author: + name: Vern Paxson + ins: V. Paxson + date: 2015 + RFC1035: + RFC1918: + RFC1939: + RFC2015: + RFC2821: + RFC3261: + RFC3365: + RFC3501: + RFC3851: + RFC4033: + RFC4301: + RFC4303: + RFC4306: + RFC4949: + RFC5246: + RFC5321: + RFC5655: + RFC5750: + RFC6120: + RFC6962: + RFC6698: + RFC7011: + RFC7258: + I-D.ietf-dprive-problem-statement: + +--- abstract + + Since the initial revelations of pervasive surveillance in 2013, + several classes of attacks on Internet communications have been + discovered. In this document we develop a threat model that + describes these attacks on Internet confidentiality. We assume an + attacker that is interested in undetected, indiscriminate + eavesdropping. The threat model is based on published, verified + attacks. + + +--- middle + +# Introduction + +Starting in June 2013, documents released to the press by Edward +Snowden have revealed several operations undertaken by intelligence +agencies to exploit Internet communications for intelligence purposes. +These attacks were largely based on protocol vulnerabilities that were +already known to exist. The attacks were nonetheless striking in +their pervasive nature, both in terms of the amount of Internet +communications targeted, and in terms of the diversity of attack +techniques employed. + +To ensure that the Internet can be trusted by users, it is necessary +for the Internet technical community to address the vulnerabilities +exploited in these attacks {{RFC7258}}. The goal of this document is +to describe more precisely the threats posed by these pervasive +attacks, and based on those threats, lay out the problems that need to +be solved in order to secure the Internet in the face of those +threats. + +The remainder of this document is structured as follows. In +{{adversary}}, we describe an idealized passive pervasive attacker, one which +could completely undetectably compromise communications at Internet +scale. In {{reported}}, we provide a brief summary of some attacks +that have been disclosed, and use these to expand the assumed +capabilities of our idealized attacker. Note that we do not attempt +to describe all possible attacks, but focus on those which result in +undetected eavesdropping. {{model}} describes a threat model based on +these attacks, focusing on classes of attack that have not been a +focus of Internet engineering to date. + +# Terminology {#terminology} + +This document makes extensive use of standard security and privacy +terminology; see {{RFC4949}} and {{RFC6973}}. Terms used from +{{RFC6973}} include Eavesdropper, Observer, Initiator, Intermediary, +Recipient, Attack (in a privacy context), Correlation, Fingerprint, +Traffic Analysis, and Identifiability (and related terms). In +addition, we use a few terms that are specific to the attacks +discussed in this document. Note especially that "passive" and "active" below +do not refer to the effort used to mount the attack; a "passive attack" +is any attack that accesses a flow but does not modify it, while an +"active attack" is any attack that modifies a flow. Some passive attacks +involve active interception and modifications of devices, rather than simple +access to the medium. The introduced terms are: + +Pervasive Attack: +: An attack on Internet communications that makes +use of access at a large number of points in the network, or otherwise +provides the attacker with access to a large amount of Internet +traffic; see {{RFC7258}}. + +Passive Pervasive Attack: +: An eavesdropping attack undertaken by a pervasive attacker, in which the +packets in a traffic stream between two endpoints are intercepted, but +in which the attacker does not modify the packets in the traffic +stream between two endpoints, modify the treatment of packets in the +traffic stream (e.g. delay, routing), or add or remove packets in the +traffic stream. Passive pervasive attacks are undetectable from the +endpoints. Equivalent to passive wiretapping as defined in {{RFC4949}}; +we use an alternate term here since the methods employed are wider +than those implied by the word "wiretapping", including the active +compromise of intermediate systems. + +Active Pervasive Attack: +: An attack undertaken by a pervasive attacker, which in addition to +the elements of a passive pervasive attack, also includes modification, +addition, or removal of +packets in a traffic stream, or modification of treatment of packets +in the traffic stream. Active pervasive attacks provide more +capabilities to the attacker at the risk of possible detection at the +endpoints. Equivalent to active wiretapping as defined in {{RFC4949}}. + +Observation: +: Information collected directly from communications by an +eavesdropper or observer. For example, the knowledge that +<alice@example.com> sent a message to <bob@example.com> +via SMTP taken from the headers of an observed SMTP message would be +an observation. + +Inference: +: Information extracted from analysis of information collected +directly from communications by an eavesdropper or observer. For +example, the knowledge that a given web page was accessed by a given +IP address, by comparing the size in octets of measured network flow +records to fingerprints derived from known sizes of linked resources +on the web servers involved, would be an inference. + +Collaborator: +: An entity that is a legitimate participant in a communication, but +who deliberately provides information about that interaction to an +attacker. + +Unwitting Collaborator: +: An entity that is a legitimate participant in a communication, and +who is the source of information obtained by the attacker without the +entity's consent or intention, because the attacker has exploited some +technology used by the entity. + +Key Exfiltration: +: The transmission of cryptographic keying material for an encrypted communication +from a collaborator, deliberately or unwittingly, to an attacker. + +Content Exfiltration: +: The transmission of the content of a communication from a collaborator, deliberately or unwittingly, to an attacker + +# An Idealized Passive Pervasive Attacker {#adversary} + +In considering the threat posed by pervasive surveillance, we begin by +defining an idealized passive pervasive attacker. While this attacker +is less capable than those which we now know to have compromised the +Internet from press reports, as elaborated in {{reported}}, it does +set a lower bound on the capabilities of an attacker interested in +indiscriminate passive surveillance while interested in remaining +undetectable. We note that, prior to the Snowden revelations in 2013, +the assumptions of attacker capability presented here would be +considered on the border of paranoia outside the network security +community. + +Our idealized attacker is an indiscriminate eavesdropper on an Internet-attached computer network that: + +- can observe every packet of all communications at any hop in any network path between an initiator and a recipient; +- can observe data at rest in any intermediate system between the endpoints controlled by the initiator and recipient; and +- can share information with other such attackers; but +- takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.). + + The techniques available to our ideal attacker are direct observation + and inference. Direct observation involves taking information + directly from eavesdropped communications, such as URLs identifying + content or email addresses identifying individuals from application- + layer headers. Inference, on the other hand, involves analyzing + observed information to derive new information, such as searching for + application or behavioral fingerprints in observed traffic to derive + information about the observed individual. The use of encryption is + generally sufficient to provide confidentiality by preventing direct + observation of content, assuming of course, uncompromised encryption + implementations and cryptographic keying material. However, + encryption provides less complete protection against inference, + especially inferences based only on plaintext portions of + communications, such as IP and TCP headers for TLS-protected traffic + [RFC5246]). + +## Information subject to direct observation + +Protocols which do not encrypt their payload make the entire content +of the communication available to the idealized attacker along their +path. Following the advice in {{RFC3365}}, most such protocols have a +secure variant which encrypts payload for confidentiality, and these +secure variants are seeing ever-wider deployment. A noteworthy +exception is DNS {{RFC1035}}, as DNSSEC {{RFC4033}} does not have +confidentiality as a requirement. + +This implies that, in the absence of +changes to the protocol as presently under development in the IETF's +DNS Private Exchange (DPRIVE) +working group {{I-D.ietf-dprive-problem-statement}}, all DNS queries and answers generated by the activities +of any protocol are available to the attacker. + +When store-and-forward protocols are used, (e.g. SMTP {{RFC5321}}) +intermediaries leave this data subject to observation by an attacker that +has compromised these intermediaries, +unless the data is encrypted end-to-end by the application layer +protocol, or the implementation uses an encrypted store for this data. + +## Information useful for inference + +Inference is information extracted from later analysis of an observed +or eavesdropped communication, and/or correlation of observed or +eavesdropped information with information available from other +sources. Indeed, most useful inference performed by the attacker falls +under the rubric of correlation. The simplest example of this is the +observation of DNS queries and answers from and to a source and +correlating those with IP addresses with which that source +communicates. This can give access to information otherwise not +available from encrypted application payloads (e.g., the Host: +HTTP/1.1 request header when HTTP is used with TLS). + +Protocols which encrypt their payload using an application- or +transport-layer encryption scheme (e.g. TLS) still expose all the +information in their network and transport layer headers to the +attacker, including source and destination addresses and ports. IPsec +ESP{{RFC4303}} further encrypts the transport-layer headers, but still +leaves IP address information unencrypted; in tunnel mode, these +addresses correspond to the tunnel endpoints. Features of the +security protocols themselves, e.g. the TLS session identifier, +may leak information that can be used for correlation and +inference. While this information is much less semantically rich than +the application payload, it can still be useful for the inferring an +individual's activities. + +Inference can also leverage information obtained from sources other +than direct traffic observation. Geolocation databases, for example, +have been developed that map IP addresses to a location, in order to +provide location-aware services such as targeted advertising. This +location information is often of sufficient resolution that it can be +used to draw further inferences toward identifying or profiling an +individual. + +Social media provide another source of more or less publicly +accessible information. This information can be extremely semantically +rich, including information about an individual's location, +associations with other individuals and groups, and +activities. Further, this information is generally contributed and +curated voluntarily by the individuals themselves: it represents +information which the individuals are not necessarily interested in +protecting for privacy reasons. However, correlation of this social +networking data with information available from direct observation of +network traffic allows the creation of a much richer picture of an +individual's activities than either alone. + +We note with some alarm that there is little that can be done at +protocol design time to limit such correlation by the attacker, and +that the existence of such data sources in many cases greatly +complicates the problem of protecting privacy by hardening protocols +alone. + +## An illustration of an ideal passive pervasive attack + +To illustrate how capable the idealized attacker is even given its +limitations, we explore the non-anonymity of encrypted IP traffic in +this section. Here we examine in detail some inference techniques for +associating a set of addresses with an individual, in order to +illustrate the difficulty of defending communications against our +idealized attacker. Here, the basic problem is that information +radiated even from protocols which have no obvious connection with +personal data can be correlated with other information which can paint +a very rich behavioral picture, that only takes one unprotected link +in the chain to associate with an identity. + +### Analysis of IP headers + +Internet traffic can be monitored by tapping Internet links, or by +installing monitoring tools in Internet routers. Of course, a single +link or a single router only provides access to a fraction of the +global Internet traffic. However, monitoring a number of high capacity +links or a set of routers placed at strategic locations provides +access to a good sampling of Internet traffic. + +Tools like IPFIX {{RFC7011}} allow administrators to acquire +statistics about sequences of packets with some common properties that +pass through a network device. The most common set of properties used +in flow measurement is the "five-tuple"of source and destination +addresses, protocol type, and source and destination ports. These +statistics are commonly used for network engineering, but could +certainly be used for other purposes. + +Let's assume for a moment that IP addresses can be correlated to +specific services or specific users. Analysis of the sequences of +packets will quickly reveal which users use what services, and also +which users engage in peer-to-peer connections with other +users. Analysis of traffic variations over time can be used to detect +increased activity by particular users, or in the case of peer-to-peer +connections increased activity within groups of users. + +### Correlation of IP addresses to user identities + +The correlation of IP addresses with specific users can be done in +various ways. For example, tools like reverse DNS lookup can be used +to retrieve the DNS names of servers. Since the addresses of servers +tend to be quite stable and since servers are relatively less numerous +than users, an attacker could easily maintain its own copy of the DNS +for well-known or popular servers, to accelerate such lookups. + +On the other hand, the reverse lookup of IP addresses of users is +generally less informative. For example, a lookup of the address +currently used by one author's home network returns a name of the form +"c-192-000-002-033.hsd1.wa.comcast.net". This particular type of +reverse DNS lookup generally reveals only coarse-grained location or +provider information, equivalent to that available from geolocation +databases. + +In many jurisdictions, Internet Service Providers (ISPs) are required +to provide identification on a case by case basis of the "owner" of a +specific IP address for law enforcement purposes. This is a reasonably +expedient process for targeted investigations, but pervasive +surveillance requires something more efficient. This provides an +incentive for the attacker to secure the cooperation of the ISP in +order to automate this correlation. + +### Monitoring messaging clients for IP address correlation + +Even if the ISP does not cooperate, user identity can often be +obtained via inference. POP3 {{RFC1939}} and IMAP {{RFC3501}} are used +to retrieve mail from mail servers, while a variant of SMTP is used to +submit messages through mail servers. IMAP connections originate from +the client, and typically start with an authentication exchange in +which the client proves its identity by answering a password +challenge. The same holds for the SIP protocol {{RFC3261}} and many +instant messaging services operating over the Internet using +proprietary protocols. + +The username is directly observable if any of these protocols operate +in cleartext; the username can then be directly associated with the +source address. + +### Retrieving IP addresses from mail headers + +SMTP {{RFC5321}} requires that each successive SMTP relay adds a +"Received" header to the mail headers. The purpose of these headers is +to enable audit of mail transmission, and perhaps to distinguish +between regular mail and spam. Here is an extract from the headers of +a message recently received from the "perpass" mailing list: + +``` + Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?) + (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA + (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100 + Message-ID: <526D7BD2.7070908@example.org> + Date: Sun, 27 Oct 2013 20:47:14 +0000 + From: Some One +``` + +This is the first "Received" header attached to the message by the +first SMTP relay; for privacy reasons, the field values have been +anonymized. We learn here that the message was submitted by "Some One" +on October 27, from a host behind a NAT (192.168.1.100) {{RFC1918}} +that used the IP address 192.0.2.44. The information remained in the +message, and is accessible by all recipients of the "perpass" mailing +list, or indeed by any attacker that sees at least one copy of the +message. + +An attacker that can observe sufficient email traffic can regularly +update the mapping between public IP addresses and individual email +identities. Even if the SMTP traffic was encrypted on submission and +relaying, the attacker can still receive a copy of public mailing +lists like "perpass". + +### Tracking address usage with web cookies + +Many web sites only encrypt a small fraction of their transactions. A +popular pattern is to use HTTPS for the login information, and then +use a "cookie" to associate following clear-text transactions with the +user's identity. Cookies are also used by various advertisement +services to quickly identify the users and serve them with +"personalized" advertisements. Such cookies are particularly useful if +the advertisement services want to keep tracking the user across +multiple sessions that may use different IP addresses. + +As cookies are sent in clear text, an attacker can build a database +that associates cookies to IP addresses for non-HTTPS traffic. If the +IP address is already identified, the cookie can be linked to the user +identify. After that, if the same cookie appears on a new IP address, +the new IP address can be immediately associated with the +pre-determined identity. + +### Graph-based approaches to address correlation + +An attacker can track traffic from an IP address not yet associated +with an individual to various public services (e.g. websites, mail +servers, game servers), and exploit patterns in the observed traffic +to correlate this address with other addresses that show similar +patterns. For example, any two addresses that show connections to the +same IMAP or webmail services, the same set of favorite websites, and +game servers at similar times of day may be associated with the same +individual. Correlated addresses can then be tied to an individual +through one of the techniques above, walking the "network graph" to +expand the set of attributable traffic. + +### Tracking of Link Layer Identifiers + +Moving back down the stack, technologies like Ethernet or Wi-Fi use MAC Addresses to identify link-level destinations. MAC Addresses assigned according to IEEE-802 standards are globally-unique identifiers for the device. If the link is publicly accessible, an attacker can eavesdrop and perform tracking. For example, the attacker can track the wireless traffic at publicly accessible Wi-Fi networks. Simple devices can monitor the traffic, and reveal which MAC Addresses are present. +Also, devices do not need to be connected to a network to expose link-layer identifiers. Active service discovery always discloses the MAC address of the user, and sometimes the SSIDs of previously visited networks. For instance, certain techniques such as the use of “hidden SSIDs” require the mobile device to broadcast the network identifier together with the device identifier. This combination can further expose the user to inference attacks, as more information can be derived from the combination of MAC address, SSID being probed, time and current location. For example, a user actively probing for a semi-unique SSID on a flight out of a certain city can imply that the user is no longer at the physical location of the corresponding AP. +Given that large-scale databases of the MAC addresses of wireless access points for geolocation purposes have been known to exist for some time, the attacker could easily build a database linking link-layer identifiers, time and device or user identities, and use it to track the movement of devices and of their owners. +On the other hand, if the network does not use some form of Wi-Fi encryption, or if the attacker can access the decrypted traffic, the analysis will also provide the correlation between link-layer identifiers such as MAC Addresses and IP addresses. Additional monitoring using techniques exposed in the previous sections will reveal the correlation between MAC addresses, IP addresses, and user identity. For instance, similarly to the use of web cookies, MAC addresses provide identity information that can be used to associate a user to different IP addresses. + +# Reported Instances of Large-Scale Attacks {#reported} + +The situation in reality is more bleak than that suggested by an +analysis of our idealized attacker. Through revelations of sensitive +documents in several media outlets, the Internet community has been +made aware of several intelligence activities conducted by US and UK +national intelligence agencies, particularly the US National Security +Agency (NSA) and the UK Government Communications Headquarters +(GCHQ). These documents have revealed methods that these agencies use +to attack Internet applications and obtain sensitive user information. +We note that these reports are primarily useful as an illustration of +the types of capabilities fielded by pervasive attackers as of the +date of the Snowden leaks in 2013. + +First, they confirm the deployment of large-scale passive +collection of Internet traffic, which confirms the existence of +pervasive passive attackers with at least the capabilities of our +idealized attacker. For example {{pass1}}{{pass2}}{{pass3}}{{pass4}}: + +- NSA's XKEYSCORE system accesses data from multiple access points and +searches for "selectors" such as email addresses, at the scale of tens +of terabytes of data per day. + +- GCHQ's Tempora system appears to have access to around 1,500 major cables +passing through the UK. + +- NSA's MUSCULAR program has tapped cables between data centers +belonging to major service providers. + +- Several programs appear to perform wide-scale collection +of cookies in web traffic and location data from location-aware +portable devices such as smartphones. + +However, the capabilities described by these reports go beyond those of our +idealized attacker. They include the compromise of cryptographic protocols, +including decryption of TLS-protected Internet sessions {{dec1}}{{dec2}}{{dec3}}. +For example, the NSA BULLRUN project worked to undermine encryption through +multiple approaches, including covert modifications to cryptographic +software on end systems. + +Reported capabilities include the direct compromise of intermediate systems +and arrangements with service providers for bulk data and metadata +access {{dir1}}{{dir2}}{{dir3}}, bypassing the need to capture +traffic on the wire. For example, the NSA PRISM program provides the +agency with access to many types of user data (e.g., email, chat, VoIP). + +The reported capabilities also include elements of active pervasive attack, +including: + +* Insertion of devices as a man-in-the-middle of Internet + transactions {{TOR1}}{{TOR2}}. For example, NSA's QUANTUM system + appears to use several different techniques to hijack HTTP + connections, ranging from DNS response injection to HTTP 302 + redirects. + +* Use of implants on end systems to undermine security and anonymity + features {{dec2}}{{TOR1}}{{TOR2}}. For example, QUANTUM is used to + direct users to a FOXACID server, which in turn delivers an implant + to compromise browsers of Tor users. + +* Use of implants on network elements from many major equipment providers, + including Cisco, Juniper, Huawei, Dell, and HP, as provided by the NSA's + Advanced Network Technology group. {{spiegel1}} + +* Use of botnet-scale collections of compromised hosts {{spiegel3}}. + +The scale of the compromise extends beyond the network to include subversion of the technical standards process itself. For example, there is suspicion that NSA modifications to the DUAL_EC_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA. This RNG was made part of NIST's SP 800-90A, for which NIST acknowledges NSA's assistance. There have also been reports that the NSA paid RSA Security for a related contract with the result that the curve became the default in the RSA BSAFE product line. + +We use the term "pervasive attack" {{RFC7258}} to collectively +describe these operations. The term "pervasive" is used because the +attacks are designed to indiscriminately gather as much data as +possible and to apply selective analysis on targets after the fact. +This means that all, or nearly all, Internet communications are +targets for these attacks. To achieve this scale, the attacks are +physically pervasive; they affect a large number of Internet +communications. They are pervasive in content, consuming and +exploiting any information revealed by the protocol. And they are +pervasive in technology, exploiting many different vulnerabilities in +many different protocols. + +It's important to note that although the attacks mentioned above were +executed by NSA and GCHQ, there are many other organizations that can +mount pervasive surveillance attacks. Because of the resources +required to achieve pervasive scale, these attacks are most commonly +undertaken by nation-state actors. For example, the Chinese Internet +filtering system known as the "Great Firewall of China" uses several +techniques that are similar to the QUANTUM program, and which have a +high degree of pervasiveness with regard to the Internet in China. + +# Threat Model {#model} + +Given these disclosures, we must consider a broader threat model. + +Pervasive surveillance aims to collect information across a large +number of Internet communications, analyzing the collected +communications to identify information of interest within individual +communications, or inferring information from correlated +communications. This analysis sometimes benefits from decryption of +encrypted communications and deanonymization of anonymized +communications. As a result, these attackers desire both access to +the bulk of Internet traffic and to the keying material required to +decrypt any traffic that has been encrypted. Even if keys are not +available, note that the presence of a communication and the fact that +it is encrypted may both be inputs to an analysis, even if the +attacker cannot decrypt the communication. + +The attacks listed above highlight new avenues both for access to +traffic and for access to relevant encryption keys. They further +indicate that the scale of surveillance is sufficient to provide a +general capability to cross-correlate communications, a threat not +previously thought to be relevant at the scale of the Internet. + +## Attacker Capabilities + +| Attack Class | Capability | +|:--------------------------|:------------------------------------------| +| Passive observation | Directly capture data in transit | +| Passive inference | Infer from reduced/encrypted data | +| Active | Manipulate / inject data in transit | +| Static key exfiltration | Obtain key material once / rarely | +| Dynamic key exfiltration | Obtain per-session key material | +| Content exfiltration | Access data at rest | + +Security analyses of Internet protocols commonly consider two classes +of attacker: Passive pervasive attackers, who can simply listen in on +communications as they transit the network, and active pervasive +attackers, who can modify or delete packets in addition to simply +collecting them. + +In the context of pervasive passive surveillance, these attacks take +on an even greater significance. In the past, these attackers were +often assumed to operate near the edge of the network, where attacks +can be simpler. For example, in some LANs, it is simple for any node +to engage in passive listening to other nodes' traffic or inject +packets to accomplish active pervasive attacks. However, as we now +know, both passive and active pervasive attacks are undertaken by +pervasive attackers closer to the core of the network, greatly +expanding the scope and capability of the attacker. + +Eavesdropping and observation at a larger scale make passive inference +attacks easier to carry out: a passive pervasive attacker with access to a +large portion of the Internet can analyze collected traffic to create +a much more detailed view of individual behavior than an attacker that +collects at a single point. Even the usual claim that encryption +defeats passive pervasive attackers is weakened, since a pervasive flow +access attacker can infer relationships from correlations over large +numbers of sessions, e.g., pairing encrypted sessions with unencrypted +sessions from the same host, or performing traffic fingerprinting +between known and unknown encrypted sessions. Reports on the NSA +XKEYSCORE system would indicate it is an example of such an attacker. + +An active pervasive attacker likewise has capabilities +beyond those of a localized active attacker. Flow +modification attacks are often limited by network topology, for +example by a requirement that the attacker be able to see a targeted +session as well as inject packets into it. A pervasive flow +modification attacker with access at multiple points within the core +of the Internet is able to overcome these topological limitations and +perform attacks over a much broader scope. Being positioned in the +core of the network rather than the edge can also enable an active +pervasive attacker to reroute targeted traffic, amplifying the +ability to perform both eavesdropping and traffic injection. +Active pervasive attackers can also benefit from passive pervasive +collection to identify vulnerable hosts. + +While not directly related to pervasiveness, attackers that are in a +position to mount a active pervasive attack are also often +in a position to subvert authentication, a traditional protection +against such attacks. Authentication in the Internet is often +achieved via trusted third party authorities such as the Certificate +Authorities (CAs) that provide web sites with authentication +credentials. An attacker with sufficient resources may also be able to +induce an authority to grant credentials for an identity of the +attacker’s choosing. If the parties to a communication will trust +multiple authorities to certify a specific identity, this attack may +be mounted by suborning any one of the authorities (the proverbial +"weakest link"). Subversion of authorities in this way can allow an +active attack to succeed in spite of an authentication +check. + +Beyond these three classes (observation, inference, and active), +reports on the BULLRUN effort to defeat encryption and the PRISM +effort to obtain data from service providers suggest three more +classes of attack: + +* Static key exfiltration +* Dynamic key exfiltration +* Content exfiltration + +These attacks all rely on a collaborator providing the attacker with +some information, either keys or data. These attacks have not +traditionally been considered in scope for the Security Considerations +sections of IETF protocols, as they occur outside the protocol. + +The term "key exfiltration" refers to the transfer of keying material +for an encrypted communication from the collaborator to the attacker. +By "static", we mean that the transfer of keys happens once, or +rarely, typically of a long-lived key. For example, this case would +cover a web site operator that provides the private key corresponding +to its HTTPS certificate to an intelligence agency. + +"Dynamic" key exfiltration, by contrast, refers to attacks in which +the collaborator delivers keying material to the attacker frequently, +e.g., on a per-session basis. This does not necessarily imply +frequent communications with the attacker; the transfer of keying +material may be virtual. For example, if an endpoint were modified in +such a way that the attacker could predict the state of its +psuedorandom number generator, then the attacker would be able to +derive per-session keys even without per-session communications. + +Finally, content exfiltration is the attack in which the collaborator +simply provides the attacker with the desired data or metadata. Unlike +the key exfiltration cases, this attack does not require the attacker +to capture the desired data as it flows through the network. The exfiltration +is of data at rest, rather than data in transit. This increases the scope of data +that the attacker can obtain, since the attacker can access historical +data -- the attacker does not have to be listening +at the time the communication happens. + +Exfiltration attacks can be accomplished via attacks against one of +the parties to a communication, i.e., by the attacker stealing the +keys or content rather than the party providing them willingly. In +these cases, the party may not be aware that they are collaborating, +at least at a human level. Rather, the subverted technical assets are +"collaborating" with the attacker (by providing keys/content) without +their owner's knowledge or consent. + +Any party that has access to encryption keys or unencrypted data can +be a collaborator. While collaborators are typically the endpoints of +a communication (with encryption securing the links), intermediaries +in an unencrypted communication can also facilitate content +exfiltration attacks as collaborators by providing the attacker access +to those communications. For example, documents describing the NSA +PRISM program claim that NSA is able to access user data directly from +servers, where it is stored unencrypted. In these cases, the operator +of the server would be a collaborator, if an unwitting one. By +contrast, in the NSA MUSCULAR program, a set of collaborators enabled +attackers to access the cables connecting data centers used by service +providers such as Google and Yahoo. Because communications among +these data centers were not encrypted, the collaboration by an +intermediate entity allowed NSA to collect unencrypted user data. + +## Attacker Costs + +| Attack Class | Cost / Risk to Attacker | +|:--------------------------|:----------------------------------| +| Passive observation | Passive data access | +| Passive inference | Passive data access + processing | +| Active | Active data access + processing | +| Static key exfiltration | One-time interaction | +| Dynamic key exfiltration | Ongoing interaction / code change | +| Content exfiltration | Ongoing, bulk interaction | + +Each of the attack types discussed in the previous section entails +certain costs and risks. These costs differ by attack, and can be +helpful in guiding response to pervasive attack. + +Depending on the attack, the attacker may be exposed to several types +of risk, ranging from simply losing access to arrest or prosecution. +In order for any of these negative consequences to occur, however, the +attacker must first be discovered and identified. So the primary risk +we focus on here is the risk of discovery and attribution. + +A passive pervasive attack is the simplest to mount in some ways. The base +requirement is that the attacker obtain physical access to a +communications medium and extract communications from it. For +example, the attacker might tap a fiber-optic cable, acquire a mirror +port on a switch, or listen to a wireless signal. The need for these +taps to have physical access or proximity to a link exposes the +attacker to the risk that the taps will be discovered. For example, a +fiber tap or mirror port might be discovered by network operators +noticing increased attenuation in the fiber or a change in switch +configuration. Of course, passive pervasive attacks may be accomplished +with the cooperation of the network operator, in which case there is a +risk that the attacker's interactions with the network operator will +be exposed. + +In many ways, the costs and risks for an active pervasive attack are +similar to those for a passive pervasive attack, with a few additions. An +active attacker requires more robust network access than a +passive attacker, since for example they will often need to +transmit data as well as receiving it. In the wireless example above, +the attacker would need to act as an transmitter as well as receiver, +greatly increasing the probability the attacker will be discovered +(e.g., using direction-finding technology). Active attacks +are also much more observable at higher layers of the network. For +example, an active attacker that attempts to use a +mis-issued certificate could be detected via Certificate Transparency +{{RFC6962}}. + +In terms of raw implementation complexity, passive pervasive attacks require +only enough processing to extract information from the network and +store it. Active pervasive attacks, by contrast, often depend on +winning race conditions to inject packets into active connections. So +active pervasive attacks in the core of the network require +processing hardware to that can operate at line speed (roughly 100Gbps +to 1Tbps in the core) to identify opportunities for attack and insert +attack traffic in a high-volume traffic. Key exfiltration attacks +rely on passive pervasive attack for access to encrypted data, with the +collaborator providing keys to decrypt the data. So the attacker +undertakes the cost and risk of a passive pervasive attack, as well as +additional risk of discovery via the interactions that the attacker +has with the collaborator. + +Some active attacks are more expensive than others. For example, active +man-in-the-middle (MITM) attacks require access to one or more points on a +communication's network path that allow visibility of the entire session and +the ability to modify or drop legitimate packets in favor of the attacker's +packets. A similar but weaker form of attack, called an active +man-on-the-side (MOTS), requires access to only part of the session. In an +active MOTS attack, the attacker need only be able to inject or modify traffic +on the network element the attacker has access to. While this may not allow +for full control of a communication session (as in an MITM attack), the +attacker can perform a number of powerful attacks, including but not limited +to: injecting packets that could terminate the session (e.g., TCP RST +packets), sending a fake DNS reply to redirect ensuing TCP connections to an +address of the attacker's choice (i.e., winning a "DNS response race"), and +mounting an HTTP Redirect attack by observing a TCP/HTTP connection to a +target address and injecting a TCP data packet containing an HTTP redirect. +For example, the system dubbed by researchers as China's "Great Cannon" +{{great-cannon}} can operate in ful MITM mode to accomplish very complex +attacks that can modify content in transit while the well-known Great Firewall +of China is a MOTS system that focuses on blocking access to certain kinds of +traffic and destinations via TCP RST packet injection. + +In this sense, static exfiltration has a lower risk profile than +dynamic. In the static case, the attacker need only interact with the +collaborator a small number of times, possibly only once, say to +exchange a private key. In the dynamic case, the attacker must have +continuing interactions with the collaborator. As noted above these +interactions may be real, such as in-person meetings, or virtual, such as +software modifications that render keys available to the attacker. +Both of these types of interactions introduce a risk that they will be +discovered, e.g., by employees of the collaborator organization +noticing suspicious meetings or suspicious code changes. + +Content exfiltration has a similar risk profile to dynamic key +exfiltration. In a content exfiltration attack, the attacker saves +the cost and risk of conducting a passive pervasive attack. The risk of +discovery through interactions with the collaborator, however, is +still present, and may be higher. The content of a communication is +obviously larger than the key used to encrypt it, often by several +orders of magnitude. So in the content exfiltration case, the +interactions between the collaborator and the attacker need to be much +higher-bandwidth than in the key exfiltration cases, with a +corresponding increase in the risk that this high-bandwidth channel +will be discovered. + +It should also be noted that in these latter three exfiltration cases, +the collaborator also undertakes a risk that his collaboration with +the attacker will be discovered. Thus the attacker may have to incur +additional cost in order to convince the collaborator to participate +in the attack. Likewise, the scope of these attacks is limited to +case where the attacker can convince a collaborator to participate. +If the attacker is a national government, for example, it may be able +to compel participation within its borders, but have a much more +difficult time recruiting foreign collaborators. + +As noted above, the collaborator in an exfiltration attack can be +unwitting; the attacker can steal keys or data to enable the attack. +In some ways, the risks of this approach are similar to the case of an +active collaborator. In the static case, the attacker needs to steal +information from the collaborator once; in the dynamic case, the +attacker needs to continued presence inside the collaborators systems. +The main difference is that the risk in this case is of automated +discovery (e.g., by intrusion detection systems) rather than discovery +by humans. + +# Security Considerations + +This document describes a threat model for pervasive surveillance +attacks. Mitigations are to be given in a future document. + +# IANA Considerations + +This document has no actions for IANA. + +# Acknowledgements + +Thanks to Dave Thaler for the list of attacks and taxonomy; to +Security Area Directors Stephen Farrell, Sean Turner, and Kathleen +Moriarty for starting and managing the IETF's discussion on pervasive +attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, Evangelos +Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, Russ Housley, and the IAB +Privacy and Security Program for their input. diff --git a/draft-iab-privsec-confidentiality-threat-06.pdf b/draft-iab-privsec-confidentiality-threat-06.pdf new file mode 100644 index 0000000..302b663 Binary files /dev/null and b/draft-iab-privsec-confidentiality-threat-06.pdf differ diff --git a/draft-iab-privsec-confidentiality-threat-06.txt b/draft-iab-privsec-confidentiality-threat-06.txt new file mode 100644 index 0000000..5de3248 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-06.txt @@ -0,0 +1,1344 @@ + + + + +Network Working Group R. Barnes +Internet-Draft +Intended status: Informational B. Schneier +Expires: November 12, 2015 + C. Jennings + + T. Hardie + + B. Trammell + + C. Huitema + + D. Borkmann + May 11, 2015 + + + Confidentiality in the Face of Pervasive Surveillance: A Threat Model + and Problem Statement + draft-iab-privsec-confidentiality-threat-06 + +Abstract + + Since the initial revelations of pervasive surveillance in 2013, + several classes of attacks on Internet communications have been + discovered. In this document we develop a threat model that + describes these attacks on Internet confidentiality. We assume an + attacker that is interested in undetected, indiscriminate + eavesdropping. The threat model is based on published, verified + attacks. + +Status of This Memo + + This Internet-Draft is submitted in full conformance with the + provisions of BCP 78 and BCP 79. + + Internet-Drafts are working documents of the Internet Engineering + Task Force (IETF). Note that other groups may also distribute + working documents as Internet-Drafts. The list of current Internet- + Drafts is at http://datatracker.ietf.org/drafts/current/. + + Internet-Drafts are draft documents valid for a maximum of six months + and may be updated, replaced, or obsoleted by other documents at any + time. It is inappropriate to use Internet-Drafts as reference + material or to cite them other than as "work in progress." + + This Internet-Draft will expire on November 12, 2015. + + + + + +Barnes, et al. Expires November 12, 2015 [Page 1] + +Internet-Draft Confidentiality Threat Model May 2015 + + +Copyright Notice + + Copyright (c) 2015 IETF Trust and the persons identified as the + document authors. All rights reserved. + + This document is subject to BCP 78 and the IETF Trust's Legal + Provisions Relating to IETF Documents + (http://trustee.ietf.org/license-info) in effect on the date of + publication of this document. Please review these documents + carefully, as they describe your rights and restrictions with respect + to this document. Code Components extracted from this document must + include Simplified BSD License text as described in Section 4.e of + the Trust Legal Provisions and are provided without warranty as + described in the Simplified BSD License. + +1. Introduction + + Starting in June 2013, documents released to the press by Edward + Snowden have revealed several operations undertaken by intelligence + agencies to exploit Internet communications for intelligence + purposes. These attacks were largely based on protocol + vulnerabilities that were already known to exist. The attacks were + nonetheless striking in their pervasive nature, both in terms of the + amount of Internet communications targeted, and in terms of the + diversity of attack techniques employed. + + To ensure that the Internet can be trusted by users, it is necessary + for the Internet technical community to address the vulnerabilities + exploited in these attacks [RFC7258]. The goal of this document is + to describe more precisely the threats posed by these pervasive + attacks, and based on those threats, lay out the problems that need + to be solved in order to secure the Internet in the face of those + threats. + + The remainder of this document is structured as follows. In + Section 3, we describe an idealized passive pervasive attacker, one + which could completely undetectably compromise communications at + Internet scale. In Section 4, we provide a brief summary of some + attacks that have been disclosed, and use these to expand the assumed + capabilities of our idealized attacker. Note that we do not attempt + to describe all possible attacks, but focus on those which result in + undetected eavesdropping. Section 5 describes a threat model based + on these attacks, focusing on classes of attack that have not been a + focus of Internet engineering to date. + + + + + + + +Barnes, et al. Expires November 12, 2015 [Page 2] + +Internet-Draft Confidentiality Threat Model May 2015 + + +2. Terminology + + This document makes extensive use of standard security and privacy + terminology; see [RFC4949] and [RFC6973]. Terms used from [RFC6973] + include Eavesdropper, Observer, Initiator, Intermediary, Recipient, + Attack (in a privacy context), Correlation, Fingerprint, Traffic + Analysis, and Identifiability (and related terms). In addition, we + use a few terms that are specific to the attacks discussed in this + document. Note especially that "passive" and "active" below do not + refer to the effort used to mount the attack; a "passive attack" is + any attack that accesses a flow but does not modify it, while an + "active attack" is any attack that modifies a flow. Some passive + attacks involve active interception and modifications of devices, + rather than simple access to the medium. The introduced terms are: + + Pervasive Attack: An attack on Internet communications that makes + use of access at a large number of points in the network, or + otherwise provides the attacker with access to a large amount of + Internet traffic; see [RFC7258]. + + Passive Pervasive Attack: An eavesdropping attack undertaken by a + pervasive attacker, in which the packets in a traffic stream + between two endpoints are intercepted, but in which the attacker + does not modify the packets in the traffic stream between two + endpoints, modify the treatment of packets in the traffic stream + (e.g. delay, routing), or add or remove packets in the traffic + stream. Passive pervasive attacks are undetectable from the + endpoints. Equivalent to passive wiretapping as defined in + [RFC4949]; we use an alternate term here since the methods + employed are wider than those implied by the word "wiretapping", + including the active compromise of intermediate systems. + + Active Pervasive Attack: An attack undertaken by a pervasive + attacker, which in addition to the elements of a passive pervasive + attack, also includes modification, addition, or removal of + packets in a traffic stream, or modification of treatment of + packets in the traffic stream. Active pervasive attacks provide + more capabilities to the attacker at the risk of possible + detection at the endpoints. Equivalent to active wiretapping as + defined in [RFC4949]. + + Observation: Information collected directly from communications by + an eavesdropper or observer. For example, the knowledge that + sent a message to via SMTP + taken from the headers of an observed SMTP message would be an + observation. + + + + + +Barnes, et al. Expires November 12, 2015 [Page 3] + +Internet-Draft Confidentiality Threat Model May 2015 + + + Inference: Information extracted from analysis of information + collected directly from communications by an eavesdropper or + observer. For example, the knowledge that a given web page was + accessed by a given IP address, by comparing the size in octets of + measured network flow records to fingerprints derived from known + sizes of linked resources on the web servers involved, would be an + inference. + + Collaborator: An entity that is a legitimate participant in a + communication, but who deliberately provides information about + that interaction to an attacker. + + Unwitting Collaborator: An entity that is a legitimate participant + in a communication, and who is the source of information obtained + by the attacker without the entity's consent or intention, because + the attacker has exploited some technology used by the entity. + + Key Exfiltration: The transmission of cryptographic keying material + for an encrypted communication from a collaborator, deliberately + or unwittingly, to an attacker. + + Content Exfiltration: The transmission of the content of a + communication from a collaborator, deliberately or unwittingly, to + an attacker + +3. An Idealized Passive Pervasive Attacker + + In considering the threat posed by pervasive surveillance, we begin + by defining an idealized passive pervasive attacker. While this + attacker is less capable than those which we now know to have + compromised the Internet from press reports, as elaborated in + Section 4, it does set a lower bound on the capabilities of an + attacker interested in indiscriminate passive surveillance while + interested in remaining undetectable. We note that, prior to the + Snowden revelations in 2013, the assumptions of attacker capability + presented here would be considered on the border of paranoia outside + the network security community. + + Our idealized attacker is an indiscriminate eavesdropper on an + Internet-attached computer network that: + + o can observe every packet of all communications at any hop in any + network path between an initiator and a recipient; + + o can observe data at rest in any intermediate system between the + endpoints controlled by the initiator and recipient; and + + o can share information with other such attackers; but + + + +Barnes, et al. Expires November 12, 2015 [Page 4] + +Internet-Draft Confidentiality Threat Model May 2015 + + + o takes no other action with respect to these communications (i.e., + blocking, modification, injection, etc.). + + The techniques available to our ideal attacker are direct + observation and inference. Direct observation involves taking + information directly from eavesdropped communications, such as + URLs identifying content or email addresses identifying + individuals from application- layer headers. Inference, on the + other hand, involves analyzing observed information to derive new + information, such as searching for application or behavioral + fingerprints in observed traffic to derive information about the + observed individual. The use of encryption is generally + sufficient to provide confidentiality by preventing direct + observation of content, assuming of course, uncompromised + encryption implementations and cryptographic keying material. + However, encryption provides less complete protection against + inference, especially inferences based only on plaintext portions + of communications, such as IP and TCP headers for TLS-protected + traffic [RFC5246]). + +3.1. Information subject to direct observation + + Protocols which do not encrypt their payload make the entire content + of the communication available to the idealized attacker along their + path. Following the advice in [RFC3365], most such protocols have a + secure variant which encrypts payload for confidentiality, and these + secure variants are seeing ever-wider deployment. A noteworthy + exception is DNS [RFC1035], as DNSSEC [RFC4033] does not have + confidentiality as a requirement. + + This implies that, in the absence of changes to the protocol as + presently under development in the IETF's DNS Private Exchange + (DPRIVE) working group [I-D.ietf-dprive-problem-statement], all DNS + queries and answers generated by the activities of any protocol are + available to the attacker. + + When store-and-forward protocols are used, (e.g. SMTP [RFC5321]) + intermediaries leave this data subject to observation by an attacker + that has compromised these intermediaries, unless the data is + encrypted end-to-end by the application layer protocol, or the + implementation uses an encrypted store for this data. + +3.2. Information useful for inference + + Inference is information extracted from later analysis of an observed + or eavesdropped communication, and/or correlation of observed or + eavesdropped information with information available from other + sources. Indeed, most useful inference performed by the attacker + + + +Barnes, et al. Expires November 12, 2015 [Page 5] + +Internet-Draft Confidentiality Threat Model May 2015 + + + falls under the rubric of correlation. The simplest example of this + is the observation of DNS queries and answers from and to a source + and correlating those with IP addresses with which that source + communicates. This can give access to information otherwise not + available from encrypted application payloads (e.g., the Host: + HTTP/1.1 request header when HTTP is used with TLS). + + Protocols which encrypt their payload using an application- or + transport-layer encryption scheme (e.g. TLS) still expose all the + information in their network and transport layer headers to the + attacker, including source and destination addresses and ports. + IPsec ESP[RFC4303] further encrypts the transport-layer headers, but + still leaves IP address information unencrypted; in tunnel mode, + these addresses correspond to the tunnel endpoints. Features of the + security protocols themselves, e.g. the TLS session identifier, may + leak information that can be used for correlation and inference. + While this information is much less semantically rich than the + application payload, it can still be useful for the inferring an + individual's activities. + + Inference can also leverage information obtained from sources other + than direct traffic observation. Geolocation databases, for example, + have been developed that map IP addresses to a location, in order to + provide location-aware services such as targeted advertising. This + location information is often of sufficient resolution that it can be + used to draw further inferences toward identifying or profiling an + individual. + + Social media provide another source of more or less publicly + accessible information. This information can be extremely + semantically rich, including information about an individual's + location, associations with other individuals and groups, and + activities. Further, this information is generally contributed and + curated voluntarily by the individuals themselves: it represents + information which the individuals are not necessarily interested in + protecting for privacy reasons. However, correlation of this social + networking data with information available from direct observation of + network traffic allows the creation of a much richer picture of an + individual's activities than either alone. + + We note with some alarm that there is little that can be done at + protocol design time to limit such correlation by the attacker, and + that the existence of such data sources in many cases greatly + complicates the problem of protecting privacy by hardening protocols + alone. + + + + + + +Barnes, et al. Expires November 12, 2015 [Page 6] + +Internet-Draft Confidentiality Threat Model May 2015 + + +3.3. An illustration of an ideal passive pervasive attack + + To illustrate how capable the idealized attacker is even given its + limitations, we explore the non-anonymity of encrypted IP traffic in + this section. Here we examine in detail some inference techniques + for associating a set of addresses with an individual, in order to + illustrate the difficulty of defending communications against our + idealized attacker. Here, the basic problem is that information + radiated even from protocols which have no obvious connection with + personal data can be correlated with other information which can + paint a very rich behavioral picture, that only takes one unprotected + link in the chain to associate with an identity. + +3.3.1. Analysis of IP headers + + Internet traffic can be monitored by tapping Internet links, or by + installing monitoring tools in Internet routers. Of course, a single + link or a single router only provides access to a fraction of the + global Internet traffic. However, monitoring a number of high + capacity links or a set of routers placed at strategic locations + provides access to a good sampling of Internet traffic. + + Tools like IPFIX [RFC7011] allow administrators to acquire statistics + about sequences of packets with some common properties that pass + through a network device. The most common set of properties used in + flow measurement is the "five-tuple"of source and destination + addresses, protocol type, and source and destination ports. These + statistics are commonly used for network engineering, but could + certainly be used for other purposes. + + Let's assume for a moment that IP addresses can be correlated to + specific services or specific users. Analysis of the sequences of + packets will quickly reveal which users use what services, and also + which users engage in peer-to-peer connections with other users. + Analysis of traffic variations over time can be used to detect + increased activity by particular users, or in the case of peer-to- + peer connections increased activity within groups of users. + +3.3.2. Correlation of IP addresses to user identities + + The correlation of IP addresses with specific users can be done in + various ways. For example, tools like reverse DNS lookup can be used + to retrieve the DNS names of servers. Since the addresses of servers + tend to be quite stable and since servers are relatively less + numerous than users, an attacker could easily maintain its own copy + of the DNS for well-known or popular servers, to accelerate such + lookups. + + + + +Barnes, et al. Expires November 12, 2015 [Page 7] + +Internet-Draft Confidentiality Threat Model May 2015 + + + On the other hand, the reverse lookup of IP addresses of users is + generally less informative. For example, a lookup of the address + currently used by one author's home network returns a name of the + form "c-192-000-002-033.hsd1.wa.comcast.net". This particular type + of reverse DNS lookup generally reveals only coarse-grained location + or provider information, equivalent to that available from + geolocation databases. + + In many jurisdictions, Internet Service Providers (ISPs) are required + to provide identification on a case by case basis of the "owner" of a + specific IP address for law enforcement purposes. This is a + reasonably expedient process for targeted investigations, but + pervasive surveillance requires something more efficient. This + provides an incentive for the attacker to secure the cooperation of + the ISP in order to automate this correlation. + +3.3.3. Monitoring messaging clients for IP address correlation + + Even if the ISP does not cooperate, user identity can often be + obtained via inference. POP3 [RFC1939] and IMAP [RFC3501] are used + to retrieve mail from mail servers, while a variant of SMTP is used + to submit messages through mail servers. IMAP connections originate + from the client, and typically start with an authentication exchange + in which the client proves its identity by answering a password + challenge. The same holds for the SIP protocol [RFC3261] and many + instant messaging services operating over the Internet using + proprietary protocols. + + The username is directly observable if any of these protocols operate + in cleartext; the username can then be directly associated with the + source address. + +3.3.4. Retrieving IP addresses from mail headers + + SMTP [RFC5321] requires that each successive SMTP relay adds a + "Received" header to the mail headers. The purpose of these headers + is to enable audit of mail transmission, and perhaps to distinguish + between regular mail and spam. Here is an extract from the headers + of a message recently received from the "perpass" mailing list: + + "Received: from 192-000-002-044.zone13.example.org (HELO + ?192.168.1.100?) (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net + with ESMTPSA (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct + 2013 21:47:14 +0100 Message-ID: <526D7BD2.7070908@example.org> Date: + Sun, 27 Oct 2013 20:47:14 +0000 From: Some One + " + + + + + +Barnes, et al. Expires November 12, 2015 [Page 8] + +Internet-Draft Confidentiality Threat Model May 2015 + + + This is the first "Received" header attached to the message by the + first SMTP relay; for privacy reasons, the field values have been + anonymized. We learn here that the message was submitted by "Some + One" on October 27, from a host behind a NAT (192.168.1.100) + [RFC1918] that used the IP address 192.0.2.44. The information + remained in the message, and is accessible by all recipients of the + "perpass" mailing list, or indeed by any attacker that sees at least + one copy of the message. + + An attacker that can observe sufficient email traffic can regularly + update the mapping between public IP addresses and individual email + identities. Even if the SMTP traffic was encrypted on submission and + relaying, the attacker can still receive a copy of public mailing + lists like "perpass". + +3.3.5. Tracking address usage with web cookies + + Many web sites only encrypt a small fraction of their transactions. + A popular pattern is to use HTTPS for the login information, and then + use a "cookie" to associate following clear-text transactions with + the user's identity. Cookies are also used by various advertisement + services to quickly identify the users and serve them with + "personalized" advertisements. Such cookies are particularly useful + if the advertisement services want to keep tracking the user across + multiple sessions that may use different IP addresses. + + As cookies are sent in clear text, an attacker can build a database + that associates cookies to IP addresses for non-HTTPS traffic. If + the IP address is already identified, the cookie can be linked to the + user identify. After that, if the same cookie appears on a new IP + address, the new IP address can be immediately associated with the + pre-determined identity. + +3.3.6. Graph-based approaches to address correlation + + An attacker can track traffic from an IP address not yet associated + with an individual to various public services (e.g. websites, mail + servers, game servers), and exploit patterns in the observed traffic + to correlate this address with other addresses that show similar + patterns. For example, any two addresses that show connections to + the same IMAP or webmail services, the same set of favorite websites, + and game servers at similar times of day may be associated with the + same individual. Correlated addresses can then be tied to an + individual through one of the techniques above, walking the "network + graph" to expand the set of attributable traffic. + + + + + + +Barnes, et al. Expires November 12, 2015 [Page 9] + +Internet-Draft Confidentiality Threat Model May 2015 + + +3.3.7. Tracking of Link Layer Identifiers + + Moving back down the stack, technologies like Ethernet or Wi-Fi use + MAC Addresses to identify link-level destinations. MAC Addresses + assigned according to IEEE-802 standards are globally-unique + identifiers for the device. If the link is publicly accessible, an + attacker can eavesdrop and perform tracking. For example, the + attacker can track the wireless traffic at publicly accessible Wi-Fi + networks. Simple devices can monitor the traffic, and reveal which + MAC Addresses are present. Also, devices do not need to be connected + to a network to expose link-layer identifiers. Active service + discovery always discloses the MAC address of the user, and sometimes + the SSIDs of previously visited networks. For instance, certain + techniques such as the use of "hidden SSIDs" require the mobile + device to broadcast the network identifier together with the device + identifier. This combination can further expose the user to + inference attacks, as more information can be derived from the + combination of MAC address, SSID being probed, time and current + location. For example, a user actively probing for a semi-unique + SSID on a flight out of a certain city can imply that the user is no + longer at the physical location of the corresponding AP. Given that + large-scale databases of the MAC addresses of wireless access points + for geolocation purposes have been known to exist for some time, the + attacker could easily build a database linking link-layer + identifiers, time and device or user identities, and use it to track + the movement of devices and of their owners. On the other hand, if + the network does not use some form of Wi-Fi encryption, or if the + attacker can access the decrypted traffic, the analysis will also + provide the correlation between link-layer identifiers such as MAC + Addresses and IP addresses. Additional monitoring using techniques + exposed in the previous sections will reveal the correlation between + MAC addresses, IP addresses, and user identity. For instance, + similarly to the use of web cookies, MAC addresses provide identity + information that can be used to associate a user to different IP + addresses. + +4. Reported Instances of Large-Scale Attacks + + The situation in reality is more bleak than that suggested by an + analysis of our idealized attacker. Through revelations of sensitive + documents in several media outlets, the Internet community has been + made aware of several intelligence activities conducted by US and UK + national intelligence agencies, particularly the US National Security + Agency (NSA) and the UK Government Communications Headquarters + (GCHQ). These documents have revealed methods that these agencies + use to attack Internet applications and obtain sensitive user + information. We note that these reports are primarily useful as an + + + + +Barnes, et al. Expires November 12, 2015 [Page 10] + +Internet-Draft Confidentiality Threat Model May 2015 + + + illustration of the types of capabilities fielded by pervasive + attackers as of the date of the Snowden leaks in 2013. + + First, they confirm the deployment of large-scale passive collection + of Internet traffic, which confirms the existence of pervasive + passive attackers with at least the capabilities of our idealized + attacker. For example [pass1][pass2][pass3][pass4]: + + o NSA's XKEYSCORE system accesses data from multiple access points + and searches for "selectors" such as email addresses, at the scale + of tens of terabytes of data per day. + + o GCHQ's Tempora system appears to have access to around 1,500 major + cables passing through the UK. + + o NSA's MUSCULAR program has tapped cables between data centers + belonging to major service providers. + + o Several programs appear to perform wide-scale collection of + cookies in web traffic and location data from location-aware + portable devices such as smartphones. + + However, the capabilities described by these reports go beyond those + of our idealized attacker. They include the compromise of + cryptographic protocols, including decryption of TLS-protected + Internet sessions [dec1][dec2][dec3]. For example, the NSA BULLRUN + project worked to undermine encryption through multiple approaches, + including covert modifications to cryptographic software on end + systems. + + Reported capabilities include the direct compromise of intermediate + systems and arrangements with service providers for bulk data and + metadata access [dir1][dir2][dir3], bypassing the need to capture + traffic on the wire. For example, the NSA PRISM program provides the + agency with access to many types of user data (e.g., email, chat, + VoIP). + + The reported capabilities also include elements of active pervasive + attack, including: + + o Insertion of devices as a man-in-the-middle of Internet + transactions [TOR1][TOR2]. For example, NSA's QUANTUM system + appears to use several different techniques to hijack HTTP + connections, ranging from DNS response injection to HTTP 302 + redirects. + + o Use of implants on end systems to undermine security and anonymity + features [dec2][TOR1][TOR2]. For example, QUANTUM is used to + + + +Barnes, et al. Expires November 12, 2015 [Page 11] + +Internet-Draft Confidentiality Threat Model May 2015 + + + direct users to a FOXACID server, which in turn delivers an + implant to compromise browsers of Tor users. + + o Use of implants on network elements from many major equipment + providers, including Cisco, Juniper, Huawei, Dell, and HP, as + provided by the NSA's Advanced Network Technology group. + [spiegel1] + + o Use of botnet-scale collections of compromised hosts [spiegel3]. + + The scale of the compromise extends beyond the network to include + subversion of the technical standards process itself. For example, + there is suspicion that NSA modifications to the DUAL_EC_DRBG random + number generator were made to ensure that keys generated using that + generator could be predicted by NSA. This RNG was made part of + NIST's SP 800-90A, for which NIST acknowledges NSA's assistance. + There have also been reports that the NSA paid RSA Security for a + related contract with the result that the curve became the default in + the RSA BSAFE product line. + + We use the term "pervasive attack" [RFC7258] to collectively describe + these operations. The term "pervasive" is used because the attacks + are designed to indiscriminately gather as much data as possible and + to apply selective analysis on targets after the fact. This means + that all, or nearly all, Internet communications are targets for + these attacks. To achieve this scale, the attacks are physically + pervasive; they affect a large number of Internet communications. + They are pervasive in content, consuming and exploiting any + information revealed by the protocol. And they are pervasive in + technology, exploiting many different vulnerabilities in many + different protocols. + + It's important to note that although the attacks mentioned above were + executed by NSA and GCHQ, there are many other organizations that can + mount pervasive surveillance attacks. Because of the resources + required to achieve pervasive scale, these attacks are most commonly + undertaken by nation-state actors. For example, the Chinese Internet + filtering system known as the "Great Firewall of China" uses several + techniques that are similar to the QUANTUM program, and which have a + high degree of pervasiveness with regard to the Internet in China. + +5. Threat Model + + Given these disclosures, we must consider a broader threat model. + + Pervasive surveillance aims to collect information across a large + number of Internet communications, analyzing the collected + communications to identify information of interest within individual + + + +Barnes, et al. Expires November 12, 2015 [Page 12] + +Internet-Draft Confidentiality Threat Model May 2015 + + + communications, or inferring information from correlated + communications. This analysis sometimes benefits from decryption of + encrypted communications and deanonymization of anonymized + communications. As a result, these attackers desire both access to + the bulk of Internet traffic and to the keying material required to + decrypt any traffic that has been encrypted. Even if keys are not + available, note that the presence of a communication and the fact + that it is encrypted may both be inputs to an analysis, even if the + attacker cannot decrypt the communication. + + The attacks listed above highlight new avenues both for access to + traffic and for access to relevant encryption keys. They further + indicate that the scale of surveillance is sufficient to provide a + general capability to cross-correlate communications, a threat not + previously thought to be relevant at the scale of the Internet. + +5.1. Attacker Capabilities + + +--------------------------+-------------------------------------+ + | Attack Class | Capability | + +--------------------------+-------------------------------------+ + | Passive observation | Directly capture data in transit | + | | | + | Passive inference | Infer from reduced/encrypted data | + | | | + | Active | Manipulate / inject data in transit | + | | | + | Static key exfiltration | Obtain key material once / rarely | + | | | + | Dynamic key exfiltration | Obtain per-session key material | + | | | + | Content exfiltration | Access data at rest | + +--------------------------+-------------------------------------+ + + Security analyses of Internet protocols commonly consider two classes + of attacker: Passive pervasive attackers, who can simply listen in on + communications as they transit the network, and active pervasive + attackers, who can modify or delete packets in addition to simply + collecting them. + + In the context of pervasive passive surveillance, these attacks take + on an even greater significance. In the past, these attackers were + often assumed to operate near the edge of the network, where attacks + can be simpler. For example, in some LANs, it is simple for any node + to engage in passive listening to other nodes' traffic or inject + packets to accomplish active pervasive attacks. However, as we now + know, both passive and active pervasive attacks are undertaken by + + + + +Barnes, et al. Expires November 12, 2015 [Page 13] + +Internet-Draft Confidentiality Threat Model May 2015 + + + pervasive attackers closer to the core of the network, greatly + expanding the scope and capability of the attacker. + + Eavesdropping and observation at a larger scale make passive + inference attacks easier to carry out: a passive pervasive attacker + with access to a large portion of the Internet can analyze collected + traffic to create a much more detailed view of individual behavior + than an attacker that collects at a single point. Even the usual + claim that encryption defeats passive pervasive attackers is + weakened, since a pervasive flow access attacker can infer + relationships from correlations over large numbers of sessions, e.g., + pairing encrypted sessions with unencrypted sessions from the same + host, or performing traffic fingerprinting between known and unknown + encrypted sessions. Reports on the NSA XKEYSCORE system would + indicate it is an example of such an attacker. + + An active pervasive attacker likewise has capabilities beyond those + of a localized active attacker. Flow modification attacks are often + limited by network topology, for example by a requirement that the + attacker be able to see a targeted session as well as inject packets + into it. A pervasive flow modification attacker with access at + multiple points within the core of the Internet is able to overcome + these topological limitations and perform attacks over a much broader + scope. Being positioned in the core of the network rather than the + edge can also enable an active pervasive attacker to reroute targeted + traffic, amplifying the ability to perform both eavesdropping and + traffic injection. Active pervasive attackers can also benefit from + passive pervasive collection to identify vulnerable hosts. + + While not directly related to pervasiveness, attackers that are in a + position to mount a active pervasive attack are also often in a + position to subvert authentication, a traditional protection against + such attacks. Authentication in the Internet is often achieved via + trusted third party authorities such as the Certificate Authorities + (CAs) that provide web sites with authentication credentials. An + attacker with sufficient resources may also be able to induce an + authority to grant credentials for an identity of the attacker's + choosing. If the parties to a communication will trust multiple + authorities to certify a specific identity, this attack may be + mounted by suborning any one of the authorities (the proverbial + "weakest link"). Subversion of authorities in this way can allow an + active attack to succeed in spite of an authentication check. + + Beyond these three classes (observation, inference, and active), + reports on the BULLRUN effort to defeat encryption and the PRISM + effort to obtain data from service providers suggest three more + classes of attack: + + + + +Barnes, et al. Expires November 12, 2015 [Page 14] + +Internet-Draft Confidentiality Threat Model May 2015 + + + o Static key exfiltration + + o Dynamic key exfiltration + + o Content exfiltration + + These attacks all rely on a collaborator providing the attacker with + some information, either keys or data. These attacks have not + traditionally been considered in scope for the Security + Considerations sections of IETF protocols, as they occur outside the + protocol. + + The term "key exfiltration" refers to the transfer of keying material + for an encrypted communication from the collaborator to the attacker. + By "static", we mean that the transfer of keys happens once, or + rarely, typically of a long-lived key. For example, this case would + cover a web site operator that provides the private key corresponding + to its HTTPS certificate to an intelligence agency. + + "Dynamic" key exfiltration, by contrast, refers to attacks in which + the collaborator delivers keying material to the attacker frequently, + e.g., on a per-session basis. This does not necessarily imply + frequent communications with the attacker; the transfer of keying + material may be virtual. For example, if an endpoint were modified + in such a way that the attacker could predict the state of its + psuedorandom number generator, then the attacker would be able to + derive per-session keys even without per-session communications. + + Finally, content exfiltration is the attack in which the collaborator + simply provides the attacker with the desired data or metadata. + Unlike the key exfiltration cases, this attack does not require the + attacker to capture the desired data as it flows through the network. + The exfiltration is of data at rest, rather than data in transit. + This increases the scope of data that the attacker can obtain, since + the attacker can access historical data - the attacker does not have + to be listening at the time the communication happens. + + Exfiltration attacks can be accomplished via attacks against one of + the parties to a communication, i.e., by the attacker stealing the + keys or content rather than the party providing them willingly. In + these cases, the party may not be aware that they are collaborating, + at least at a human level. Rather, the subverted technical assets + are "collaborating" with the attacker (by providing keys/content) + without their owner's knowledge or consent. + + Any party that has access to encryption keys or unencrypted data can + be a collaborator. While collaborators are typically the endpoints + of a communication (with encryption securing the links), + + + +Barnes, et al. Expires November 12, 2015 [Page 15] + +Internet-Draft Confidentiality Threat Model May 2015 + + + intermediaries in an unencrypted communication can also facilitate + content exfiltration attacks as collaborators by providing the + attacker access to those communications. For example, documents + describing the NSA PRISM program claim that NSA is able to access + user data directly from servers, where it is stored unencrypted. In + these cases, the operator of the server would be a collaborator, if + an unwitting one. By contrast, in the NSA MUSCULAR program, a set of + collaborators enabled attackers to access the cables connecting data + centers used by service providers such as Google and Yahoo. Because + communications among these data centers were not encrypted, the + collaboration by an intermediate entity allowed NSA to collect + unencrypted user data. + +5.2. Attacker Costs + + +--------------------------+-----------------------------------+ + | Attack Class | Cost / Risk to Attacker | + +--------------------------+-----------------------------------+ + | Passive observation | Passive data access | + | | | + | Passive inference | Passive data access + processing | + | | | + | Active | Active data access + processing | + | | | + | Static key exfiltration | One-time interaction | + | | | + | Dynamic key exfiltration | Ongoing interaction / code change | + | | | + | Content exfiltration | Ongoing, bulk interaction | + +--------------------------+-----------------------------------+ + + Each of the attack types discussed in the previous section entails + certain costs and risks. These costs differ by attack, and can be + helpful in guiding response to pervasive attack. + + Depending on the attack, the attacker may be exposed to several types + of risk, ranging from simply losing access to arrest or prosecution. + In order for any of these negative consequences to occur, however, + the attacker must first be discovered and identified. So the primary + risk we focus on here is the risk of discovery and attribution. + + A passive pervasive attack is the simplest to mount in some ways. + The base requirement is that the attacker obtain physical access to a + communications medium and extract communications from it. For + example, the attacker might tap a fiber-optic cable, acquire a mirror + port on a switch, or listen to a wireless signal. The need for these + taps to have physical access or proximity to a link exposes the + attacker to the risk that the taps will be discovered. For example, + + + +Barnes, et al. Expires November 12, 2015 [Page 16] + +Internet-Draft Confidentiality Threat Model May 2015 + + + a fiber tap or mirror port might be discovered by network operators + noticing increased attenuation in the fiber or a change in switch + configuration. Of course, passive pervasive attacks may be + accomplished with the cooperation of the network operator, in which + case there is a risk that the attacker's interactions with the + network operator will be exposed. + + In many ways, the costs and risks for an active pervasive attack are + similar to those for a passive pervasive attack, with a few + additions. An active attacker requires more robust network access + than a passive attacker, since for example they will often need to + transmit data as well as receiving it. In the wireless example + above, the attacker would need to act as an transmitter as well as + receiver, greatly increasing the probability the attacker will be + discovered (e.g., using direction-finding technology). Active + attacks are also much more observable at higher layers of the + network. For example, an active attacker that attempts to use a mis- + issued certificate could be detected via Certificate Transparency + [RFC6962]. + + In terms of raw implementation complexity, passive pervasive attacks + require only enough processing to extract information from the + network and store it. Active pervasive attacks, by contrast, often + depend on winning race conditions to inject packets into active + connections. So active pervasive attacks in the core of the network + require processing hardware to that can operate at line speed + (roughly 100Gbps to 1Tbps in the core) to identify opportunities for + attack and insert attack traffic in a high-volume traffic. Key + exfiltration attacks rely on passive pervasive attack for access to + encrypted data, with the collaborator providing keys to decrypt the + data. So the attacker undertakes the cost and risk of a passive + pervasive attack, as well as additional risk of discovery via the + interactions that the attacker has with the collaborator. + + Some active attacks are more expensive than others. For example, + active man-in-the-middle (MITM) attacks require access to one or more + points on a communication's network path that allow visibility of the + entire session and the ability to modify or drop legitimate packets + in favor of the attacker's packets. A similar but weaker form of + attack, called an active man-on-the-side (MOTS), requires access to + only part of the session. In an active MOTS attack, the attacker + need only be able to inject or modify traffic on the network element + the attacker has access to. While this may not allow for full + control of a communication session (as in an MITM attack), the + attacker can perform a number of powerful attacks, including but not + limited to: injecting packets that could terminate the session (e.g., + TCP RST packets), sending a fake DNS reply to redirect ensuing TCP + connections to an address of the attacker's choice (i.e., winning a + + + +Barnes, et al. Expires November 12, 2015 [Page 17] + +Internet-Draft Confidentiality Threat Model May 2015 + + + "DNS response race"), and mounting an HTTP Redirect attack by + observing a TCP/HTTP connection to a target address and injecting a + TCP data packet containing an HTTP redirect. For example, the system + dubbed by researchers as China's "Great Cannon" [great-cannon] can + operate in ful MITM mode to accomplish very complex attacks that can + modify content in transit while the well-known Great Firewall of + China is a MOTS system that focuses on blocking access to certain + kinds of traffic and destinations via TCP RST packet injection. + + In this sense, static exfiltration has a lower risk profile than + dynamic. In the static case, the attacker need only interact with + the collaborator a small number of times, possibly only once, say to + exchange a private key. In the dynamic case, the attacker must have + continuing interactions with the collaborator. As noted above these + interactions may be real, such as in-person meetings, or virtual, + such as software modifications that render keys available to the + attacker. Both of these types of interactions introduce a risk that + they will be discovered, e.g., by employees of the collaborator + organization noticing suspicious meetings or suspicious code changes. + + Content exfiltration has a similar risk profile to dynamic key + exfiltration. In a content exfiltration attack, the attacker saves + the cost and risk of conducting a passive pervasive attack. The risk + of discovery through interactions with the collaborator, however, is + still present, and may be higher. The content of a communication is + obviously larger than the key used to encrypt it, often by several + orders of magnitude. So in the content exfiltration case, the + interactions between the collaborator and the attacker need to be + much higher-bandwidth than in the key exfiltration cases, with a + corresponding increase in the risk that this high-bandwidth channel + will be discovered. + + It should also be noted that in these latter three exfiltration + cases, the collaborator also undertakes a risk that his collaboration + with the attacker will be discovered. Thus the attacker may have to + incur additional cost in order to convince the collaborator to + participate in the attack. Likewise, the scope of these attacks is + limited to case where the attacker can convince a collaborator to + participate. If the attacker is a national government, for example, + it may be able to compel participation within its borders, but have a + much more difficult time recruiting foreign collaborators. + + As noted above, the collaborator in an exfiltration attack can be + unwitting; the attacker can steal keys or data to enable the attack. + In some ways, the risks of this approach are similar to the case of + an active collaborator. In the static case, the attacker needs to + steal information from the collaborator once; in the dynamic case, + the attacker needs to continued presence inside the collaborators + + + +Barnes, et al. Expires November 12, 2015 [Page 18] + +Internet-Draft Confidentiality Threat Model May 2015 + + + systems. The main difference is that the risk in this case is of + automated discovery (e.g., by intrusion detection systems) rather + than discovery by humans. + +6. Security Considerations + + This document describes a threat model for pervasive surveillance + attacks. Mitigations are to be given in a future document. + +7. IANA Considerations + + This document has no actions for IANA. + +8. Acknowledgements + + Thanks to Dave Thaler for the list of attacks and taxonomy; to + Security Area Directors Stephen Farrell, Sean Turner, and Kathleen + Moriarty for starting and managing the IETF's discussion on pervasive + attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, + Evangelos Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, Russ Housley, + and the IAB Privacy and Security Program for their input. + +9. References + +9.1. Normative References + + [RFC6973] Cooper, A., Tschofenig, H., Aboba, B., Peterson, J., + Morris, J., Hansen, M., and R. Smith, "Privacy + Considerations for Internet Protocols", RFC 6973, July + 2013. + +9.2. Informative References + + [pass1] The Guardian, "How the NSA is still harvesting your online + data", 2013, + . + + [pass2] The Guardian, "NSA's Prism surveillance program: how it + works and what it can do", 2013, + . + + [pass3] The Guardian, "XKeyscore: NSA tool collects 'nearly + everything a user does on the internet'", 2013, + . + + + + +Barnes, et al. Expires November 12, 2015 [Page 19] + +Internet-Draft Confidentiality Threat Model May 2015 + + + [pass4] The Guardian, "How does GCHQ's internet surveillance + work?", n.d., . + + [dec1] The New York Times, "N.S.A. Able to Foil Basic Safeguards + of Privacy on Web", 2013, + . + + [dec2] The Guardian, "Project Bullrun - classification guide to + the NSA's decryption program", 2013, + . + + [dec3] The Guardian, "Revealed: how US and UK spy agencies defeat + internet privacy and security", 2013, + . + + [TOR] The Tor Project, "Tor", 2013, + . + + [TOR1] Schneier, B., "How the NSA Attacks Tor/Firefox Users With + QUANTUM and FOXACID", 2013, + . + + [TOR2] The Guardian, "'Tor Stinks' presentation - read the full + document", 2013, + . + + [dir1] The Guardian, "NSA collecting phone records of millions of + Verizon customers daily", 2013, + . + + [dir2] The Guardian, "NSA Prism program taps in to user data of + Apple, Google and others", 2013, + . + + [dir3] The Guardian, "Sigint - how the NSA collaborates with + technology companies", 2013, + . + + + + + +Barnes, et al. Expires November 12, 2015 [Page 20] + +Internet-Draft Confidentiality Threat Model May 2015 + + + [secure] Schneier, B., "NSA surveillance: A guide to staying + secure", 2013, + . + + [snowden] Technology Review, "NSA Leak Leaves Crypto-Math Intact but + Highlights Known Workarounds", 2013, + . + + [spiegel1] + C Stocker, ., "NSA's Secret Toolbox: Unit Offers Spy + Gadgets for Every Need", December 2013, + . + + [spiegel3] + H Schmundt, ., "The Digital Arms Race: NSA Preps America + for Future Battle", January 2014, + . + + [key-recovery] + Golle, P., "The Design and Implementation of Protocol- + Based Hidden Key Recovery", 2003, + . + + [great-cannon] + Paxson, V., "China's Great Cannon", 2015, + . + + [RFC1035] Mockapetris, P., "Domain names - implementation and + specification", STD 13, RFC 1035, November 1987. + + [RFC1918] Rekhter, Y., Moskowitz, R., Karrenberg, D., Groot, G., and + E. Lear, "Address Allocation for Private Internets", BCP + 5, RFC 1918, February 1996. + + [RFC1939] Myers, J. and M. Rose, "Post Office Protocol - Version 3", + STD 53, RFC 1939, May 1996. + + [RFC2015] Elkins, M., "MIME Security with Pretty Good Privacy + (PGP)", RFC 2015, October 1996. + + + + + +Barnes, et al. Expires November 12, 2015 [Page 21] + +Internet-Draft Confidentiality Threat Model May 2015 + + + [RFC2821] Klensin, J., "Simple Mail Transfer Protocol", RFC 2821, + April 2001. + + [RFC3261] Rosenberg, J., Schulzrinne, H., Camarillo, G., Johnston, + A., Peterson, J., Sparks, R., Handley, M., and E. + Schooler, "SIP: Session Initiation Protocol", RFC 3261, + June 2002. + + [RFC3365] Schiller, J., "Strong Security Requirements for Internet + Engineering Task Force Standard Protocols", BCP 61, RFC + 3365, August 2002. + + [RFC3501] Crispin, M., "INTERNET MESSAGE ACCESS PROTOCOL - VERSION + 4rev1", RFC 3501, March 2003. + + [RFC3851] Ramsdell, B., "Secure/Multipurpose Internet Mail + Extensions (S/MIME) Version 3.1 Message Specification", + RFC 3851, July 2004. + + [RFC4033] Arends, R., Austein, R., Larson, M., Massey, D., and S. + Rose, "DNS Security Introduction and Requirements", RFC + 4033, March 2005. + + [RFC4301] Kent, S. and K. Seo, "Security Architecture for the + Internet Protocol", RFC 4301, December 2005. + + [RFC4303] Kent, S., "IP Encapsulating Security Payload (ESP)", RFC + 4303, December 2005. + + [RFC4306] Kaufman, C., "Internet Key Exchange (IKEv2) Protocol", RFC + 4306, December 2005. + + [RFC4949] Shirey, R., "Internet Security Glossary, Version 2", RFC + 4949, August 2007. + + [RFC5246] Dierks, T. and E. Rescorla, "The Transport Layer Security + (TLS) Protocol Version 1.2", RFC 5246, August 2008. + + [RFC5321] Klensin, J., "Simple Mail Transfer Protocol", RFC 5321, + October 2008. + + [RFC5655] Trammell, B., Boschi, E., Mark, L., Zseby, T., and A. + Wagner, "Specification of the IP Flow Information Export + (IPFIX) File Format", RFC 5655, October 2009. + + [RFC5750] Ramsdell, B. and S. Turner, "Secure/Multipurpose Internet + Mail Extensions (S/MIME) Version 3.2 Certificate + Handling", RFC 5750, January 2010. + + + +Barnes, et al. Expires November 12, 2015 [Page 22] + +Internet-Draft Confidentiality Threat Model May 2015 + + + [RFC6120] Saint-Andre, P., "Extensible Messaging and Presence + Protocol (XMPP): Core", RFC 6120, March 2011. + + [RFC6962] Laurie, B., Langley, A., and E. Kasper, "Certificate + Transparency", RFC 6962, June 2013. + + [RFC6698] Hoffman, P. and J. Schlyter, "The DNS-Based Authentication + of Named Entities (DANE) Transport Layer Security (TLS) + Protocol: TLSA", RFC 6698, August 2012. + + [RFC7011] Claise, B., Trammell, B., and P. Aitken, "Specification of + the IP Flow Information Export (IPFIX) Protocol for the + Exchange of Flow Information", STD 77, RFC 7011, September + 2013. + + [RFC7258] Farrell, S. and H. Tschofenig, "Pervasive Monitoring Is an + Attack", BCP 188, RFC 7258, May 2014. + + [I-D.ietf-dprive-problem-statement] + Bortzmeyer, S., "DNS privacy considerations", draft-ietf- + dprive-problem-statement-02 (work in progress), February + 2015. + +Authors' Addresses + + Richard Barnes + + Email: rlb@ipv.sx + + + Bruce Schneier + + Email: schneier@schneier.com + + + Cullen Jennings + + Email: fluffy@cisco.com + + + Ted Hardie + + Email: ted.ietf@gmail.com + + + Brian Trammell + + Email: ietf@trammell.ch + + + +Barnes, et al. Expires November 12, 2015 [Page 23] + +Internet-Draft Confidentiality Threat Model May 2015 + + + Christian Huitema + + Email: huitema@huitema.net + + + Daniel Borkmann + + Email: dborkman@iogearbox.net + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Barnes, et al. Expires November 12, 2015 [Page 24] diff --git a/draft-iab-privsec-confidentiality-threat-06.xml b/draft-iab-privsec-confidentiality-threat-06.xml new file mode 100644 index 0000000..8abe295 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-06.xml @@ -0,0 +1,1108 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +]> + + + + + + Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement + + + +
+ rlb@ipv.sx +
+ + + +
+ schneier@schneier.com +
+ + + +
+ fluffy@cisco.com +
+ + + +
+ ted.ietf@gmail.com +
+ + + +
+ ietf@trammell.ch +
+ + + +
+ huitema@huitema.net +
+ + + +
+ dborkman@iogearbox.net +
+ + + + + + + + + + + +Since the initial revelations of pervasive surveillance in 2013, + several classes of attacks on Internet communications have been + discovered. In this document we develop a threat model that + describes these attacks on Internet confidentiality. We assume an + attacker that is interested in undetected, indiscriminate + eavesdropping. The threat model is based on published, verified + attacks. + + + + + + + + + + + +
+ +Starting in June 2013, documents released to the press by Edward +Snowden have revealed several operations undertaken by intelligence +agencies to exploit Internet communications for intelligence purposes. +These attacks were largely based on protocol vulnerabilities that were +already known to exist. The attacks were nonetheless striking in +their pervasive nature, both in terms of the amount of Internet +communications targeted, and in terms of the diversity of attack +techniques employed. + +To ensure that the Internet can be trusted by users, it is necessary +for the Internet technical community to address the vulnerabilities +exploited in these attacks . The goal of this document is +to describe more precisely the threats posed by these pervasive +attacks, and based on those threats, lay out the problems that need to +be solved in order to secure the Internet in the face of those +threats. + +The remainder of this document is structured as follows. In +, we describe an idealized passive pervasive attacker, one which +could completely undetectably compromise communications at Internet +scale. In , we provide a brief summary of some attacks +that have been disclosed, and use these to expand the assumed +capabilities of our idealized attacker. Note that we do not attempt +to describe all possible attacks, but focus on those which result in +undetected eavesdropping. describes a threat model based on +these attacks, focusing on classes of attack that have not been a +focus of Internet engineering to date. + +
+
+ +This document makes extensive use of standard security and privacy +terminology; see and . Terms used from + include Eavesdropper, Observer, Initiator, Intermediary, +Recipient, Attack (in a privacy context), Correlation, Fingerprint, +Traffic Analysis, and Identifiability (and related terms). In +addition, we use a few terms that are specific to the attacks +discussed in this document. Note especially that “passive” and “active” below +do not refer to the effort used to mount the attack; a “passive attack” +is any attack that accesses a flow but does not modify it, while an +“active attack” is any attack that modifies a flow. Some passive attacks +involve active interception and modifications of devices, rather than simple +access to the medium. The introduced terms are: + + + + An attack on Internet communications that makes +use of access at a large number of points in the network, or otherwise +provides the attacker with access to a large amount of Internet +traffic; see . + + An eavesdropping attack undertaken by a pervasive attacker, in which the +packets in a traffic stream between two endpoints are intercepted, but +in which the attacker does not modify the packets in the traffic +stream between two endpoints, modify the treatment of packets in the +traffic stream (e.g. delay, routing), or add or remove packets in the +traffic stream. Passive pervasive attacks are undetectable from the +endpoints. Equivalent to passive wiretapping as defined in ; +we use an alternate term here since the methods employed are wider +than those implied by the word “wiretapping”, including the active +compromise of intermediate systems. + + An attack undertaken by a pervasive attacker, which in addition to +the elements of a passive pervasive attack, also includes modification, +addition, or removal of +packets in a traffic stream, or modification of treatment of packets +in the traffic stream. Active pervasive attacks provide more +capabilities to the attacker at the risk of possible detection at the +endpoints. Equivalent to active wiretapping as defined in . + + Information collected directly from communications by an +eavesdropper or observer. For example, the knowledge that +<alice@example.com> sent a message to <bob@example.com> +via SMTP taken from the headers of an observed SMTP message would be +an observation. + + Information extracted from analysis of information collected +directly from communications by an eavesdropper or observer. For +example, the knowledge that a given web page was accessed by a given +IP address, by comparing the size in octets of measured network flow +records to fingerprints derived from known sizes of linked resources +on the web servers involved, would be an inference. + + An entity that is a legitimate participant in a communication, but +who deliberately provides information about that interaction to an +attacker. + + An entity that is a legitimate participant in a communication, and +who is the source of information obtained by the attacker without the +entity’s consent or intention, because the attacker has exploited some +technology used by the entity. + + The transmission of cryptographic keying material for an encrypted communication +from a collaborator, deliberately or unwittingly, to an attacker. + + The transmission of the content of a communication from a collaborator, deliberately or unwittingly, to an attacker + + +
+
+ +In considering the threat posed by pervasive surveillance, we begin by +defining an idealized passive pervasive attacker. While this attacker +is less capable than those which we now know to have compromised the +Internet from press reports, as elaborated in , it does +set a lower bound on the capabilities of an attacker interested in +indiscriminate passive surveillance while interested in remaining +undetectable. We note that, prior to the Snowden revelations in 2013, +the assumptions of attacker capability presented here would be +considered on the border of paranoia outside the network security +community. + +Our idealized attacker is an indiscriminate eavesdropper on an Internet-attached computer network that: + + + can observe every packet of all communications at any hop in any network path between an initiator and a recipient; + can observe data at rest in any intermediate system between the endpoints controlled by the initiator and recipient; and + can share information with other such attackers; but + takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.). +The techniques available to our ideal attacker are direct observation +and inference. Direct observation involves taking information +directly from eavesdropped communications, such as URLs identifying +content or email addresses identifying individuals from application- +layer headers. Inference, on the other hand, involves analyzing +observed information to derive new information, such as searching for +application or behavioral fingerprints in observed traffic to derive +information about the observed individual. The use of encryption is +generally sufficient to provide confidentiality by preventing direct +observation of content, assuming of course, uncompromised encryption +implementations and cryptographic keying material. However, +encryption provides less complete protection against inference, +especially inferences based only on plaintext portions of +communications, such as IP and TCP headers for TLS-protected traffic +). + + +
+ +Protocols which do not encrypt their payload make the entire content +of the communication available to the idealized attacker along their +path. Following the advice in , most such protocols have a +secure variant which encrypts payload for confidentiality, and these +secure variants are seeing ever-wider deployment. A noteworthy +exception is DNS , as DNSSEC does not have +confidentiality as a requirement. + +This implies that, in the absence of +changes to the protocol as presently under development in the IETF’s +DNS Private Exchange (DPRIVE) +working group , all DNS queries and answers generated by the activities +of any protocol are available to the attacker. + +When store-and-forward protocols are used, (e.g. SMTP ) +intermediaries leave this data subject to observation by an attacker that +has compromised these intermediaries, +unless the data is encrypted end-to-end by the application layer +protocol, or the implementation uses an encrypted store for this data. + +
+
+ +Inference is information extracted from later analysis of an observed +or eavesdropped communication, and/or correlation of observed or +eavesdropped information with information available from other +sources. Indeed, most useful inference performed by the attacker falls +under the rubric of correlation. The simplest example of this is the +observation of DNS queries and answers from and to a source and +correlating those with IP addresses with which that source +communicates. This can give access to information otherwise not +available from encrypted application payloads (e.g., the Host: +HTTP/1.1 request header when HTTP is used with TLS). + +Protocols which encrypt their payload using an application- or +transport-layer encryption scheme (e.g. TLS) still expose all the +information in their network and transport layer headers to the +attacker, including source and destination addresses and ports. IPsec +ESP further encrypts the transport-layer headers, but still +leaves IP address information unencrypted; in tunnel mode, these +addresses correspond to the tunnel endpoints. Features of the +security protocols themselves, e.g. the TLS session identifier, +may leak information that can be used for correlation and +inference. While this information is much less semantically rich than +the application payload, it can still be useful for the inferring an +individual’s activities. + +Inference can also leverage information obtained from sources other +than direct traffic observation. Geolocation databases, for example, +have been developed that map IP addresses to a location, in order to +provide location-aware services such as targeted advertising. This +location information is often of sufficient resolution that it can be +used to draw further inferences toward identifying or profiling an +individual. + +Social media provide another source of more or less publicly +accessible information. This information can be extremely semantically +rich, including information about an individual’s location, +associations with other individuals and groups, and +activities. Further, this information is generally contributed and +curated voluntarily by the individuals themselves: it represents +information which the individuals are not necessarily interested in +protecting for privacy reasons. However, correlation of this social +networking data with information available from direct observation of +network traffic allows the creation of a much richer picture of an +individual’s activities than either alone. + +We note with some alarm that there is little that can be done at +protocol design time to limit such correlation by the attacker, and +that the existence of such data sources in many cases greatly +complicates the problem of protecting privacy by hardening protocols +alone. + +
+
+ +To illustrate how capable the idealized attacker is even given its +limitations, we explore the non-anonymity of encrypted IP traffic in +this section. Here we examine in detail some inference techniques for +associating a set of addresses with an individual, in order to +illustrate the difficulty of defending communications against our +idealized attacker. Here, the basic problem is that information +radiated even from protocols which have no obvious connection with +personal data can be correlated with other information which can paint +a very rich behavioral picture, that only takes one unprotected link +in the chain to associate with an identity. + +
+ +Internet traffic can be monitored by tapping Internet links, or by +installing monitoring tools in Internet routers. Of course, a single +link or a single router only provides access to a fraction of the +global Internet traffic. However, monitoring a number of high capacity +links or a set of routers placed at strategic locations provides +access to a good sampling of Internet traffic. + +Tools like IPFIX allow administrators to acquire +statistics about sequences of packets with some common properties that +pass through a network device. The most common set of properties used +in flow measurement is the “five-tuple”of source and destination +addresses, protocol type, and source and destination ports. These +statistics are commonly used for network engineering, but could +certainly be used for other purposes. + +Let’s assume for a moment that IP addresses can be correlated to +specific services or specific users. Analysis of the sequences of +packets will quickly reveal which users use what services, and also +which users engage in peer-to-peer connections with other +users. Analysis of traffic variations over time can be used to detect +increased activity by particular users, or in the case of peer-to-peer +connections increased activity within groups of users. + +
+
+ +The correlation of IP addresses with specific users can be done in +various ways. For example, tools like reverse DNS lookup can be used +to retrieve the DNS names of servers. Since the addresses of servers +tend to be quite stable and since servers are relatively less numerous +than users, an attacker could easily maintain its own copy of the DNS +for well-known or popular servers, to accelerate such lookups. + +On the other hand, the reverse lookup of IP addresses of users is +generally less informative. For example, a lookup of the address +currently used by one author’s home network returns a name of the form +“c-192-000-002-033.hsd1.wa.comcast.net”. This particular type of +reverse DNS lookup generally reveals only coarse-grained location or +provider information, equivalent to that available from geolocation +databases. + +In many jurisdictions, Internet Service Providers (ISPs) are required +to provide identification on a case by case basis of the “owner” of a +specific IP address for law enforcement purposes. This is a reasonably +expedient process for targeted investigations, but pervasive +surveillance requires something more efficient. This provides an +incentive for the attacker to secure the cooperation of the ISP in +order to automate this correlation. + +
+
+ +Even if the ISP does not cooperate, user identity can often be +obtained via inference. POP3 and IMAP are used +to retrieve mail from mail servers, while a variant of SMTP is used to +submit messages through mail servers. IMAP connections originate from +the client, and typically start with an authentication exchange in +which the client proves its identity by answering a password +challenge. The same holds for the SIP protocol and many +instant messaging services operating over the Internet using +proprietary protocols. + +The username is directly observable if any of these protocols operate +in cleartext; the username can then be directly associated with the +source address. + +
+
+ +SMTP requires that each successive SMTP relay adds a +“Received” header to the mail headers. The purpose of these headers is +to enable audit of mail transmission, and perhaps to distinguish +between regular mail and spam. Here is an extract from the headers of +a message recently received from the “perpass” mailing list: + + + Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?) + (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA + (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100 + Message-ID: <526D7BD2.7070908@example.org> + Date: Sun, 27 Oct 2013 20:47:14 +0000 + From: Some One <some.one@example.org> + + +This is the first “Received” header attached to the message by the +first SMTP relay; for privacy reasons, the field values have been +anonymized. We learn here that the message was submitted by “Some One” +on October 27, from a host behind a NAT (192.168.1.100) +that used the IP address 192.0.2.44. The information remained in the +message, and is accessible by all recipients of the “perpass” mailing +list, or indeed by any attacker that sees at least one copy of the +message. + +An attacker that can observe sufficient email traffic can regularly +update the mapping between public IP addresses and individual email +identities. Even if the SMTP traffic was encrypted on submission and +relaying, the attacker can still receive a copy of public mailing +lists like “perpass”. + +
+
+ +Many web sites only encrypt a small fraction of their transactions. A +popular pattern is to use HTTPS for the login information, and then +use a “cookie” to associate following clear-text transactions with the +user’s identity. Cookies are also used by various advertisement +services to quickly identify the users and serve them with +“personalized” advertisements. Such cookies are particularly useful if +the advertisement services want to keep tracking the user across +multiple sessions that may use different IP addresses. + +As cookies are sent in clear text, an attacker can build a database +that associates cookies to IP addresses for non-HTTPS traffic. If the +IP address is already identified, the cookie can be linked to the user +identify. After that, if the same cookie appears on a new IP address, +the new IP address can be immediately associated with the +pre-determined identity. + +
+
+ +An attacker can track traffic from an IP address not yet associated +with an individual to various public services (e.g. websites, mail +servers, game servers), and exploit patterns in the observed traffic +to correlate this address with other addresses that show similar +patterns. For example, any two addresses that show connections to the +same IMAP or webmail services, the same set of favorite websites, and +game servers at similar times of day may be associated with the same +individual. Correlated addresses can then be tied to an individual +through one of the techniques above, walking the “network graph” to +expand the set of attributable traffic. + +
+
+ +Moving back down the stack, technologies like Ethernet or Wi-Fi use MAC Addresses to identify link-level destinations. MAC Addresses assigned according to IEEE-802 standards are globally-unique identifiers for the device. If the link is publicly accessible, an attacker can eavesdrop and perform tracking. For example, the attacker can track the wireless traffic at publicly accessible Wi-Fi networks. Simple devices can monitor the traffic, and reveal which MAC Addresses are present. +Also, devices do not need to be connected to a network to expose link-layer identifiers. Active service discovery always discloses the MAC address of the user, and sometimes the SSIDs of previously visited networks. For instance, certain techniques such as the use of “hidden SSIDs” require the mobile device to broadcast the network identifier together with the device identifier. This combination can further expose the user to inference attacks, as more information can be derived from the combination of MAC address, SSID being probed, time and current location. For example, a user actively probing for a semi-unique SSID on a flight out of a certain city can imply that the user is no longer at the physical location of the corresponding AP. +Given that large-scale databases of the MAC addresses of wireless access points for geolocation purposes have been known to exist for some time, the attacker could easily build a database linking link-layer identifiers, time and device or user identities, and use it to track the movement of devices and of their owners. +On the other hand, if the network does not use some form of Wi-Fi encryption, or if the attacker can access the decrypted traffic, the analysis will also provide the correlation between link-layer identifiers such as MAC Addresses and IP addresses. Additional monitoring using techniques exposed in the previous sections will reveal the correlation between MAC addresses, IP addresses, and user identity. For instance, similarly to the use of web cookies, MAC addresses provide identity information that can be used to associate a user to different IP addresses. + +
+
+
+
+ +The situation in reality is more bleak than that suggested by an +analysis of our idealized attacker. Through revelations of sensitive +documents in several media outlets, the Internet community has been +made aware of several intelligence activities conducted by US and UK +national intelligence agencies, particularly the US National Security +Agency (NSA) and the UK Government Communications Headquarters +(GCHQ). These documents have revealed methods that these agencies use +to attack Internet applications and obtain sensitive user information. +We note that these reports are primarily useful as an illustration of +the types of capabilities fielded by pervasive attackers as of the +date of the Snowden leaks in 2013. + +First, they confirm the deployment of large-scale passive +collection of Internet traffic, which confirms the existence of +pervasive passive attackers with at least the capabilities of our +idealized attacker. For example : + + + NSA’s XKEYSCORE system accesses data from multiple access points and +searches for “selectors” such as email addresses, at the scale of tens +of terabytes of data per day. + GCHQ’s Tempora system appears to have access to around 1,500 major cables +passing through the UK. + NSA’s MUSCULAR program has tapped cables between data centers +belonging to major service providers. + Several programs appear to perform wide-scale collection +of cookies in web traffic and location data from location-aware +portable devices such as smartphones. + + +However, the capabilities described by these reports go beyond those of our +idealized attacker. They include the compromise of cryptographic protocols, +including decryption of TLS-protected Internet sessions . +For example, the NSA BULLRUN project worked to undermine encryption through +multiple approaches, including covert modifications to cryptographic +software on end systems. + +Reported capabilities include the direct compromise of intermediate systems +and arrangements with service providers for bulk data and metadata +access , bypassing the need to capture +traffic on the wire. For example, the NSA PRISM program provides the +agency with access to many types of user data (e.g., email, chat, VoIP). + +The reported capabilities also include elements of active pervasive attack, +including: + + + Insertion of devices as a man-in-the-middle of Internet +transactions . For example, NSA’s QUANTUM system +appears to use several different techniques to hijack HTTP +connections, ranging from DNS response injection to HTTP 302 +redirects. + Use of implants on end systems to undermine security and anonymity +features . For example, QUANTUM is used to +direct users to a FOXACID server, which in turn delivers an implant +to compromise browsers of Tor users. + Use of implants on network elements from many major equipment providers, +including Cisco, Juniper, Huawei, Dell, and HP, as provided by the NSA’s +Advanced Network Technology group. + Use of botnet-scale collections of compromised hosts . + + +The scale of the compromise extends beyond the network to include subversion of the technical standards process itself. For example, there is suspicion that NSA modifications to the DUAL_EC_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA. This RNG was made part of NIST’s SP 800-90A, for which NIST acknowledges NSA’s assistance. There have also been reports that the NSA paid RSA Security for a related contract with the result that the curve became the default in the RSA BSAFE product line. + +We use the term “pervasive attack” to collectively +describe these operations. The term “pervasive” is used because the +attacks are designed to indiscriminately gather as much data as +possible and to apply selective analysis on targets after the fact. +This means that all, or nearly all, Internet communications are +targets for these attacks. To achieve this scale, the attacks are +physically pervasive; they affect a large number of Internet +communications. They are pervasive in content, consuming and +exploiting any information revealed by the protocol. And they are +pervasive in technology, exploiting many different vulnerabilities in +many different protocols. + +It’s important to note that although the attacks mentioned above were +executed by NSA and GCHQ, there are many other organizations that can +mount pervasive surveillance attacks. Because of the resources +required to achieve pervasive scale, these attacks are most commonly +undertaken by nation-state actors. For example, the Chinese Internet +filtering system known as the “Great Firewall of China” uses several +techniques that are similar to the QUANTUM program, and which have a +high degree of pervasiveness with regard to the Internet in China. + +
+
+ +Given these disclosures, we must consider a broader threat model. + +Pervasive surveillance aims to collect information across a large +number of Internet communications, analyzing the collected +communications to identify information of interest within individual +communications, or inferring information from correlated +communications. This analysis sometimes benefits from decryption of +encrypted communications and deanonymization of anonymized +communications. As a result, these attackers desire both access to +the bulk of Internet traffic and to the keying material required to +decrypt any traffic that has been encrypted. Even if keys are not +available, note that the presence of a communication and the fact that +it is encrypted may both be inputs to an analysis, even if the +attacker cannot decrypt the communication. + +The attacks listed above highlight new avenues both for access to +traffic and for access to relevant encryption keys. They further +indicate that the scale of surveillance is sufficient to provide a +general capability to cross-correlate communications, a threat not +previously thought to be relevant at the scale of the Internet. + +
+ + + Attack Class + Capability + Passive observation + Directly capture data in transit + Passive inference + Infer from reduced/encrypted data + Active + Manipulate / inject data in transit + Static key exfiltration + Obtain key material once / rarely + Dynamic key exfiltration + Obtain per-session key material + Content exfiltration + Access data at rest + + +Security analyses of Internet protocols commonly consider two classes +of attacker: Passive pervasive attackers, who can simply listen in on +communications as they transit the network, and active pervasive +attackers, who can modify or delete packets in addition to simply +collecting them. + +In the context of pervasive passive surveillance, these attacks take +on an even greater significance. In the past, these attackers were +often assumed to operate near the edge of the network, where attacks +can be simpler. For example, in some LANs, it is simple for any node +to engage in passive listening to other nodes’ traffic or inject +packets to accomplish active pervasive attacks. However, as we now +know, both passive and active pervasive attacks are undertaken by +pervasive attackers closer to the core of the network, greatly +expanding the scope and capability of the attacker. + +Eavesdropping and observation at a larger scale make passive inference +attacks easier to carry out: a passive pervasive attacker with access to a +large portion of the Internet can analyze collected traffic to create +a much more detailed view of individual behavior than an attacker that +collects at a single point. Even the usual claim that encryption +defeats passive pervasive attackers is weakened, since a pervasive flow +access attacker can infer relationships from correlations over large +numbers of sessions, e.g., pairing encrypted sessions with unencrypted +sessions from the same host, or performing traffic fingerprinting +between known and unknown encrypted sessions. Reports on the NSA +XKEYSCORE system would indicate it is an example of such an attacker. + +An active pervasive attacker likewise has capabilities +beyond those of a localized active attacker. Flow +modification attacks are often limited by network topology, for +example by a requirement that the attacker be able to see a targeted +session as well as inject packets into it. A pervasive flow +modification attacker with access at multiple points within the core +of the Internet is able to overcome these topological limitations and +perform attacks over a much broader scope. Being positioned in the +core of the network rather than the edge can also enable an active +pervasive attacker to reroute targeted traffic, amplifying the +ability to perform both eavesdropping and traffic injection. +Active pervasive attackers can also benefit from passive pervasive +collection to identify vulnerable hosts. + +While not directly related to pervasiveness, attackers that are in a +position to mount a active pervasive attack are also often +in a position to subvert authentication, a traditional protection +against such attacks. Authentication in the Internet is often +achieved via trusted third party authorities such as the Certificate +Authorities (CAs) that provide web sites with authentication +credentials. An attacker with sufficient resources may also be able to +induce an authority to grant credentials for an identity of the +attacker’s choosing. If the parties to a communication will trust +multiple authorities to certify a specific identity, this attack may +be mounted by suborning any one of the authorities (the proverbial +“weakest link”). Subversion of authorities in this way can allow an +active attack to succeed in spite of an authentication +check. + +Beyond these three classes (observation, inference, and active), +reports on the BULLRUN effort to defeat encryption and the PRISM +effort to obtain data from service providers suggest three more +classes of attack: + + + Static key exfiltration + Dynamic key exfiltration + Content exfiltration + + +These attacks all rely on a collaborator providing the attacker with +some information, either keys or data. These attacks have not +traditionally been considered in scope for the Security Considerations +sections of IETF protocols, as they occur outside the protocol. + +The term “key exfiltration” refers to the transfer of keying material +for an encrypted communication from the collaborator to the attacker. +By “static”, we mean that the transfer of keys happens once, or +rarely, typically of a long-lived key. For example, this case would +cover a web site operator that provides the private key corresponding +to its HTTPS certificate to an intelligence agency. + +“Dynamic” key exfiltration, by contrast, refers to attacks in which +the collaborator delivers keying material to the attacker frequently, +e.g., on a per-session basis. This does not necessarily imply +frequent communications with the attacker; the transfer of keying +material may be virtual. For example, if an endpoint were modified in +such a way that the attacker could predict the state of its +psuedorandom number generator, then the attacker would be able to +derive per-session keys even without per-session communications. + +Finally, content exfiltration is the attack in which the collaborator +simply provides the attacker with the desired data or metadata. Unlike +the key exfiltration cases, this attack does not require the attacker +to capture the desired data as it flows through the network. The exfiltration +is of data at rest, rather than data in transit. This increases the scope of data +that the attacker can obtain, since the attacker can access historical +data – the attacker does not have to be listening +at the time the communication happens. + +Exfiltration attacks can be accomplished via attacks against one of +the parties to a communication, i.e., by the attacker stealing the +keys or content rather than the party providing them willingly. In +these cases, the party may not be aware that they are collaborating, +at least at a human level. Rather, the subverted technical assets are +“collaborating” with the attacker (by providing keys/content) without +their owner’s knowledge or consent. + +Any party that has access to encryption keys or unencrypted data can +be a collaborator. While collaborators are typically the endpoints of +a communication (with encryption securing the links), intermediaries +in an unencrypted communication can also facilitate content +exfiltration attacks as collaborators by providing the attacker access +to those communications. For example, documents describing the NSA +PRISM program claim that NSA is able to access user data directly from +servers, where it is stored unencrypted. In these cases, the operator +of the server would be a collaborator, if an unwitting one. By +contrast, in the NSA MUSCULAR program, a set of collaborators enabled +attackers to access the cables connecting data centers used by service +providers such as Google and Yahoo. Because communications among +these data centers were not encrypted, the collaboration by an +intermediate entity allowed NSA to collect unencrypted user data. + +
+
+ + + Attack Class + Cost / Risk to Attacker + Passive observation + Passive data access + Passive inference + Passive data access + processing + Active + Active data access + processing + Static key exfiltration + One-time interaction + Dynamic key exfiltration + Ongoing interaction / code change + Content exfiltration + Ongoing, bulk interaction + + +Each of the attack types discussed in the previous section entails +certain costs and risks. These costs differ by attack, and can be +helpful in guiding response to pervasive attack. + +Depending on the attack, the attacker may be exposed to several types +of risk, ranging from simply losing access to arrest or prosecution. +In order for any of these negative consequences to occur, however, the +attacker must first be discovered and identified. So the primary risk +we focus on here is the risk of discovery and attribution. + +A passive pervasive attack is the simplest to mount in some ways. The base +requirement is that the attacker obtain physical access to a +communications medium and extract communications from it. For +example, the attacker might tap a fiber-optic cable, acquire a mirror +port on a switch, or listen to a wireless signal. The need for these +taps to have physical access or proximity to a link exposes the +attacker to the risk that the taps will be discovered. For example, a +fiber tap or mirror port might be discovered by network operators +noticing increased attenuation in the fiber or a change in switch +configuration. Of course, passive pervasive attacks may be accomplished +with the cooperation of the network operator, in which case there is a +risk that the attacker’s interactions with the network operator will +be exposed. + +In many ways, the costs and risks for an active pervasive attack are +similar to those for a passive pervasive attack, with a few additions. An +active attacker requires more robust network access than a +passive attacker, since for example they will often need to +transmit data as well as receiving it. In the wireless example above, +the attacker would need to act as an transmitter as well as receiver, +greatly increasing the probability the attacker will be discovered +(e.g., using direction-finding technology). Active attacks +are also much more observable at higher layers of the network. For +example, an active attacker that attempts to use a +mis-issued certificate could be detected via Certificate Transparency +. + +In terms of raw implementation complexity, passive pervasive attacks require +only enough processing to extract information from the network and +store it. Active pervasive attacks, by contrast, often depend on +winning race conditions to inject packets into active connections. So +active pervasive attacks in the core of the network require +processing hardware to that can operate at line speed (roughly 100Gbps +to 1Tbps in the core) to identify opportunities for attack and insert +attack traffic in a high-volume traffic. Key exfiltration attacks +rely on passive pervasive attack for access to encrypted data, with the +collaborator providing keys to decrypt the data. So the attacker +undertakes the cost and risk of a passive pervasive attack, as well as +additional risk of discovery via the interactions that the attacker +has with the collaborator. + +Some active attacks are more expensive than others. For example, active +man-in-the-middle (MITM) attacks require access to one or more points on a +communication’s network path that allow visibility of the entire session and +the ability to modify or drop legitimate packets in favor of the attacker’s +packets. A similar but weaker form of attack, called an active +man-on-the-side (MOTS), requires access to only part of the session. In an +active MOTS attack, the attacker need only be able to inject or modify traffic +on the network element the attacker has access to. While this may not allow +for full control of a communication session (as in an MITM attack), the +attacker can perform a number of powerful attacks, including but not limited +to: injecting packets that could terminate the session (e.g., TCP RST +packets), sending a fake DNS reply to redirect ensuing TCP connections to an +address of the attacker’s choice (i.e., winning a “DNS response race”), and +mounting an HTTP Redirect attack by observing a TCP/HTTP connection to a +target address and injecting a TCP data packet containing an HTTP redirect. +For example, the system dubbed by researchers as China’s “Great Cannon” + can operate in ful MITM mode to accomplish very complex +attacks that can modify content in transit while the well-known Great Firewall +of China is a MOTS system that focuses on blocking access to certain kinds of +traffic and destinations via TCP RST packet injection. + +In this sense, static exfiltration has a lower risk profile than +dynamic. In the static case, the attacker need only interact with the +collaborator a small number of times, possibly only once, say to +exchange a private key. In the dynamic case, the attacker must have +continuing interactions with the collaborator. As noted above these +interactions may be real, such as in-person meetings, or virtual, such as +software modifications that render keys available to the attacker. +Both of these types of interactions introduce a risk that they will be +discovered, e.g., by employees of the collaborator organization +noticing suspicious meetings or suspicious code changes. + +Content exfiltration has a similar risk profile to dynamic key +exfiltration. In a content exfiltration attack, the attacker saves +the cost and risk of conducting a passive pervasive attack. The risk of +discovery through interactions with the collaborator, however, is +still present, and may be higher. The content of a communication is +obviously larger than the key used to encrypt it, often by several +orders of magnitude. So in the content exfiltration case, the +interactions between the collaborator and the attacker need to be much +higher-bandwidth than in the key exfiltration cases, with a +corresponding increase in the risk that this high-bandwidth channel +will be discovered. + +It should also be noted that in these latter three exfiltration cases, +the collaborator also undertakes a risk that his collaboration with +the attacker will be discovered. Thus the attacker may have to incur +additional cost in order to convince the collaborator to participate +in the attack. Likewise, the scope of these attacks is limited to +case where the attacker can convince a collaborator to participate. +If the attacker is a national government, for example, it may be able +to compel participation within its borders, but have a much more +difficult time recruiting foreign collaborators. + +As noted above, the collaborator in an exfiltration attack can be +unwitting; the attacker can steal keys or data to enable the attack. +In some ways, the risks of this approach are similar to the case of an +active collaborator. In the static case, the attacker needs to steal +information from the collaborator once; in the dynamic case, the +attacker needs to continued presence inside the collaborators systems. +The main difference is that the risk in this case is of automated +discovery (e.g., by intrusion detection systems) rather than discovery +by humans. + +
+
+
+ +This document describes a threat model for pervasive surveillance +attacks. Mitigations are to be given in a future document. + +
+
+ +This document has no actions for IANA. + +
+
+ +Thanks to Dave Thaler for the list of attacks and taxonomy; to +Security Area Directors Stephen Farrell, Sean Turner, and Kathleen +Moriarty for starting and managing the IETF’s discussion on pervasive +attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, Evangelos +Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, Russ Housley, and the IAB +Privacy and Security Program for their input. + +
+ + + + + + + + +&RFC6973; + + + + + + + + + How the NSA is still harvesting your online data + + The Guardian + + + + + + + NSA's Prism surveillance program: how it works and what it can do + + The Guardian + + + + + + + XKeyscore: NSA tool collects 'nearly everything a user does on the internet' + + The Guardian + + + + + + + How does GCHQ's internet surveillance work? + + The Guardian + + + + + + + N.S.A. Able to Foil Basic Safeguards of Privacy on Web + + The New York Times + + + + + + + Project Bullrun – classification guide to the NSA's decryption program + + The Guardian + + + + + + + Revealed: how US and UK spy agencies defeat internet privacy and security + + The Guardian + + + + + + + Tor + + The Tor Project + + + + + + + How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID + + + + + + + + + 'Tor Stinks' presentation – read the full document + + The Guardian + + + + + + + NSA collecting phone records of millions of Verizon customers daily + + The Guardian + + + + + + + NSA Prism program taps in to user data of Apple, Google and others + + The Guardian + + + + + + + Sigint – how the NSA collaborates with technology companies + + The Guardian + + + + + + + NSA surveillance: A guide to staying secure + + The Guardian + + + + + + + NSA Leak Leaves Crypto-Math Intact but Highlights Known Workarounds + + Technology Review + + + + + + + NSA's Secret Toolbox: Unit Offers Spy Gadgets for Every Need + + + + + + + + + The Digital Arms Race: NSA Preps America for Future Battle + + + + + + + + + The Design and Implementation of Protocol-Based Hidden Key Recovery + + + + + + + + + China's Great Cannon + + + + + + +&RFC1035; +&RFC1918; +&RFC1939; +&RFC2015; +&RFC2821; +&RFC3261; +&RFC3365; +&RFC3501; +&RFC3851; +&RFC4033; +&RFC4301; +&RFC4303; +&RFC4306; +&RFC4949; +&RFC5246; +&RFC5321; +&RFC5655; +&RFC5750; +&RFC6120; +&RFC6962; +&RFC6698; +&RFC7011; +&RFC7258; +&I-D.ietf-dprive-problem-statement; + + + + + + + + + diff --git a/draft-iab-privsec-confidentiality-threat-07.md b/draft-iab-privsec-confidentiality-threat-07.md new file mode 100644 index 0000000..8e913fe --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-07.md @@ -0,0 +1,991 @@ +--- +title: "Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement" +abbrev: Confidentiality Threat Model +docname: draft-iab-privsec-confidentiality-threat-07 +date: 2015-05-28 +category: info +ipr: trust200902 +pi: + toc: yes + +author: + - + ins: R. Barnes + name: Richard Barnes + email: rlb@ipv.sx + - + ins: B. Schneier + name: Bruce Schneier + email: schneier@schneier.com + - + ins: C. Jennings + name: Cullen Jennings + email: fluffy@cisco.com + - + ins: T. Hardie + name: Ted Hardie + email: ted.ietf@gmail.com + - + ins: B. Trammell + name: Brian Trammell + email: ietf@trammell.ch + - + ins: C. Huitema + name: Christian Huitema + email: huitema@huitema.net + - + ins: D. Borkmann + name: Daniel Borkmann + email: dborkman@iogearbox.net + +normative: + RFC6973: + +informative: + pass1: + target: http://www.theguardian.com/world/2013/jun/27/nsa-online-metadata-collection + title: "How the NSA is still harvesting your online data" + author: + organization: The Guardian + date: 2013 + pass2: + target: http://www.theguardian.com/world/2013/jun/08/nsa-prism-server-collection-facebook-google + title: "NSA's Prism surveillance program: how it works and what it can do" + author: + organization: The Guardian + date: 2013 + pass3: + target: http://www.theguardian.com/world/2013/jul/31/nsa-top-secret-program-online-data + title: "XKeyscore: NSA tool collects 'nearly everything a user does on the internet'" + author: + organization: The Guardian + date: 2013 + pass4: + target: http://www.theguardian.com/uk/2013/jun/21/how-does-gchq-internet-surveillance-work + title: "How does GCHQ's internet surveillance work?" + author: + organization: The Guardian + dec1: + target: http://www.nytimes.com/2013/09/06/us/nsa-foils-much-internet-encryption.html + title: "N.S.A. Able to Foil Basic Safeguards of Privacy on Web" + author: + organization: The New York Times + date: 2013 + dec2: + target: http://www.theguardian.com/world/interactive/2013/sep/05/nsa-project-bullrun-classification-guide + title: "Project Bullrun – classification guide to the NSA's decryption program" + author: + organization: The Guardian + date: 2013 + dec3: + target: http://www.theguardian.com/world/2013/sep/05/nsa-gchq-encryption-codes-security + title: "Revealed: how US and UK spy agencies defeat internet privacy and security" + author: + organization: The Guardian + date: 2013 + TOR1: + target: https://www.schneier.com/blog/archives/2013/10/how_the_nsa_att.html + title: "How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID" + author: + name: Bruce Schneier + ins: B. Schneier + date: 2013 + TOR2: + target: http://www.theguardian.com/world/interactive/2013/oct/04/tor-stinks-nsa-presentation-document + title: "'Tor Stinks' presentation – read the full document" + author: + organization: The Guardian + date: 2013 + dir1: + target: http://www.theguardian.com/world/2013/jun/06/nsa-phone-records-verizon-court-order + title: "NSA collecting phone records of millions of Verizon customers daily" + author: + organization: The Guardian + date: 2013 + dir2: + target: http://www.theguardian.com/world/2013/jun/06/us-tech-giants-nsa-data + title: "NSA Prism program taps in to user data of Apple, Google and others" + author: + organization: The Guardian + date: 2013 + dir3: + target: http://www.theguardian.com/world/interactive/2013/sep/05/sigint-nsa-collaborates-technology-companies + title: "Sigint – how the NSA collaborates with technology companies" + author: + organization: The Guardian + date: 2013 + spiegel1: + target: http://www.spiegel.de/international/world/nsa-secret-toolbox-ant-unit-offers-spy-gadgets-for-every-need-a-941006.html + title: "NSA's Secret Toolbox: Unit Offers Spy Gadgets for Every Need" + author: + ins: J Applebaum + name: Jacob Applebaum + author: + ins: J Horchert + name: Judith Horchert + author: + ins: O Reissmann + name: Ole Reissmann + author: + ins: M Rosenbach + name: Marcel Rosenbach + author: + ins: J Schindler + name: Jorg Schindler + author: + ins: C Stocker + name: Christian Stocker + date: 2013-12-30 + spiegel3: + target: http://www.spiegel.de/international/world/new-snowden-docs-indicate-scope-of-nsa-preparations-for-cyber-battle-a-1013409.html + title: "The Digital Arms Race: NSA Preps America for Future Battle" + author: + ins: J Appelbaum + name: Jacob Appelbaum + author: + ins: A Gibson + name: Aaron Gibson + author: + ins: C Guarnieri + name: Claudio Guarnieri + author: + ins: A Muller-Maguhn + name: Andy Muller-Maguhn + author: + ins: M Sontheimer + name: Michael Sontheimer + author: + ins: L Poitras + name: Laura Poitras + author: + ins: M Rosenbach + name: Marcel Rosenbach + author: + ins: L Ryge + name: Leif Ryge + author: + ins: H Schmundt + name: Hilmar Schmundt + date: 2014-01-17 + great-cannon: + target: https://citizenlab.org/2015/04/chinas-great-cannon/ + title: "China's Great Cannon" + author: + name: Bill Marczak + ins: B. Marczak + author: + name: Nicholas Weaver + ins: N. Weaver + author: + name: Jakub Dalek + ins: J. Dalek + author: + name: Roya Ensafi + ins: R. Ensafi + author: + name: David Fifield + ins: D. Fifield + author: + name: Sarah McKune + ins: S. McKune + author: + name: Arn Rey + ins: A. Rey + author: + name: John Scott-Railton + ins: J. Scott-Railton + author: + name: Ronald Deibert + ins: R. Deibert + author: + name: Vern Paxson + ins: V. Paxson + date: 2015 + RFC1035: + RFC1918: + RFC1939: + RFC3261: + RFC3365: + RFC3501: + RFC4033: + RFC4303: + RFC4949: + RFC5246: + RFC5321: + RFC6962: + RFC7011: + RFC7258: + I-D.ietf-dprive-problem-statement: + +--- abstract + + Since the initial revelations of pervasive surveillance in 2013, + several classes of attacks on Internet communications have been + discovered. In this document we develop a threat model that + describes these attacks on Internet confidentiality. We assume an + attacker that is interested in undetected, indiscriminate + eavesdropping. The threat model is based on published, verified + attacks. + + +--- middle + +# Introduction + +Starting in June 2013, documents released to the press by Edward +Snowden have revealed several operations undertaken by intelligence +agencies to exploit Internet communications for intelligence purposes. +These attacks were largely based on protocol vulnerabilities that were +already known to exist. The attacks were nonetheless striking in +their pervasive nature, both in terms of the volume of Internet +traffic targeted, and in terms of the diversity of attack +techniques employed. + +To ensure that the Internet can be trusted by users, it is necessary +for the Internet technical community to address the vulnerabilities +exploited in these attacks {{RFC7258}}. The goal of this document is +to describe more precisely the threats posed by these pervasive +attacks, and based on those threats, lay out the problems that need to +be solved in order to secure the Internet in the face of those +threats. + +The remainder of this document is structured as follows. In +{{adversary}}, we describe an idealized passive pervasive attacker, one which +could completely undetectably compromise communications at Internet +scale. In {{reported}}, we provide a brief summary of some attacks +that have been disclosed, and use these to expand the assumed +capabilities of our idealized attacker. Note that we do not attempt +to describe all possible attacks, but focus on those which result in +undetected eavesdropping. {{model}} describes a threat model based on +these attacks, focusing on classes of attack that have not been a +focus of Internet engineering to date. + +# Terminology {#terminology} + +This document makes extensive use of standard security and privacy +terminology; see {{RFC4949}} and {{RFC6973}}. Terms used from +{{RFC6973}} include Eavesdropper, Observer, Initiator, Intermediary, +Recipient, Attack (in a privacy context), Correlation, Fingerprint, +Traffic Analysis, and Identifiability (and related terms). In +addition, we use a few terms that are specific to the attacks +discussed in this document. Note especially that "passive" and "active" below +do not refer to the effort used to mount the attack; a "passive attack" +is any attack that accesses a flow but does not modify it, while an +"active attack" is any attack that modifies a flow. Some passive attacks +involve active interception and modifications of devices, rather than simple +access to the medium. The introduced terms are: + +Pervasive Attack: +: An attack on Internet communications that makes +use of access at a large number of points in the network, or otherwise +provides the attacker with access to a large amount of Internet +traffic; see {{RFC7258}}. + +Passive Pervasive Attack: +: An eavesdropping attack undertaken by a pervasive attacker, in which the +packets in a traffic stream between two endpoints are intercepted, but +in which the attacker does not modify the packets in the traffic +stream between two endpoints, modify the treatment of packets in the +traffic stream (e.g. delay, routing), or add or remove packets in the +traffic stream. Passive pervasive attacks are undetectable from the +endpoints. Equivalent to passive wiretapping as defined in {{RFC4949}}; +we use an alternate term here since the methods employed are wider +than those implied by the word "wiretapping", including the active +compromise of intermediate systems. + +Active Pervasive Attack: +: An attack undertaken by a pervasive attacker, which in addition to +the elements of a passive pervasive attack, also includes modification, +addition, or removal of +packets in a traffic stream, or modification of treatment of packets +in the traffic stream. Active pervasive attacks provide more +capabilities to the attacker at the risk of possible detection at the +endpoints. Equivalent to active wiretapping as defined in {{RFC4949}}. + +Observation: +: Information collected directly from communications by an +eavesdropper or observer. For example, the knowledge that +<alice@example.com> sent a message to <bob@example.com> +via SMTP taken from the headers of an observed SMTP message would be +an observation. + +Inference: +: Information derived from analysis of information collected +directly from communications by an eavesdropper or observer. For +example, the knowledge that a given web page was accessed by a given +IP address, by comparing the size in octets of measured network flow +records to fingerprints derived from known sizes of linked resources +on the web servers involved, would be an inference. + +Collaborator: +: An entity that is a legitimate participant in a communication, and provides information about that communication to an attacker. Collaborators may either deliberately or unwittingly cooperate with the attacker, in the latter case because the attacker has subverted the collaborator through technical, social, or other means. + +Key Exfiltration: +: The transmission of cryptographic keying material for an encrypted communication +from a collaborator, deliberately or unwittingly, to an attacker. + +Content Exfiltration: +: The transmission of the content of a communication from a collaborator, deliberately or unwittingly, to an attacker + +# An Idealized Passive Pervasive Attacker {#adversary} + +In considering the threat posed by pervasive surveillance, we begin by +defining an idealized passive pervasive attacker. While this attacker +is less capable than those which we now know to have compromised the +Internet from press reports, as elaborated in {{reported}}, it does +set a lower bound on the capabilities of an attacker interested in +indiscriminate passive surveillance while interested in remaining +undetectable. We note that, prior to the Snowden revelations in 2013, +the assumptions of attacker capability presented here would be +considered on the border of paranoia outside the network security +community. + +Our idealized attacker is an indiscriminate eavesdropper on an Internet-attached computer network that: + +- can observe every packet of all communications at any hop in any network path between an initiator and a recipient; +- can observe data at rest in any intermediate system between the endpoints controlled by the initiator and recipient; and +- can share information with other such attackers; but +- takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.). + + The techniques available to our ideal attacker are direct observation + and inference. Direct observation involves taking information + directly from eavesdropped communications, such as URLs identifying + content or email addresses identifying individuals from application- + layer headers. Inference, on the other hand, involves analyzing + observed information to derive new information, such as searching for + application or behavioral fingerprints in observed traffic to derive + information about the observed individual. The use of encryption is + generally sufficient to provide confidentiality by preventing direct + observation of content, assuming of course, uncompromised encryption + implementations and cryptographic keying material. However, + encryption provides less complete protection against inference, + especially inferences based only on plaintext portions of + communications, such as IP and TCP headers for TLS-protected traffic + [RFC5246]). + +## Information subject to direct observation + +Protocols which do not encrypt their payload make the entire content +of the communication available to the idealized attacker along their +path. Following the advice in {{RFC3365}}, most such protocols have a +secure variant which encrypts payload for confidentiality, and these +secure variants are seeing ever-wider deployment. A noteworthy +exception is DNS {{RFC1035}}, as DNSSEC {{RFC4033}} does not have +confidentiality as a requirement. + +This implies that, in the absence of +changes to the protocol as presently under development in the IETF's +DNS Private Exchange (DPRIVE) +working group {{I-D.ietf-dprive-problem-statement}}, all DNS queries and answers generated by the activities +of any protocol are available to the attacker. + +When store-and-forward protocols are used, (e.g. SMTP {{RFC5321}}) +intermediaries leave this data subject to observation by an attacker that +has compromised these intermediaries, +unless the data is encrypted end-to-end by the application layer +protocol, or the implementation uses an encrypted store for this data. + +## Information useful for inference + +Inference is information extracted from later analysis of an observed +or eavesdropped communication, and/or correlation of observed or +eavesdropped information with information available from other +sources. Indeed, most useful inference performed by the attacker falls +under the rubric of correlation. The simplest example of this is the +observation of DNS queries and answers from and to a source and +correlating those with IP addresses with which that source +communicates. This can give access to information otherwise not +available from encrypted application payloads (e.g., the Host: +HTTP/1.1 request header when HTTP is used with TLS). + +Protocols which encrypt their payload using an application- or +transport-layer encryption scheme (e.g. TLS) still expose all the +information in their network and transport layer headers to the +attacker, including source and destination addresses and ports. IPsec +ESP {{RFC4303}} further encrypts the transport-layer headers, but still +leaves IP address information unencrypted; in tunnel mode, these +addresses correspond to the tunnel endpoints. Features of the +security protocols themselves, e.g. the TLS session identifier, +may leak information that can be used for correlation and +inference. While this information is much less semantically rich than +the application payload, it can still be useful for the inferring an +individual's activities. + +Inference can also leverage information obtained from sources other +than direct traffic observation. Geolocation databases, for example, +have been developed that map IP addresses to a location, in order to +provide location-aware services such as targeted advertising. This +location information is often of sufficient resolution that it can be +used to draw further inferences toward identifying or profiling an +individual. + +Social media provide another source of more or less publicly +accessible information. This information can be extremely semantically +rich, including information about an individual's location, +associations with other individuals and groups, and +activities. Further, this information is generally contributed and +curated voluntarily by the individuals themselves: it represents +information which the individuals are not necessarily interested in +protecting for privacy reasons. However, correlation of this social +networking data with information available from direct observation of +network traffic allows the creation of a much richer picture of an +individual's activities than either alone. + +We note with some alarm that there is little that can be done at +protocol design time to limit such correlation by the attacker, and +that the existence of such data sources in many cases greatly +complicates the problem of protecting privacy by hardening protocols +alone. + +## An illustration of an ideal passive pervasive attack + +To illustrate how capable the idealized attacker is even given its +limitations, we explore the non-anonymity of encrypted IP traffic in +this section. Here we examine in detail some inference techniques for +associating a set of addresses with an individual, in order to +illustrate the difficulty of defending communications against our +idealized attacker. Here, the basic problem is that information +radiated even from protocols which have no obvious connection with +personal data can be correlated with other information which can paint +a very rich behavioral picture, that only takes one unprotected link +in the chain to associate with an identity. + +### Analysis of IP headers + +Internet traffic can be monitored by tapping Internet links, or by +installing monitoring tools in Internet routers. Of course, a single +link or a single router only provides access to a fraction of the +global Internet traffic. However, monitoring a number of high capacity +links or a set of routers placed at strategic locations provides +access to a good sampling of Internet traffic. + +Tools like IPFIX {{RFC7011}} allow administrators to acquire +statistics about sequences of packets with some common properties that +pass through a network device. The most common set of properties used +in flow measurement is the "five-tuple" of source and destination +addresses, protocol type, and source and destination ports. These +statistics are commonly used for network engineering, but could +certainly be used for other purposes. + +Let's assume for a moment that IP addresses can be correlated to +specific services or specific users. Analysis of the sequences of +packets will quickly reveal which users use what services, and also +which users engage in peer-to-peer connections with other +users. Analysis of traffic variations over time can be used to detect +increased activity by particular users, or in the case of peer-to-peer +connections increased activity within groups of users. + +### Correlation of IP addresses to user identities + +The correlation of IP addresses with specific users can be done in +various ways. For example, tools like reverse DNS lookup can be used +to retrieve the DNS names of servers. Since the addresses of servers +tend to be quite stable and since servers are relatively less numerous +than users, an attacker could easily maintain its own copy of the DNS +for well-known or popular servers, to accelerate such lookups. + +On the other hand, the reverse lookup of IP addresses of users is +generally less informative. For example, a lookup of the address +currently used by one author's home network returns a name of the form +"c-192-000-002-033.hsd1.wa.comcast.net". This particular type of +reverse DNS lookup generally reveals only coarse-grained location or +provider information, equivalent to that available from geolocation +databases. + +In many jurisdictions, Internet Service Providers (ISPs) are required +to provide identification on a case by case basis of the "owner" of a +specific IP address for law enforcement purposes. This is a reasonably +expedient process for targeted investigations, but pervasive +surveillance requires something more efficient. This provides an +incentive for the attacker to secure the cooperation of the ISP in +order to automate this correlation. + +### Monitoring messaging clients for IP address correlation + +Even if the ISP does not cooperate, user identity can often be +obtained via inference. POP3 {{RFC1939}} and IMAP {{RFC3501}} are used +to retrieve mail from mail servers, while a variant of SMTP is used to +submit messages through mail servers. IMAP connections originate from +the client, and typically start with an authentication exchange in +which the client proves its identity by answering a password +challenge. The same holds for the SIP protocol {{RFC3261}} and many +instant messaging services operating over the Internet using +proprietary protocols. + +The username is directly observable if any of these protocols operate +in cleartext; the username can then be directly associated with the +source address. + +### Retrieving IP addresses from mail headers + +SMTP {{RFC5321}} requires that each successive SMTP relay adds a +"Received" header to the mail headers. The purpose of these headers is +to enable audit of mail transmission, and perhaps to distinguish +between regular mail and spam. Here is an extract from the headers of +a message recently received from the "perpass" mailing list: + +``` + Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?) + (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA + (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100 + Message-ID: <526D7BD2.7070908@example.org> + Date: Sun, 27 Oct 2013 20:47:14 +0000 + From: Some One +``` + +This is the first "Received" header attached to the message by the +first SMTP relay; for privacy reasons, the field values have been +anonymized. We learn here that the message was submitted by "Some One" +on October 27, from a host behind a NAT (192.168.1.100) {{RFC1918}} +that used the IP address 192.0.2.44. The information remained in the +message, and is accessible by all recipients of the "perpass" mailing +list, or indeed by any attacker that sees at least one copy of the +message. + +An attacker that can observe sufficient email traffic can regularly +update the mapping between public IP addresses and individual email +identities. Even if the SMTP traffic was encrypted on submission and +relaying, the attacker can still receive a copy of public mailing +lists like "perpass". + +### Tracking address usage with web cookies + +Many web sites only encrypt a small fraction of their transactions. A +popular pattern is to use HTTPS for the login information, and then +use a "cookie" to associate following clear-text transactions with the +user's identity. Cookies are also used by various advertisement +services to quickly identify the users and serve them with +"personalized" advertisements. Such cookies are particularly useful if +the advertisement services want to keep tracking the user across +multiple sessions that may use different IP addresses. + +As cookies are sent in clear text, an attacker can build a database +that associates cookies to IP addresses for non-HTTPS traffic. If the +IP address is already identified, the cookie can be linked to the user +identify. After that, if the same cookie appears on a new IP address, +the new IP address can be immediately associated with the +pre-determined identity. + +### Graph-based approaches to address correlation + +An attacker can track traffic from an IP address not yet associated +with an individual to various public services (e.g. websites, mail +servers, game servers), and exploit patterns in the observed traffic +to correlate this address with other addresses that show similar +patterns. For example, any two addresses that show connections to the +same IMAP or webmail services, the same set of favorite websites, and +game servers at similar times of day may be associated with the same +individual. Correlated addresses can then be tied to an individual +through one of the techniques above, walking the "network graph" to +expand the set of attributable traffic. + +### Tracking of Link Layer Identifiers + +Moving back down the stack, technologies like Ethernet or Wi-Fi use MAC Addresses to identify link-level destinations. MAC Addresses assigned according to IEEE-802 standards are globally-unique identifiers for the device. If the link is publicly accessible, an attacker can eavesdrop and perform tracking. For example, the attacker can track the wireless traffic at publicly accessible Wi-Fi networks. Simple devices can monitor the traffic, and reveal which MAC Addresses are present. +Also, devices do not need to be connected to a network to expose link-layer identifiers. Active service discovery always discloses the MAC address of the user, and sometimes the SSIDs of previously visited networks. For instance, certain techniques such as the use of “hidden SSIDs” require the mobile device to broadcast the network identifier together with the device identifier. This combination can further expose the user to inference attacks, as more information can be derived from the combination of MAC address, SSID being probed, time and current location. For example, a user actively probing for a semi-unique SSID on a flight out of a certain city can imply that the user is no longer at the physical location of the corresponding AP. +Given that large-scale databases of the MAC addresses of wireless access points for geolocation purposes have been known to exist for some time, the attacker could easily build a database linking link-layer identifiers, time and device or user identities, and use it to track the movement of devices and of their owners. +On the other hand, if the network does not use some form of Wi-Fi encryption, or if the attacker can access the decrypted traffic, the analysis will also provide the correlation between link-layer identifiers such as MAC Addresses and IP addresses. Additional monitoring using techniques exposed in the previous sections will reveal the correlation between MAC addresses, IP addresses, and user identity. For instance, similarly to the use of web cookies, MAC addresses provide identity information that can be used to associate a user to different IP addresses. + +# Reported Instances of Large-Scale Attacks {#reported} + +The situation in reality is more bleak than that suggested by an analysis of +our idealized attacker. Through revelations of sensitive documents in several +media outlets, the Internet community has been made aware of several +intelligence activities conducted by US and UK national intelligence agencies, +particularly the US National Security Agency (NSA) and the UK Government +Communications Headquarters (GCHQ). These documents have revealed methods that +these agencies use to attack Internet applications and obtain sensitive user +information. There is little reason to suppose that only the US or UK +governments are involved in these sorts of activities; the examples are just +ones that were disclosed. We note that these reports are primarily useful as +an illustration of the types of capabilities fielded by pervasive attackers as +of the date of the Snowden leaks in 2013. + +First, they confirm the deployment of large-scale passive +collection of Internet traffic, which confirms the existence of +pervasive passive attackers with at least the capabilities of our +idealized attacker. For example {{pass1}}{{pass2}}{{pass3}}{{pass4}}: + +- NSA's XKEYSCORE system accesses data from multiple access points and +searches for "selectors" such as email addresses, at the scale of tens +of terabytes of data per day. + +- GCHQ's Tempora system appears to have access to around 1,500 major cables +passing through the UK. + +- NSA's MUSCULAR program has tapped cables between data centers +belonging to major service providers. + +- Several programs appear to perform wide-scale collection +of cookies in web traffic and location data from location-aware +portable devices such as smartphones. + +However, the capabilities described by these reports go beyond those of our +idealized attacker. They include the compromise of cryptographic protocols, +including decryption of TLS-protected Internet sessions {{dec1}}{{dec2}}{{dec3}}. +For example, the NSA BULLRUN project worked to undermine encryption through +multiple approaches, including covert modifications to cryptographic +software on end systems. + +Reported capabilities include the direct compromise of intermediate systems +and arrangements with service providers for bulk data and metadata +access {{dir1}}{{dir2}}{{dir3}}, bypassing the need to capture +traffic on the wire. For example, the NSA PRISM program provides the +agency with access to many types of user data (e.g., email, chat, VoIP). + +The reported capabilities also include elements of active pervasive attack, +including: + +* Insertion of devices as a man-in-the-middle of Internet + transactions {{TOR1}}{{TOR2}}. For example, NSA's QUANTUM system + appears to use several different techniques to hijack HTTP + connections, ranging from DNS response injection to HTTP 302 + redirects. + +* Use of implants on end systems to undermine security and anonymity + features {{dec2}}{{TOR1}}{{TOR2}}. For example, QUANTUM is used to + direct users to a FOXACID server, which in turn delivers an implant + to compromise browsers of Tor users. + +* Use of implants on network elements from many major equipment providers, + including Cisco, Juniper, Huawei, Dell, and HP, as provided by the NSA's + Advanced Network Technology group. {{spiegel1}} + +* Use of botnet-scale collections of compromised hosts {{spiegel3}}. + +The scale of the compromise extends beyond the network to include subversion of the technical standards process itself. For example, there is suspicion that NSA modifications to the DUAL_EC_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA. This RNG was made part of NIST's SP 800-90A, for which NIST acknowledges NSA's assistance. There have also been reports that the NSA paid RSA Security for a related contract with the result that the curve became the default in the RSA BSAFE product line. + +We use the term "pervasive attack" {{RFC7258}} to collectively +describe these operations. The term "pervasive" is used because the +attacks are designed to indiscriminately gather as much data as +possible and to apply selective analysis on targets after the fact. +This means that all, or nearly all, Internet communications are +targets for these attacks. To achieve this scale, the attacks are +physically pervasive; they affect a large number of Internet +communications. They are pervasive in content, consuming and +exploiting any information revealed by the protocol. And they are +pervasive in technology, exploiting many different vulnerabilities in +many different protocols. + +Again, it's important to note that, although the attacks mentioned above were +executed by NSA and GCHQ, there are many other organizations that can mount +pervasive surveillance attacks. Because of the resources required to achieve +pervasive scale, these attacks are most commonly undertaken by nation-state +actors. For example, the Chinese Internet filtering system known as the +"Great Firewall of China" uses several techniques that are similar to the +QUANTUM program, and which have a high degree of pervasiveness with regard to +the Internet in China. Therefore, legal restrictions in any one jurisdiction on pervasive monitoring activities cannot eliminate the risk of pervasive attack to the Internet as a whole. + +# Threat Model {#model} + +Given these disclosures, we must consider a broader threat model. + +Pervasive surveillance aims to collect information across a large +number of Internet communications, analyzing the collected +communications to identify information of interest within individual +communications, or inferring information from correlated +communications. This analysis sometimes benefits from decryption of +encrypted communications and deanonymization of anonymized +communications. As a result, these attackers desire both access to +the bulk of Internet traffic and to the keying material required to +decrypt any traffic that has been encrypted. Even if keys are not +available, note that the presence of a communication and the fact that +it is encrypted may both be inputs to an analysis, even if the +attacker cannot decrypt the communication. + +The attacks listed above highlight new avenues both for access to +traffic and for access to relevant encryption keys. They further +indicate that the scale of surveillance is sufficient to provide a +general capability to cross-correlate communications, a threat not +previously thought to be relevant at the scale of the Internet. + +## Attacker Capabilities + +| Attack Class | Capability | +|:--------------------------|:------------------------------------------| +| Passive observation | Directly capture data in transit | +| Passive inference | Infer from reduced/encrypted data | +| Active | Manipulate / inject data in transit | +| Static key exfiltration | Obtain key material once / rarely | +| Dynamic key exfiltration | Obtain per-session key material | +| Content exfiltration | Access data at rest | + +Security analyses of Internet protocols commonly consider two classes +of attacker: Passive pervasive attackers, who can simply listen in on +communications as they transit the network, and active pervasive +attackers, who can modify or delete packets in addition to simply +collecting them. + +In the context of pervasive passive surveillance, these attacks take +on an even greater significance. In the past, these attackers were +often assumed to operate near the edge of the network, where attacks +can be simpler. For example, in some LANs, it is simple for any node +to engage in passive listening to other nodes' traffic or inject +packets to accomplish active pervasive attacks. However, as we now +know, both passive and active pervasive attacks are undertaken by +pervasive attackers closer to the core of the network, greatly +expanding the scope and capability of the attacker. + +Eavesdropping and observation at a larger scale make passive inference +attacks easier to carry out: a passive pervasive attacker with access to a +large portion of the Internet can analyze collected traffic to create +a much more detailed view of individual behavior than an attacker that +collects at a single point. Even the usual claim that encryption +defeats passive pervasive attackers is weakened, since a pervasive flow +access attacker can infer relationships from correlations over large +numbers of sessions, e.g., pairing encrypted sessions with unencrypted +sessions from the same host, or performing traffic fingerprinting +between known and unknown encrypted sessions. Reports on the NSA +XKEYSCORE system would indicate it is an example of such an attacker. + +An active pervasive attacker likewise has capabilities +beyond those of a localized active attacker. Flow +modification attacks are often limited by network topology, for +example by a requirement that the attacker be able to see a targeted +session as well as inject packets into it. A pervasive flow +modification attacker with access at multiple points within the core +of the Internet is able to overcome these topological limitations and +perform attacks over a much broader scope. Being positioned in the +core of the network rather than the edge can also enable an active +pervasive attacker to reroute targeted traffic, amplifying the +ability to perform both eavesdropping and traffic injection. +Active pervasive attackers can also benefit from passive pervasive +collection to identify vulnerable hosts. + +While not directly related to pervasiveness, attackers that are in a +position to mount a active pervasive attack are also often +in a position to subvert authentication, a traditional protection +against such attacks. Authentication in the Internet is often +achieved via trusted third party authorities such as the Certificate +Authorities (CAs) that provide web sites with authentication +credentials. An attacker with sufficient resources may also be able to +induce an authority to grant credentials for an identity of the +attacker’s choosing. If the parties to a communication will trust +multiple authorities to certify a specific identity, this attack may +be mounted by suborning any one of the authorities (the proverbial +"weakest link"). Subversion of authorities in this way can allow an +active attack to succeed in spite of an authentication +check. + +Beyond these three classes (observation, inference, and active), +reports on the BULLRUN effort to defeat encryption and the PRISM +effort to obtain data from service providers suggest three more +classes of attack: + +* Static key exfiltration +* Dynamic key exfiltration +* Content exfiltration + +These attacks all rely on a collaborator providing the attacker with +some information, either keys or data. These attacks have not +traditionally been considered in scope for the Security Considerations +sections of IETF protocols, as they occur outside the protocol. + +The term "key exfiltration" refers to the transfer of keying material +for an encrypted communication from the collaborator to the attacker. +By "static", we mean that the transfer of keys happens once, or +rarely, typically of a long-lived key. For example, this case would +cover a web site operator that provides the private key corresponding +to its HTTPS certificate to an intelligence agency. + +"Dynamic" key exfiltration, by contrast, refers to attacks in which +the collaborator delivers keying material to the attacker frequently, +e.g., on a per-session basis. This does not necessarily imply +frequent communications with the attacker; the transfer of keying +material may be virtual. For example, if an endpoint were modified in +such a way that the attacker could predict the state of its +psuedorandom number generator, then the attacker would be able to +derive per-session keys even without per-session communications. + +Finally, content exfiltration is the attack in which the collaborator +simply provides the attacker with the desired data or metadata. Unlike +the key exfiltration cases, this attack does not require the attacker +to capture the desired data as it flows through the network. The exfiltration +is of data at rest, rather than data in transit. This increases the scope of data +that the attacker can obtain, since the attacker can access historical +data -- the attacker does not have to be listening +at the time the communication happens. + +Exfiltration attacks can be accomplished via attacks against one of +the parties to a communication, i.e., by the attacker stealing the +keys or content rather than the party providing them willingly. In +these cases, the party may not be aware that they are collaborating, +at least at a human level. Rather, the subverted technical assets are +"collaborating" with the attacker (by providing keys/content) without +their owner's knowledge or consent. + +Any party that has access to encryption keys or unencrypted data can +be a collaborator. While collaborators are typically the endpoints of +a communication (with encryption securing the links), intermediaries +in an unencrypted communication can also facilitate content +exfiltration attacks as collaborators by providing the attacker access +to those communications. For example, documents describing the NSA +PRISM program claim that NSA is able to access user data directly from +servers, where it is stored unencrypted. In these cases, the operator +of the server would be a collaborator, if an unwitting one. By +contrast, in the NSA MUSCULAR program, a set of collaborators enabled +attackers to access the cables connecting data centers used by service +providers such as Google and Yahoo. Because communications among +these data centers were not encrypted, the collaboration by an +intermediate entity allowed NSA to collect unencrypted user data. + +## Attacker Costs + +| Attack Class | Cost / Risk to Attacker | +|:--------------------------|:----------------------------------| +| Passive observation | Passive data access | +| Passive inference | Passive data access + processing | +| Active | Active data access + processing | +| Static key exfiltration | One-time interaction | +| Dynamic key exfiltration | Ongoing interaction / code change | +| Content exfiltration | Ongoing, bulk interaction | + +Each of the attack types discussed in the previous section entails +certain costs and risks. These costs differ by attack, and can be +helpful in guiding response to pervasive attack. + +Depending on the attack, the attacker may be exposed to several types +of risk, ranging from simply losing access to arrest or prosecution. +In order for any of these negative consequences to occur, however, the +attacker must first be discovered and identified. So the primary risk +we focus on here is the risk of discovery and attribution. + +A passive pervasive attack is the simplest to mount in some ways. The base +requirement is that the attacker obtain physical access to a +communications medium and extract communications from it. For +example, the attacker might tap a fiber-optic cable, acquire a mirror +port on a switch, or listen to a wireless signal. The need for these +taps to have physical access or proximity to a link exposes the +attacker to the risk that the taps will be discovered. For example, a +fiber tap or mirror port might be discovered by network operators +noticing increased attenuation in the fiber or a change in switch +configuration. Of course, passive pervasive attacks may be accomplished +with the cooperation of the network operator, in which case there is a +risk that the attacker's interactions with the network operator will +be exposed. + +In many ways, the costs and risks for an active pervasive attack are +similar to those for a passive pervasive attack, with a few additions. An +active attacker requires more robust network access than a +passive attacker, since for example they will often need to +transmit data as well as receive it. In the wireless example above, +the attacker would need to act as an transmitter as well as receiver, +greatly increasing the probability the attacker will be discovered +(e.g., using direction-finding technology). Active attacks +are also much more observable at higher layers of the network. For +example, an active attacker that attempts to use a +mis-issued certificate could be detected via Certificate Transparency +{{RFC6962}}. + +In terms of raw implementation complexity, passive pervasive attacks require +only enough processing to extract information from the network and +store it. Active pervasive attacks, by contrast, often depend on +winning race conditions to inject packets into active connections. So +active pervasive attacks in the core of the network require +processing hardware to that can operate at line speed (roughly 100Gbps +to 1Tbps in the core) to identify opportunities for attack and insert +attack traffic in a high-volume traffic. Key exfiltration attacks +rely on passive pervasive attack for access to encrypted data, with the +collaborator providing keys to decrypt the data. So the attacker +undertakes the cost and risk of a passive pervasive attack, as well as +additional risk of discovery via the interactions that the attacker +has with the collaborator. + +Some active attacks are more expensive than others. For example, active +man-in-the-middle (MITM) attacks require access to one or more points on a +communication's network path that allow visibility of the entire session and +the ability to modify or drop legitimate packets in favor of the attacker's +packets. A similar but weaker form of attack, called an active +man-on-the-side (MOTS), requires access to only part of the session. In an +active MOTS attack, the attacker need only be able to inject or modify traffic +on the network element the attacker has access to. While this may not allow +for full control of a communication session (as in an MITM attack), the +attacker can perform a number of powerful attacks, including but not limited +to: injecting packets that could terminate the session (e.g., TCP RST +packets), sending a fake DNS reply to redirect ensuing TCP connections to an +address of the attacker's choice (i.e., winning a "DNS response race"), and +mounting an HTTP Redirect attack by observing a TCP/HTTP connection to a +target address and injecting a TCP data packet containing an HTTP redirect. +For example, the system dubbed by researchers as China's "Great Cannon" +{{great-cannon}} can operate in ful MITM mode to accomplish very complex +attacks that can modify content in transit while the well-known Great Firewall +of China is a MOTS system that focuses on blocking access to certain kinds of +traffic and destinations via TCP RST packet injection. + +In this sense, static exfiltration has a lower risk profile than +dynamic. In the static case, the attacker need only interact with the +collaborator a small number of times, possibly only once, say to +exchange a private key. In the dynamic case, the attacker must have +continuing interactions with the collaborator. As noted above these +interactions may be real, such as in-person meetings, or virtual, such as +software modifications that render keys available to the attacker. +Both of these types of interactions introduce a risk that they will be +discovered, e.g., by employees of the collaborator organization +noticing suspicious meetings or suspicious code changes. + +Content exfiltration has a similar risk profile to dynamic key +exfiltration. In a content exfiltration attack, the attacker saves +the cost and risk of conducting a passive pervasive attack. The risk of +discovery through interactions with the collaborator, however, is +still present, and may be higher. The content of a communication is +obviously larger than the key used to encrypt it, often by several +orders of magnitude. So in the content exfiltration case, the +interactions between the collaborator and the attacker need to be much +higher-bandwidth than in the key exfiltration cases, with a +corresponding increase in the risk that this high-bandwidth channel +will be discovered. + +It should also be noted that in these latter three exfiltration cases, +the collaborator also undertakes a risk that his collaboration with +the attacker will be discovered. Thus the attacker may have to incur +additional cost in order to convince the collaborator to participate +in the attack. Likewise, the scope of these attacks is limited to +case where the attacker can convince a collaborator to participate. +If the attacker is a national government, for example, it may be able +to compel participation within its borders, but have a much more +difficult time recruiting foreign collaborators. + +As noted above, the collaborator in an exfiltration attack can be +unwitting; the attacker can steal keys or data to enable the attack. +In some ways, the risks of this approach are similar to the case of an +active collaborator. In the static case, the attacker needs to steal +information from the collaborator once; in the dynamic case, the +attacker needs to continued presence inside the collaborators systems. +The main difference is that the risk in this case is of automated +discovery (e.g., by intrusion detection systems) rather than discovery +by humans. + +# Security Considerations + +This document describes a threat model for pervasive surveillance +attacks. Mitigations are to be given in a future document. + +# IANA Considerations + +This document has no actions for IANA. + +# IAB Members at the Time of Approval + + Jari Arkko (IETF Chair) + Mary Barnes + Marc Blanchet + Ralph Droms + Ted Hardie + Joe Hildebrand + Russ Housley + Erik Nordmark + Robert Sparks + Andrew Sullivan + Dave Thaler + Brian Trammell + Suzanne Woolf + +# Acknowledgements + +Thanks to Dave Thaler for the list of attacks and taxonomy; to Security Area +Directors Stephen Farrell, Sean Turner, and Kathleen Moriarty for starting and +managing the IETF's discussion on pervasive attack; and to Stephan Neuhaus, +Mark Townsley, Chris Inacio, Evangelos Halepilidis, Bjoern Hoehrmann, Aziz +Mohaisen, Russ Housley, Joe Hall, Andrew Sullivan, the IEEE 802 Privacy +Executive Committee SG, and the IAB Privacy and Security Program for their +input. diff --git a/draft-iab-privsec-confidentiality-threat-07.pdf b/draft-iab-privsec-confidentiality-threat-07.pdf new file mode 100644 index 0000000..d753ed7 Binary files /dev/null and b/draft-iab-privsec-confidentiality-threat-07.pdf differ diff --git a/draft-iab-privsec-confidentiality-threat-07.txt b/draft-iab-privsec-confidentiality-threat-07.txt new file mode 100644 index 0000000..c9c7a3b --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-07.txt @@ -0,0 +1,1344 @@ + + + + +Network Working Group R. Barnes +Internet-Draft +Intended status: Informational B. Schneier +Expires: November 29, 2015 + C. Jennings + + T. Hardie + + B. Trammell + + C. Huitema + + D. Borkmann + + May 28, 2015 + + + Confidentiality in the Face of Pervasive Surveillance: A Threat Model + and Problem Statement + draft-iab-privsec-confidentiality-threat-07 + +Abstract + + Since the initial revelations of pervasive surveillance in 2013, + several classes of attacks on Internet communications have been + discovered. In this document we develop a threat model that + describes these attacks on Internet confidentiality. We assume an + attacker that is interested in undetected, indiscriminate + eavesdropping. The threat model is based on published, verified + attacks. + +Status of This Memo + + This Internet-Draft is submitted in full conformance with the + provisions of BCP 78 and BCP 79. + + Internet-Drafts are working documents of the Internet Engineering + Task Force (IETF). Note that other groups may also distribute + working documents as Internet-Drafts. The list of current Internet- + Drafts is at http://datatracker.ietf.org/drafts/current/. + + Internet-Drafts are draft documents valid for a maximum of six months + and may be updated, replaced, or obsoleted by other documents at any + time. It is inappropriate to use Internet-Drafts as reference + material or to cite them other than as "work in progress." + + This Internet-Draft will expire on November 29, 2015. + + + + +Barnes, et al. Expires November 29, 2015 [Page 1] + +Internet-Draft Confidentiality Threat Model May 2015 + + +Copyright Notice + + Copyright (c) 2015 IETF Trust and the persons identified as the + document authors. All rights reserved. + + This document is subject to BCP 78 and the IETF Trust's Legal + Provisions Relating to IETF Documents + (http://trustee.ietf.org/license-info) in effect on the date of + publication of this document. Please review these documents + carefully, as they describe your rights and restrictions with respect + to this document. Code Components extracted from this document must + include Simplified BSD License text as described in Section 4.e of + the Trust Legal Provisions and are provided without warranty as + described in the Simplified BSD License. + +Table of Contents + + 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3 + 2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3 + 3. An Idealized Passive Pervasive Attacker . . . . . . . . . . . 5 + 3.1. Information subject to direct observation . . . . . . . . 6 + 3.2. Information useful for inference . . . . . . . . . . . . 6 + 3.3. An illustration of an ideal passive pervasive attack . . 7 + 3.3.1. Analysis of IP headers . . . . . . . . . . . . . . . 7 + 3.3.2. Correlation of IP addresses to user identities . . . 8 + 3.3.3. Monitoring messaging clients for IP address + correlation . . . . . . . . . . . . . . . . . . . . . 8 + 3.3.4. Retrieving IP addresses from mail headers . . . . . . 9 + 3.3.5. Tracking address usage with web cookies . . . . . . . 9 + 3.3.6. Graph-based approaches to address correlation . . . . 10 + 3.3.7. Tracking of Link Layer Identifiers . . . . . . . . . 10 + 4. Reported Instances of Large-Scale Attacks . . . . . . . . . . 11 + 5. Threat Model . . . . . . . . . . . . . . . . . . . . . . . . 13 + 5.1. Attacker Capabilities . . . . . . . . . . . . . . . . . . 14 + 5.2. Attacker Costs . . . . . . . . . . . . . . . . . . . . . 17 + 6. Security Considerations . . . . . . . . . . . . . . . . . . . 19 + 7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 19 + 8. IAB Members at the Time of Approval . . . . . . . . . . . . . 20 + 9. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 20 + 10. References . . . . . . . . . . . . . . . . . . . . . . . . . 20 + 10.1. Normative References . . . . . . . . . . . . . . . . . . 20 + 10.2. Informative References . . . . . . . . . . . . . . . . . 20 + Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 23 + + + + + + + + +Barnes, et al. Expires November 29, 2015 [Page 2] + +Internet-Draft Confidentiality Threat Model May 2015 + + +1. Introduction + + Starting in June 2013, documents released to the press by Edward + Snowden have revealed several operations undertaken by intelligence + agencies to exploit Internet communications for intelligence + purposes. These attacks were largely based on protocol + vulnerabilities that were already known to exist. The attacks were + nonetheless striking in their pervasive nature, both in terms of the + volume of Internet traffic targeted, and in terms of the diversity of + attack techniques employed. + + To ensure that the Internet can be trusted by users, it is necessary + for the Internet technical community to address the vulnerabilities + exploited in these attacks [RFC7258]. The goal of this document is + to describe more precisely the threats posed by these pervasive + attacks, and based on those threats, lay out the problems that need + to be solved in order to secure the Internet in the face of those + threats. + + The remainder of this document is structured as follows. In + Section 3, we describe an idealized passive pervasive attacker, one + which could completely undetectably compromise communications at + Internet scale. In Section 4, we provide a brief summary of some + attacks that have been disclosed, and use these to expand the assumed + capabilities of our idealized attacker. Note that we do not attempt + to describe all possible attacks, but focus on those which result in + undetected eavesdropping. Section 5 describes a threat model based + on these attacks, focusing on classes of attack that have not been a + focus of Internet engineering to date. + +2. Terminology + + This document makes extensive use of standard security and privacy + terminology; see [RFC4949] and [RFC6973]. Terms used from [RFC6973] + include Eavesdropper, Observer, Initiator, Intermediary, Recipient, + Attack (in a privacy context), Correlation, Fingerprint, Traffic + Analysis, and Identifiability (and related terms). In addition, we + use a few terms that are specific to the attacks discussed in this + document. Note especially that "passive" and "active" below do not + refer to the effort used to mount the attack; a "passive attack" is + any attack that accesses a flow but does not modify it, while an + "active attack" is any attack that modifies a flow. Some passive + attacks involve active interception and modifications of devices, + rather than simple access to the medium. The introduced terms are: + + Pervasive Attack: An attack on Internet communications that makes + use of access at a large number of points in the network, or + + + + +Barnes, et al. Expires November 29, 2015 [Page 3] + +Internet-Draft Confidentiality Threat Model May 2015 + + + otherwise provides the attacker with access to a large amount of + Internet traffic; see [RFC7258]. + + Passive Pervasive Attack: An eavesdropping attack undertaken by a + pervasive attacker, in which the packets in a traffic stream + between two endpoints are intercepted, but in which the attacker + does not modify the packets in the traffic stream between two + endpoints, modify the treatment of packets in the traffic stream + (e.g. delay, routing), or add or remove packets in the traffic + stream. Passive pervasive attacks are undetectable from the + endpoints. Equivalent to passive wiretapping as defined in + [RFC4949]; we use an alternate term here since the methods + employed are wider than those implied by the word "wiretapping", + including the active compromise of intermediate systems. + + Active Pervasive Attack: An attack undertaken by a pervasive + attacker, which in addition to the elements of a passive pervasive + attack, also includes modification, addition, or removal of + packets in a traffic stream, or modification of treatment of + packets in the traffic stream. Active pervasive attacks provide + more capabilities to the attacker at the risk of possible + detection at the endpoints. Equivalent to active wiretapping as + defined in [RFC4949]. + + Observation: Information collected directly from communications by + an eavesdropper or observer. For example, the knowledge that + sent a message to via SMTP + taken from the headers of an observed SMTP message would be an + observation. + + Inference: Information derived from analysis of information + collected directly from communications by an eavesdropper or + observer. For example, the knowledge that a given web page was + accessed by a given IP address, by comparing the size in octets of + measured network flow records to fingerprints derived from known + sizes of linked resources on the web servers involved, would be an + inference. + + Collaborator: An entity that is a legitimate participant in a + communication, and provides information about that communication + to an attacker. Collaborators may either deliberately or + unwittingly cooperate with the attacker, in the latter case + because the attacker has subverted the collaborator through + technical, social, or other means. + + Key Exfiltration: The transmission of cryptographic keying material + for an encrypted communication from a collaborator, deliberately + or unwittingly, to an attacker. + + + +Barnes, et al. Expires November 29, 2015 [Page 4] + +Internet-Draft Confidentiality Threat Model May 2015 + + + Content Exfiltration: The transmission of the content of a + communication from a collaborator, deliberately or unwittingly, to + an attacker + +3. An Idealized Passive Pervasive Attacker + + In considering the threat posed by pervasive surveillance, we begin + by defining an idealized passive pervasive attacker. While this + attacker is less capable than those which we now know to have + compromised the Internet from press reports, as elaborated in + Section 4, it does set a lower bound on the capabilities of an + attacker interested in indiscriminate passive surveillance while + interested in remaining undetectable. We note that, prior to the + Snowden revelations in 2013, the assumptions of attacker capability + presented here would be considered on the border of paranoia outside + the network security community. + + Our idealized attacker is an indiscriminate eavesdropper on an + Internet-attached computer network that: + + o can observe every packet of all communications at any hop in any + network path between an initiator and a recipient; + + o can observe data at rest in any intermediate system between the + endpoints controlled by the initiator and recipient; and + + o can share information with other such attackers; but + + o takes no other action with respect to these communications (i.e., + blocking, modification, injection, etc.). + + The techniques available to our ideal attacker are direct + observation and inference. Direct observation involves taking + information directly from eavesdropped communications, such as + URLs identifying content or email addresses identifying + individuals from application- layer headers. Inference, on the + other hand, involves analyzing observed information to derive new + information, such as searching for application or behavioral + fingerprints in observed traffic to derive information about the + observed individual. The use of encryption is generally + sufficient to provide confidentiality by preventing direct + observation of content, assuming of course, uncompromised + encryption implementations and cryptographic keying material. + However, encryption provides less complete protection against + inference, especially inferences based only on plaintext portions + of communications, such as IP and TCP headers for TLS-protected + traffic [RFC5246]). + + + + +Barnes, et al. Expires November 29, 2015 [Page 5] + +Internet-Draft Confidentiality Threat Model May 2015 + + +3.1. Information subject to direct observation + + Protocols which do not encrypt their payload make the entire content + of the communication available to the idealized attacker along their + path. Following the advice in [RFC3365], most such protocols have a + secure variant which encrypts payload for confidentiality, and these + secure variants are seeing ever-wider deployment. A noteworthy + exception is DNS [RFC1035], as DNSSEC [RFC4033] does not have + confidentiality as a requirement. + + This implies that, in the absence of changes to the protocol as + presently under development in the IETF's DNS Private Exchange + (DPRIVE) working group [I-D.ietf-dprive-problem-statement], all DNS + queries and answers generated by the activities of any protocol are + available to the attacker. + + When store-and-forward protocols are used, (e.g. SMTP [RFC5321]) + intermediaries leave this data subject to observation by an attacker + that has compromised these intermediaries, unless the data is + encrypted end-to-end by the application layer protocol, or the + implementation uses an encrypted store for this data. + +3.2. Information useful for inference + + Inference is information extracted from later analysis of an observed + or eavesdropped communication, and/or correlation of observed or + eavesdropped information with information available from other + sources. Indeed, most useful inference performed by the attacker + falls under the rubric of correlation. The simplest example of this + is the observation of DNS queries and answers from and to a source + and correlating those with IP addresses with which that source + communicates. This can give access to information otherwise not + available from encrypted application payloads (e.g., the Host: + HTTP/1.1 request header when HTTP is used with TLS). + + Protocols which encrypt their payload using an application- or + transport-layer encryption scheme (e.g. TLS) still expose all the + information in their network and transport layer headers to the + attacker, including source and destination addresses and ports. + IPsec ESP [RFC4303] further encrypts the transport-layer headers, but + still leaves IP address information unencrypted; in tunnel mode, + these addresses correspond to the tunnel endpoints. Features of the + security protocols themselves, e.g. the TLS session identifier, may + leak information that can be used for correlation and inference. + While this information is much less semantically rich than the + application payload, it can still be useful for the inferring an + individual's activities. + + + + +Barnes, et al. Expires November 29, 2015 [Page 6] + +Internet-Draft Confidentiality Threat Model May 2015 + + + Inference can also leverage information obtained from sources other + than direct traffic observation. Geolocation databases, for example, + have been developed that map IP addresses to a location, in order to + provide location-aware services such as targeted advertising. This + location information is often of sufficient resolution that it can be + used to draw further inferences toward identifying or profiling an + individual. + + Social media provide another source of more or less publicly + accessible information. This information can be extremely + semantically rich, including information about an individual's + location, associations with other individuals and groups, and + activities. Further, this information is generally contributed and + curated voluntarily by the individuals themselves: it represents + information which the individuals are not necessarily interested in + protecting for privacy reasons. However, correlation of this social + networking data with information available from direct observation of + network traffic allows the creation of a much richer picture of an + individual's activities than either alone. + + We note with some alarm that there is little that can be done at + protocol design time to limit such correlation by the attacker, and + that the existence of such data sources in many cases greatly + complicates the problem of protecting privacy by hardening protocols + alone. + +3.3. An illustration of an ideal passive pervasive attack + + To illustrate how capable the idealized attacker is even given its + limitations, we explore the non-anonymity of encrypted IP traffic in + this section. Here we examine in detail some inference techniques + for associating a set of addresses with an individual, in order to + illustrate the difficulty of defending communications against our + idealized attacker. Here, the basic problem is that information + radiated even from protocols which have no obvious connection with + personal data can be correlated with other information which can + paint a very rich behavioral picture, that only takes one unprotected + link in the chain to associate with an identity. + +3.3.1. Analysis of IP headers + + Internet traffic can be monitored by tapping Internet links, or by + installing monitoring tools in Internet routers. Of course, a single + link or a single router only provides access to a fraction of the + global Internet traffic. However, monitoring a number of high + capacity links or a set of routers placed at strategic locations + provides access to a good sampling of Internet traffic. + + + + +Barnes, et al. Expires November 29, 2015 [Page 7] + +Internet-Draft Confidentiality Threat Model May 2015 + + + Tools like IPFIX [RFC7011] allow administrators to acquire statistics + about sequences of packets with some common properties that pass + through a network device. The most common set of properties used in + flow measurement is the "five-tuple" of source and destination + addresses, protocol type, and source and destination ports. These + statistics are commonly used for network engineering, but could + certainly be used for other purposes. + + Let's assume for a moment that IP addresses can be correlated to + specific services or specific users. Analysis of the sequences of + packets will quickly reveal which users use what services, and also + which users engage in peer-to-peer connections with other users. + Analysis of traffic variations over time can be used to detect + increased activity by particular users, or in the case of peer-to- + peer connections increased activity within groups of users. + +3.3.2. Correlation of IP addresses to user identities + + The correlation of IP addresses with specific users can be done in + various ways. For example, tools like reverse DNS lookup can be used + to retrieve the DNS names of servers. Since the addresses of servers + tend to be quite stable and since servers are relatively less + numerous than users, an attacker could easily maintain its own copy + of the DNS for well-known or popular servers, to accelerate such + lookups. + + On the other hand, the reverse lookup of IP addresses of users is + generally less informative. For example, a lookup of the address + currently used by one author's home network returns a name of the + form "c-192-000-002-033.hsd1.wa.comcast.net". This particular type + of reverse DNS lookup generally reveals only coarse-grained location + or provider information, equivalent to that available from + geolocation databases. + + In many jurisdictions, Internet Service Providers (ISPs) are required + to provide identification on a case by case basis of the "owner" of a + specific IP address for law enforcement purposes. This is a + reasonably expedient process for targeted investigations, but + pervasive surveillance requires something more efficient. This + provides an incentive for the attacker to secure the cooperation of + the ISP in order to automate this correlation. + +3.3.3. Monitoring messaging clients for IP address correlation + + Even if the ISP does not cooperate, user identity can often be + obtained via inference. POP3 [RFC1939] and IMAP [RFC3501] are used + to retrieve mail from mail servers, while a variant of SMTP is used + to submit messages through mail servers. IMAP connections originate + + + +Barnes, et al. Expires November 29, 2015 [Page 8] + +Internet-Draft Confidentiality Threat Model May 2015 + + + from the client, and typically start with an authentication exchange + in which the client proves its identity by answering a password + challenge. The same holds for the SIP protocol [RFC3261] and many + instant messaging services operating over the Internet using + proprietary protocols. + + The username is directly observable if any of these protocols operate + in cleartext; the username can then be directly associated with the + source address. + +3.3.4. Retrieving IP addresses from mail headers + + SMTP [RFC5321] requires that each successive SMTP relay adds a + "Received" header to the mail headers. The purpose of these headers + is to enable audit of mail transmission, and perhaps to distinguish + between regular mail and spam. Here is an extract from the headers + of a message recently received from the "perpass" mailing list: + + "Received: from 192-000-002-044.zone13.example.org (HELO + ?192.168.1.100?) (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net + with ESMTPSA (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct + 2013 21:47:14 +0100 Message-ID: <526D7BD2.7070908@example.org> Date: + Sun, 27 Oct 2013 20:47:14 +0000 From: Some One + " + + This is the first "Received" header attached to the message by the + first SMTP relay; for privacy reasons, the field values have been + anonymized. We learn here that the message was submitted by "Some + One" on October 27, from a host behind a NAT (192.168.1.100) + [RFC1918] that used the IP address 192.0.2.44. The information + remained in the message, and is accessible by all recipients of the + "perpass" mailing list, or indeed by any attacker that sees at least + one copy of the message. + + An attacker that can observe sufficient email traffic can regularly + update the mapping between public IP addresses and individual email + identities. Even if the SMTP traffic was encrypted on submission and + relaying, the attacker can still receive a copy of public mailing + lists like "perpass". + +3.3.5. Tracking address usage with web cookies + + Many web sites only encrypt a small fraction of their transactions. + A popular pattern is to use HTTPS for the login information, and then + use a "cookie" to associate following clear-text transactions with + the user's identity. Cookies are also used by various advertisement + services to quickly identify the users and serve them with + "personalized" advertisements. Such cookies are particularly useful + + + +Barnes, et al. Expires November 29, 2015 [Page 9] + +Internet-Draft Confidentiality Threat Model May 2015 + + + if the advertisement services want to keep tracking the user across + multiple sessions that may use different IP addresses. + + As cookies are sent in clear text, an attacker can build a database + that associates cookies to IP addresses for non-HTTPS traffic. If + the IP address is already identified, the cookie can be linked to the + user identify. After that, if the same cookie appears on a new IP + address, the new IP address can be immediately associated with the + pre-determined identity. + +3.3.6. Graph-based approaches to address correlation + + An attacker can track traffic from an IP address not yet associated + with an individual to various public services (e.g. websites, mail + servers, game servers), and exploit patterns in the observed traffic + to correlate this address with other addresses that show similar + patterns. For example, any two addresses that show connections to + the same IMAP or webmail services, the same set of favorite websites, + and game servers at similar times of day may be associated with the + same individual. Correlated addresses can then be tied to an + individual through one of the techniques above, walking the "network + graph" to expand the set of attributable traffic. + +3.3.7. Tracking of Link Layer Identifiers + + Moving back down the stack, technologies like Ethernet or Wi-Fi use + MAC Addresses to identify link-level destinations. MAC Addresses + assigned according to IEEE-802 standards are globally-unique + identifiers for the device. If the link is publicly accessible, an + attacker can eavesdrop and perform tracking. For example, the + attacker can track the wireless traffic at publicly accessible Wi-Fi + networks. Simple devices can monitor the traffic, and reveal which + MAC Addresses are present. Also, devices do not need to be connected + to a network to expose link-layer identifiers. Active service + discovery always discloses the MAC address of the user, and sometimes + the SSIDs of previously visited networks. For instance, certain + techniques such as the use of "hidden SSIDs" require the mobile + device to broadcast the network identifier together with the device + identifier. This combination can further expose the user to + inference attacks, as more information can be derived from the + combination of MAC address, SSID being probed, time and current + location. For example, a user actively probing for a semi-unique + SSID on a flight out of a certain city can imply that the user is no + longer at the physical location of the corresponding AP. Given that + large-scale databases of the MAC addresses of wireless access points + for geolocation purposes have been known to exist for some time, the + attacker could easily build a database linking link-layer + identifiers, time and device or user identities, and use it to track + + + +Barnes, et al. Expires November 29, 2015 [Page 10] + +Internet-Draft Confidentiality Threat Model May 2015 + + + the movement of devices and of their owners. On the other hand, if + the network does not use some form of Wi-Fi encryption, or if the + attacker can access the decrypted traffic, the analysis will also + provide the correlation between link-layer identifiers such as MAC + Addresses and IP addresses. Additional monitoring using techniques + exposed in the previous sections will reveal the correlation between + MAC addresses, IP addresses, and user identity. For instance, + similarly to the use of web cookies, MAC addresses provide identity + information that can be used to associate a user to different IP + addresses. + +4. Reported Instances of Large-Scale Attacks + + The situation in reality is more bleak than that suggested by an + analysis of our idealized attacker. Through revelations of sensitive + documents in several media outlets, the Internet community has been + made aware of several intelligence activities conducted by US and UK + national intelligence agencies, particularly the US National Security + Agency (NSA) and the UK Government Communications Headquarters + (GCHQ). These documents have revealed methods that these agencies + use to attack Internet applications and obtain sensitive user + information. There is little reason to suppose that only the US or + UK governments are involved in these sorts of activities; the + examples are just ones that were disclosed. We note that these + reports are primarily useful as an illustration of the types of + capabilities fielded by pervasive attackers as of the date of the + Snowden leaks in 2013. + + First, they confirm the deployment of large-scale passive collection + of Internet traffic, which confirms the existence of pervasive + passive attackers with at least the capabilities of our idealized + attacker. For example [pass1][pass2][pass3][pass4]: + + o NSA's XKEYSCORE system accesses data from multiple access points + and searches for "selectors" such as email addresses, at the scale + of tens of terabytes of data per day. + + o GCHQ's Tempora system appears to have access to around 1,500 major + cables passing through the UK. + + o NSA's MUSCULAR program has tapped cables between data centers + belonging to major service providers. + + o Several programs appear to perform wide-scale collection of + cookies in web traffic and location data from location-aware + portable devices such as smartphones. + + + + + +Barnes, et al. Expires November 29, 2015 [Page 11] + +Internet-Draft Confidentiality Threat Model May 2015 + + + However, the capabilities described by these reports go beyond those + of our idealized attacker. They include the compromise of + cryptographic protocols, including decryption of TLS-protected + Internet sessions [dec1][dec2][dec3]. For example, the NSA BULLRUN + project worked to undermine encryption through multiple approaches, + including covert modifications to cryptographic software on end + systems. + + Reported capabilities include the direct compromise of intermediate + systems and arrangements with service providers for bulk data and + metadata access [dir1][dir2][dir3], bypassing the need to capture + traffic on the wire. For example, the NSA PRISM program provides the + agency with access to many types of user data (e.g., email, chat, + VoIP). + + The reported capabilities also include elements of active pervasive + attack, including: + + o Insertion of devices as a man-in-the-middle of Internet + transactions [TOR1][TOR2]. For example, NSA's QUANTUM system + appears to use several different techniques to hijack HTTP + connections, ranging from DNS response injection to HTTP 302 + redirects. + + o Use of implants on end systems to undermine security and anonymity + features [dec2][TOR1][TOR2]. For example, QUANTUM is used to + direct users to a FOXACID server, which in turn delivers an + implant to compromise browsers of Tor users. + + o Use of implants on network elements from many major equipment + providers, including Cisco, Juniper, Huawei, Dell, and HP, as + provided by the NSA's Advanced Network Technology group. + [spiegel1] + + o Use of botnet-scale collections of compromised hosts [spiegel3]. + + The scale of the compromise extends beyond the network to include + subversion of the technical standards process itself. For example, + there is suspicion that NSA modifications to the DUAL_EC_DRBG random + number generator were made to ensure that keys generated using that + generator could be predicted by NSA. This RNG was made part of + NIST's SP 800-90A, for which NIST acknowledges NSA's assistance. + There have also been reports that the NSA paid RSA Security for a + related contract with the result that the curve became the default in + the RSA BSAFE product line. + + We use the term "pervasive attack" [RFC7258] to collectively describe + these operations. The term "pervasive" is used because the attacks + + + +Barnes, et al. Expires November 29, 2015 [Page 12] + +Internet-Draft Confidentiality Threat Model May 2015 + + + are designed to indiscriminately gather as much data as possible and + to apply selective analysis on targets after the fact. This means + that all, or nearly all, Internet communications are targets for + these attacks. To achieve this scale, the attacks are physically + pervasive; they affect a large number of Internet communications. + They are pervasive in content, consuming and exploiting any + information revealed by the protocol. And they are pervasive in + technology, exploiting many different vulnerabilities in many + different protocols. + + Again, it's important to note that, although the attacks mentioned + above were executed by NSA and GCHQ, there are many other + organizations that can mount pervasive surveillance attacks. Because + of the resources required to achieve pervasive scale, these attacks + are most commonly undertaken by nation-state actors. For example, + the Chinese Internet filtering system known as the "Great Firewall of + China" uses several techniques that are similar to the QUANTUM + program, and which have a high degree of pervasiveness with regard to + the Internet in China. Therefore, legal restrictions in any one + jurisdiction on pervasive monitoring activities cannot eliminate the + risk of pervasive attack to the Internet as a whole. + +5. Threat Model + + Given these disclosures, we must consider a broader threat model. + + Pervasive surveillance aims to collect information across a large + number of Internet communications, analyzing the collected + communications to identify information of interest within individual + communications, or inferring information from correlated + communications. This analysis sometimes benefits from decryption of + encrypted communications and deanonymization of anonymized + communications. As a result, these attackers desire both access to + the bulk of Internet traffic and to the keying material required to + decrypt any traffic that has been encrypted. Even if keys are not + available, note that the presence of a communication and the fact + that it is encrypted may both be inputs to an analysis, even if the + attacker cannot decrypt the communication. + + The attacks listed above highlight new avenues both for access to + traffic and for access to relevant encryption keys. They further + indicate that the scale of surveillance is sufficient to provide a + general capability to cross-correlate communications, a threat not + previously thought to be relevant at the scale of the Internet. + + + + + + + +Barnes, et al. Expires November 29, 2015 [Page 13] + +Internet-Draft Confidentiality Threat Model May 2015 + + +5.1. Attacker Capabilities + + +--------------------------+-------------------------------------+ + | Attack Class | Capability | + +--------------------------+-------------------------------------+ + | Passive observation | Directly capture data in transit | + | | | + | Passive inference | Infer from reduced/encrypted data | + | | | + | Active | Manipulate / inject data in transit | + | | | + | Static key exfiltration | Obtain key material once / rarely | + | | | + | Dynamic key exfiltration | Obtain per-session key material | + | | | + | Content exfiltration | Access data at rest | + +--------------------------+-------------------------------------+ + + Security analyses of Internet protocols commonly consider two classes + of attacker: Passive pervasive attackers, who can simply listen in on + communications as they transit the network, and active pervasive + attackers, who can modify or delete packets in addition to simply + collecting them. + + In the context of pervasive passive surveillance, these attacks take + on an even greater significance. In the past, these attackers were + often assumed to operate near the edge of the network, where attacks + can be simpler. For example, in some LANs, it is simple for any node + to engage in passive listening to other nodes' traffic or inject + packets to accomplish active pervasive attacks. However, as we now + know, both passive and active pervasive attacks are undertaken by + pervasive attackers closer to the core of the network, greatly + expanding the scope and capability of the attacker. + + Eavesdropping and observation at a larger scale make passive + inference attacks easier to carry out: a passive pervasive attacker + with access to a large portion of the Internet can analyze collected + traffic to create a much more detailed view of individual behavior + than an attacker that collects at a single point. Even the usual + claim that encryption defeats passive pervasive attackers is + weakened, since a pervasive flow access attacker can infer + relationships from correlations over large numbers of sessions, e.g., + pairing encrypted sessions with unencrypted sessions from the same + host, or performing traffic fingerprinting between known and unknown + encrypted sessions. Reports on the NSA XKEYSCORE system would + indicate it is an example of such an attacker. + + + + + +Barnes, et al. Expires November 29, 2015 [Page 14] + +Internet-Draft Confidentiality Threat Model May 2015 + + + An active pervasive attacker likewise has capabilities beyond those + of a localized active attacker. Flow modification attacks are often + limited by network topology, for example by a requirement that the + attacker be able to see a targeted session as well as inject packets + into it. A pervasive flow modification attacker with access at + multiple points within the core of the Internet is able to overcome + these topological limitations and perform attacks over a much broader + scope. Being positioned in the core of the network rather than the + edge can also enable an active pervasive attacker to reroute targeted + traffic, amplifying the ability to perform both eavesdropping and + traffic injection. Active pervasive attackers can also benefit from + passive pervasive collection to identify vulnerable hosts. + + While not directly related to pervasiveness, attackers that are in a + position to mount a active pervasive attack are also often in a + position to subvert authentication, a traditional protection against + such attacks. Authentication in the Internet is often achieved via + trusted third party authorities such as the Certificate Authorities + (CAs) that provide web sites with authentication credentials. An + attacker with sufficient resources may also be able to induce an + authority to grant credentials for an identity of the attacker's + choosing. If the parties to a communication will trust multiple + authorities to certify a specific identity, this attack may be + mounted by suborning any one of the authorities (the proverbial + "weakest link"). Subversion of authorities in this way can allow an + active attack to succeed in spite of an authentication check. + + Beyond these three classes (observation, inference, and active), + reports on the BULLRUN effort to defeat encryption and the PRISM + effort to obtain data from service providers suggest three more + classes of attack: + + o Static key exfiltration + + o Dynamic key exfiltration + + o Content exfiltration + + These attacks all rely on a collaborator providing the attacker with + some information, either keys or data. These attacks have not + traditionally been considered in scope for the Security + Considerations sections of IETF protocols, as they occur outside the + protocol. + + The term "key exfiltration" refers to the transfer of keying material + for an encrypted communication from the collaborator to the attacker. + By "static", we mean that the transfer of keys happens once, or + rarely, typically of a long-lived key. For example, this case would + + + +Barnes, et al. Expires November 29, 2015 [Page 15] + +Internet-Draft Confidentiality Threat Model May 2015 + + + cover a web site operator that provides the private key corresponding + to its HTTPS certificate to an intelligence agency. + + "Dynamic" key exfiltration, by contrast, refers to attacks in which + the collaborator delivers keying material to the attacker frequently, + e.g., on a per-session basis. This does not necessarily imply + frequent communications with the attacker; the transfer of keying + material may be virtual. For example, if an endpoint were modified + in such a way that the attacker could predict the state of its + psuedorandom number generator, then the attacker would be able to + derive per-session keys even without per-session communications. + + Finally, content exfiltration is the attack in which the collaborator + simply provides the attacker with the desired data or metadata. + Unlike the key exfiltration cases, this attack does not require the + attacker to capture the desired data as it flows through the network. + The exfiltration is of data at rest, rather than data in transit. + This increases the scope of data that the attacker can obtain, since + the attacker can access historical data - the attacker does not have + to be listening at the time the communication happens. + + Exfiltration attacks can be accomplished via attacks against one of + the parties to a communication, i.e., by the attacker stealing the + keys or content rather than the party providing them willingly. In + these cases, the party may not be aware that they are collaborating, + at least at a human level. Rather, the subverted technical assets + are "collaborating" with the attacker (by providing keys/content) + without their owner's knowledge or consent. + + Any party that has access to encryption keys or unencrypted data can + be a collaborator. While collaborators are typically the endpoints + of a communication (with encryption securing the links), + intermediaries in an unencrypted communication can also facilitate + content exfiltration attacks as collaborators by providing the + attacker access to those communications. For example, documents + describing the NSA PRISM program claim that NSA is able to access + user data directly from servers, where it is stored unencrypted. In + these cases, the operator of the server would be a collaborator, if + an unwitting one. By contrast, in the NSA MUSCULAR program, a set of + collaborators enabled attackers to access the cables connecting data + centers used by service providers such as Google and Yahoo. Because + communications among these data centers were not encrypted, the + collaboration by an intermediate entity allowed NSA to collect + unencrypted user data. + + + + + + + +Barnes, et al. Expires November 29, 2015 [Page 16] + +Internet-Draft Confidentiality Threat Model May 2015 + + +5.2. Attacker Costs + + +--------------------------+-----------------------------------+ + | Attack Class | Cost / Risk to Attacker | + +--------------------------+-----------------------------------+ + | Passive observation | Passive data access | + | | | + | Passive inference | Passive data access + processing | + | | | + | Active | Active data access + processing | + | | | + | Static key exfiltration | One-time interaction | + | | | + | Dynamic key exfiltration | Ongoing interaction / code change | + | | | + | Content exfiltration | Ongoing, bulk interaction | + +--------------------------+-----------------------------------+ + + Each of the attack types discussed in the previous section entails + certain costs and risks. These costs differ by attack, and can be + helpful in guiding response to pervasive attack. + + Depending on the attack, the attacker may be exposed to several types + of risk, ranging from simply losing access to arrest or prosecution. + In order for any of these negative consequences to occur, however, + the attacker must first be discovered and identified. So the primary + risk we focus on here is the risk of discovery and attribution. + + A passive pervasive attack is the simplest to mount in some ways. + The base requirement is that the attacker obtain physical access to a + communications medium and extract communications from it. For + example, the attacker might tap a fiber-optic cable, acquire a mirror + port on a switch, or listen to a wireless signal. The need for these + taps to have physical access or proximity to a link exposes the + attacker to the risk that the taps will be discovered. For example, + a fiber tap or mirror port might be discovered by network operators + noticing increased attenuation in the fiber or a change in switch + configuration. Of course, passive pervasive attacks may be + accomplished with the cooperation of the network operator, in which + case there is a risk that the attacker's interactions with the + network operator will be exposed. + + In many ways, the costs and risks for an active pervasive attack are + similar to those for a passive pervasive attack, with a few + additions. An active attacker requires more robust network access + than a passive attacker, since for example they will often need to + transmit data as well as receive it. In the wireless example above, + the attacker would need to act as an transmitter as well as receiver, + + + +Barnes, et al. Expires November 29, 2015 [Page 17] + +Internet-Draft Confidentiality Threat Model May 2015 + + + greatly increasing the probability the attacker will be discovered + (e.g., using direction-finding technology). Active attacks are also + much more observable at higher layers of the network. For example, + an active attacker that attempts to use a mis-issued certificate + could be detected via Certificate Transparency [RFC6962]. + + In terms of raw implementation complexity, passive pervasive attacks + require only enough processing to extract information from the + network and store it. Active pervasive attacks, by contrast, often + depend on winning race conditions to inject packets into active + connections. So active pervasive attacks in the core of the network + require processing hardware to that can operate at line speed + (roughly 100Gbps to 1Tbps in the core) to identify opportunities for + attack and insert attack traffic in a high-volume traffic. Key + exfiltration attacks rely on passive pervasive attack for access to + encrypted data, with the collaborator providing keys to decrypt the + data. So the attacker undertakes the cost and risk of a passive + pervasive attack, as well as additional risk of discovery via the + interactions that the attacker has with the collaborator. + + Some active attacks are more expensive than others. For example, + active man-in-the-middle (MITM) attacks require access to one or more + points on a communication's network path that allow visibility of the + entire session and the ability to modify or drop legitimate packets + in favor of the attacker's packets. A similar but weaker form of + attack, called an active man-on-the-side (MOTS), requires access to + only part of the session. In an active MOTS attack, the attacker + need only be able to inject or modify traffic on the network element + the attacker has access to. While this may not allow for full + control of a communication session (as in an MITM attack), the + attacker can perform a number of powerful attacks, including but not + limited to: injecting packets that could terminate the session (e.g., + TCP RST packets), sending a fake DNS reply to redirect ensuing TCP + connections to an address of the attacker's choice (i.e., winning a + "DNS response race"), and mounting an HTTP Redirect attack by + observing a TCP/HTTP connection to a target address and injecting a + TCP data packet containing an HTTP redirect. For example, the system + dubbed by researchers as China's "Great Cannon" [great-cannon] can + operate in ful MITM mode to accomplish very complex attacks that can + modify content in transit while the well-known Great Firewall of + China is a MOTS system that focuses on blocking access to certain + kinds of traffic and destinations via TCP RST packet injection. + + In this sense, static exfiltration has a lower risk profile than + dynamic. In the static case, the attacker need only interact with + the collaborator a small number of times, possibly only once, say to + exchange a private key. In the dynamic case, the attacker must have + continuing interactions with the collaborator. As noted above these + + + +Barnes, et al. Expires November 29, 2015 [Page 18] + +Internet-Draft Confidentiality Threat Model May 2015 + + + interactions may be real, such as in-person meetings, or virtual, + such as software modifications that render keys available to the + attacker. Both of these types of interactions introduce a risk that + they will be discovered, e.g., by employees of the collaborator + organization noticing suspicious meetings or suspicious code changes. + + Content exfiltration has a similar risk profile to dynamic key + exfiltration. In a content exfiltration attack, the attacker saves + the cost and risk of conducting a passive pervasive attack. The risk + of discovery through interactions with the collaborator, however, is + still present, and may be higher. The content of a communication is + obviously larger than the key used to encrypt it, often by several + orders of magnitude. So in the content exfiltration case, the + interactions between the collaborator and the attacker need to be + much higher-bandwidth than in the key exfiltration cases, with a + corresponding increase in the risk that this high-bandwidth channel + will be discovered. + + It should also be noted that in these latter three exfiltration + cases, the collaborator also undertakes a risk that his collaboration + with the attacker will be discovered. Thus the attacker may have to + incur additional cost in order to convince the collaborator to + participate in the attack. Likewise, the scope of these attacks is + limited to case where the attacker can convince a collaborator to + participate. If the attacker is a national government, for example, + it may be able to compel participation within its borders, but have a + much more difficult time recruiting foreign collaborators. + + As noted above, the collaborator in an exfiltration attack can be + unwitting; the attacker can steal keys or data to enable the attack. + In some ways, the risks of this approach are similar to the case of + an active collaborator. In the static case, the attacker needs to + steal information from the collaborator once; in the dynamic case, + the attacker needs to continued presence inside the collaborators + systems. The main difference is that the risk in this case is of + automated discovery (e.g., by intrusion detection systems) rather + than discovery by humans. + +6. Security Considerations + + This document describes a threat model for pervasive surveillance + attacks. Mitigations are to be given in a future document. + +7. IANA Considerations + + This document has no actions for IANA. + + + + + +Barnes, et al. Expires November 29, 2015 [Page 19] + +Internet-Draft Confidentiality Threat Model May 2015 + + +8. IAB Members at the Time of Approval + + Jari Arkko (IETF Chair) + Mary Barnes + Marc Blanchet + Ralph Droms + Ted Hardie + Joe Hildebrand + Russ Housley + Erik Nordmark + Robert Sparks + Andrew Sullivan + Dave Thaler + Brian Trammell + Suzanne Woolf + +9. Acknowledgements + + Thanks to Dave Thaler for the list of attacks and taxonomy; to + Security Area Directors Stephen Farrell, Sean Turner, and Kathleen + Moriarty for starting and managing the IETF's discussion on pervasive + attack; and to Stephan Neuhaus, Mark Townsley, Chris Inacio, + Evangelos Halepilidis, Bjoern Hoehrmann, Aziz Mohaisen, Russ Housley, + Joe Hall, Andrew Sullivan, the IEEE 802 Privacy Executive Committee + SG, and the IAB Privacy and Security Program for their input. + +10. References + +10.1. Normative References + + [RFC6973] Cooper, A., Tschofenig, H., Aboba, B., Peterson, J., + Morris, J., Hansen, M., and R. Smith, "Privacy + Considerations for Internet Protocols", RFC 6973, July + 2013. + +10.2. Informative References + + [pass1] The Guardian, "How the NSA is still harvesting your online + data", 2013, + . + + [pass2] The Guardian, "NSA's Prism surveillance program: how it + works and what it can do", 2013, + . + + + + + +Barnes, et al. Expires November 29, 2015 [Page 20] + +Internet-Draft Confidentiality Threat Model May 2015 + + + [pass3] The Guardian, "XKeyscore: NSA tool collects 'nearly + everything a user does on the internet'", 2013, + . + + [pass4] The Guardian, "How does GCHQ's internet surveillance + work?", n.d., . + + [dec1] The New York Times, "N.S.A. Able to Foil Basic Safeguards + of Privacy on Web", 2013, + . + + [dec2] The Guardian, "Project Bullrun - classification guide to + the NSA's decryption program", 2013, + . + + [dec3] The Guardian, "Revealed: how US and UK spy agencies defeat + internet privacy and security", 2013, + . + + [TOR1] Schneier, B., "How the NSA Attacks Tor/Firefox Users With + QUANTUM and FOXACID", 2013, + . + + [TOR2] The Guardian, "'Tor Stinks' presentation - read the full + document", 2013, + . + + [dir1] The Guardian, "NSA collecting phone records of millions of + Verizon customers daily", 2013, + . + + [dir2] The Guardian, "NSA Prism program taps in to user data of + Apple, Google and others", 2013, + . + + [dir3] The Guardian, "Sigint - how the NSA collaborates with + technology companies", 2013, + . + + + +Barnes, et al. Expires November 29, 2015 [Page 21] + +Internet-Draft Confidentiality Threat Model May 2015 + + + [spiegel1] + C Stocker, ., "NSA's Secret Toolbox: Unit Offers Spy + Gadgets for Every Need", December 2013, + . + + [spiegel3] + H Schmundt, ., "The Digital Arms Race: NSA Preps America + for Future Battle", January 2014, + . + + [great-cannon] + Paxson, V., "China's Great Cannon", 2015, + . + + [RFC1035] Mockapetris, P., "Domain names - implementation and + specification", STD 13, RFC 1035, November 1987. + + [RFC1918] Rekhter, Y., Moskowitz, R., Karrenberg, D., Groot, G., and + E. Lear, "Address Allocation for Private Internets", BCP + 5, RFC 1918, February 1996. + + [RFC1939] Myers, J. and M. Rose, "Post Office Protocol - Version 3", + STD 53, RFC 1939, May 1996. + + [RFC3261] Rosenberg, J., Schulzrinne, H., Camarillo, G., Johnston, + A., Peterson, J., Sparks, R., Handley, M., and E. + Schooler, "SIP: Session Initiation Protocol", RFC 3261, + June 2002. + + [RFC3365] Schiller, J., "Strong Security Requirements for Internet + Engineering Task Force Standard Protocols", BCP 61, RFC + 3365, August 2002. + + [RFC3501] Crispin, M., "INTERNET MESSAGE ACCESS PROTOCOL - VERSION + 4rev1", RFC 3501, March 2003. + + [RFC4033] Arends, R., Austein, R., Larson, M., Massey, D., and S. + Rose, "DNS Security Introduction and Requirements", RFC + 4033, March 2005. + + [RFC4303] Kent, S., "IP Encapsulating Security Payload (ESP)", RFC + 4303, December 2005. + + + + + +Barnes, et al. Expires November 29, 2015 [Page 22] + +Internet-Draft Confidentiality Threat Model May 2015 + + + [RFC4949] Shirey, R., "Internet Security Glossary, Version 2", RFC + 4949, August 2007. + + [RFC5246] Dierks, T. and E. Rescorla, "The Transport Layer Security + (TLS) Protocol Version 1.2", RFC 5246, August 2008. + + [RFC5321] Klensin, J., "Simple Mail Transfer Protocol", RFC 5321, + October 2008. + + [RFC6962] Laurie, B., Langley, A., and E. Kasper, "Certificate + Transparency", RFC 6962, June 2013. + + [RFC7011] Claise, B., Trammell, B., and P. Aitken, "Specification of + the IP Flow Information Export (IPFIX) Protocol for the + Exchange of Flow Information", STD 77, RFC 7011, September + 2013. + + [RFC7258] Farrell, S. and H. Tschofenig, "Pervasive Monitoring Is an + Attack", BCP 188, RFC 7258, May 2014. + + [I-D.ietf-dprive-problem-statement] + Bortzmeyer, S., "DNS privacy considerations", draft-ietf- + dprive-problem-statement-05 (work in progress), May 2015. + +Authors' Addresses + + Richard Barnes + + Email: rlb@ipv.sx + + + Bruce Schneier + + Email: schneier@schneier.com + + + Cullen Jennings + + Email: fluffy@cisco.com + + + Ted Hardie + + Email: ted.ietf@gmail.com + + + + + + + +Barnes, et al. Expires November 29, 2015 [Page 23] + +Internet-Draft Confidentiality Threat Model May 2015 + + + Brian Trammell + + Email: ietf@trammell.ch + + + Christian Huitema + + Email: huitema@huitema.net + + + Daniel Borkmann + + Email: dborkman@iogearbox.net + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Barnes, et al. Expires November 29, 2015 [Page 24] diff --git a/draft-iab-privsec-confidentiality-threat-07.xml b/draft-iab-privsec-confidentiality-threat-07.xml new file mode 100644 index 0000000..f461b23 --- /dev/null +++ b/draft-iab-privsec-confidentiality-threat-07.xml @@ -0,0 +1,1067 @@ + + + + + + + + + + + + + + + + + + + + +]> + + + + + + + Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement + + + +
+ rlb@ipv.sx +
+ + + +
+ schneier@schneier.com +
+ + + +
+ fluffy@cisco.com +
+ + + +
+ ted.ietf@gmail.com +
+ + + +
+ ietf@trammell.ch +
+ + + +
+ huitema@huitema.net +
+ + + +
+ dborkman@iogearbox.net +
+ + + + + + + + + + + +Since the initial revelations of pervasive surveillance in 2013, + several classes of attacks on Internet communications have been + discovered. In this document we develop a threat model that + describes these attacks on Internet confidentiality. We assume an + attacker that is interested in undetected, indiscriminate + eavesdropping. The threat model is based on published, verified + attacks. + + + + + + + + + + + +
+ +Starting in June 2013, documents released to the press by Edward +Snowden have revealed several operations undertaken by intelligence +agencies to exploit Internet communications for intelligence purposes. +These attacks were largely based on protocol vulnerabilities that were +already known to exist. The attacks were nonetheless striking in +their pervasive nature, both in terms of the volume of Internet +traffic targeted, and in terms of the diversity of attack +techniques employed. + +To ensure that the Internet can be trusted by users, it is necessary +for the Internet technical community to address the vulnerabilities +exploited in these attacks . The goal of this document is +to describe more precisely the threats posed by these pervasive +attacks, and based on those threats, lay out the problems that need to +be solved in order to secure the Internet in the face of those +threats. + +The remainder of this document is structured as follows. In +, we describe an idealized passive pervasive attacker, one which +could completely undetectably compromise communications at Internet +scale. In , we provide a brief summary of some attacks +that have been disclosed, and use these to expand the assumed +capabilities of our idealized attacker. Note that we do not attempt +to describe all possible attacks, but focus on those which result in +undetected eavesdropping. describes a threat model based on +these attacks, focusing on classes of attack that have not been a +focus of Internet engineering to date. + +
+
+ +This document makes extensive use of standard security and privacy +terminology; see and . Terms used from + include Eavesdropper, Observer, Initiator, Intermediary, +Recipient, Attack (in a privacy context), Correlation, Fingerprint, +Traffic Analysis, and Identifiability (and related terms). In +addition, we use a few terms that are specific to the attacks +discussed in this document. Note especially that “passive” and “active” below +do not refer to the effort used to mount the attack; a “passive attack” +is any attack that accesses a flow but does not modify it, while an +“active attack” is any attack that modifies a flow. Some passive attacks +involve active interception and modifications of devices, rather than simple +access to the medium. The introduced terms are: + + + + An attack on Internet communications that makes +use of access at a large number of points in the network, or otherwise +provides the attacker with access to a large amount of Internet +traffic; see . + + An eavesdropping attack undertaken by a pervasive attacker, in which the +packets in a traffic stream between two endpoints are intercepted, but +in which the attacker does not modify the packets in the traffic +stream between two endpoints, modify the treatment of packets in the +traffic stream (e.g. delay, routing), or add or remove packets in the +traffic stream. Passive pervasive attacks are undetectable from the +endpoints. Equivalent to passive wiretapping as defined in ; +we use an alternate term here since the methods employed are wider +than those implied by the word “wiretapping”, including the active +compromise of intermediate systems. + + An attack undertaken by a pervasive attacker, which in addition to +the elements of a passive pervasive attack, also includes modification, +addition, or removal of +packets in a traffic stream, or modification of treatment of packets +in the traffic stream. Active pervasive attacks provide more +capabilities to the attacker at the risk of possible detection at the +endpoints. Equivalent to active wiretapping as defined in . + + Information collected directly from communications by an +eavesdropper or observer. For example, the knowledge that +<alice@example.com> sent a message to <bob@example.com> +via SMTP taken from the headers of an observed SMTP message would be +an observation. + + Information derived from analysis of information collected +directly from communications by an eavesdropper or observer. For +example, the knowledge that a given web page was accessed by a given +IP address, by comparing the size in octets of measured network flow +records to fingerprints derived from known sizes of linked resources +on the web servers involved, would be an inference. + + An entity that is a legitimate participant in a communication, and provides information about that communication to an attacker. Collaborators may either deliberately or unwittingly cooperate with the attacker, in the latter case because the attacker has subverted the collaborator through technical, social, or other means. + + The transmission of cryptographic keying material for an encrypted communication +from a collaborator, deliberately or unwittingly, to an attacker. + + The transmission of the content of a communication from a collaborator, deliberately or unwittingly, to an attacker + + +
+
+ +In considering the threat posed by pervasive surveillance, we begin by +defining an idealized passive pervasive attacker. While this attacker +is less capable than those which we now know to have compromised the +Internet from press reports, as elaborated in , it does +set a lower bound on the capabilities of an attacker interested in +indiscriminate passive surveillance while interested in remaining +undetectable. We note that, prior to the Snowden revelations in 2013, +the assumptions of attacker capability presented here would be +considered on the border of paranoia outside the network security +community. + +Our idealized attacker is an indiscriminate eavesdropper on an Internet-attached computer network that: + + + can observe every packet of all communications at any hop in any network path between an initiator and a recipient; + can observe data at rest in any intermediate system between the endpoints controlled by the initiator and recipient; and + can share information with other such attackers; but + takes no other action with respect to these communications (i.e., blocking, modification, injection, etc.). +The techniques available to our ideal attacker are direct observation +and inference. Direct observation involves taking information +directly from eavesdropped communications, such as URLs identifying +content or email addresses identifying individuals from application- +layer headers. Inference, on the other hand, involves analyzing +observed information to derive new information, such as searching for +application or behavioral fingerprints in observed traffic to derive +information about the observed individual. The use of encryption is +generally sufficient to provide confidentiality by preventing direct +observation of content, assuming of course, uncompromised encryption +implementations and cryptographic keying material. However, +encryption provides less complete protection against inference, +especially inferences based only on plaintext portions of +communications, such as IP and TCP headers for TLS-protected traffic +). + + +
+ +Protocols which do not encrypt their payload make the entire content +of the communication available to the idealized attacker along their +path. Following the advice in , most such protocols have a +secure variant which encrypts payload for confidentiality, and these +secure variants are seeing ever-wider deployment. A noteworthy +exception is DNS , as DNSSEC does not have +confidentiality as a requirement. + +This implies that, in the absence of +changes to the protocol as presently under development in the IETF’s +DNS Private Exchange (DPRIVE) +working group , all DNS queries and answers generated by the activities +of any protocol are available to the attacker. + +When store-and-forward protocols are used, (e.g. SMTP ) +intermediaries leave this data subject to observation by an attacker that +has compromised these intermediaries, +unless the data is encrypted end-to-end by the application layer +protocol, or the implementation uses an encrypted store for this data. + +
+
+ +Inference is information extracted from later analysis of an observed +or eavesdropped communication, and/or correlation of observed or +eavesdropped information with information available from other +sources. Indeed, most useful inference performed by the attacker falls +under the rubric of correlation. The simplest example of this is the +observation of DNS queries and answers from and to a source and +correlating those with IP addresses with which that source +communicates. This can give access to information otherwise not +available from encrypted application payloads (e.g., the Host: +HTTP/1.1 request header when HTTP is used with TLS). + +Protocols which encrypt their payload using an application- or +transport-layer encryption scheme (e.g. TLS) still expose all the +information in their network and transport layer headers to the +attacker, including source and destination addresses and ports. IPsec +ESP further encrypts the transport-layer headers, but still +leaves IP address information unencrypted; in tunnel mode, these +addresses correspond to the tunnel endpoints. Features of the +security protocols themselves, e.g. the TLS session identifier, +may leak information that can be used for correlation and +inference. While this information is much less semantically rich than +the application payload, it can still be useful for the inferring an +individual’s activities. + +Inference can also leverage information obtained from sources other +than direct traffic observation. Geolocation databases, for example, +have been developed that map IP addresses to a location, in order to +provide location-aware services such as targeted advertising. This +location information is often of sufficient resolution that it can be +used to draw further inferences toward identifying or profiling an +individual. + +Social media provide another source of more or less publicly +accessible information. This information can be extremely semantically +rich, including information about an individual’s location, +associations with other individuals and groups, and +activities. Further, this information is generally contributed and +curated voluntarily by the individuals themselves: it represents +information which the individuals are not necessarily interested in +protecting for privacy reasons. However, correlation of this social +networking data with information available from direct observation of +network traffic allows the creation of a much richer picture of an +individual’s activities than either alone. + +We note with some alarm that there is little that can be done at +protocol design time to limit such correlation by the attacker, and +that the existence of such data sources in many cases greatly +complicates the problem of protecting privacy by hardening protocols +alone. + +
+
+ +To illustrate how capable the idealized attacker is even given its +limitations, we explore the non-anonymity of encrypted IP traffic in +this section. Here we examine in detail some inference techniques for +associating a set of addresses with an individual, in order to +illustrate the difficulty of defending communications against our +idealized attacker. Here, the basic problem is that information +radiated even from protocols which have no obvious connection with +personal data can be correlated with other information which can paint +a very rich behavioral picture, that only takes one unprotected link +in the chain to associate with an identity. + +
+ +Internet traffic can be monitored by tapping Internet links, or by +installing monitoring tools in Internet routers. Of course, a single +link or a single router only provides access to a fraction of the +global Internet traffic. However, monitoring a number of high capacity +links or a set of routers placed at strategic locations provides +access to a good sampling of Internet traffic. + +Tools like IPFIX allow administrators to acquire +statistics about sequences of packets with some common properties that +pass through a network device. The most common set of properties used +in flow measurement is the “five-tuple” of source and destination +addresses, protocol type, and source and destination ports. These +statistics are commonly used for network engineering, but could +certainly be used for other purposes. + +Let’s assume for a moment that IP addresses can be correlated to +specific services or specific users. Analysis of the sequences of +packets will quickly reveal which users use what services, and also +which users engage in peer-to-peer connections with other +users. Analysis of traffic variations over time can be used to detect +increased activity by particular users, or in the case of peer-to-peer +connections increased activity within groups of users. + +
+
+ +The correlation of IP addresses with specific users can be done in +various ways. For example, tools like reverse DNS lookup can be used +to retrieve the DNS names of servers. Since the addresses of servers +tend to be quite stable and since servers are relatively less numerous +than users, an attacker could easily maintain its own copy of the DNS +for well-known or popular servers, to accelerate such lookups. + +On the other hand, the reverse lookup of IP addresses of users is +generally less informative. For example, a lookup of the address +currently used by one author’s home network returns a name of the form +“c-192-000-002-033.hsd1.wa.comcast.net”. This particular type of +reverse DNS lookup generally reveals only coarse-grained location or +provider information, equivalent to that available from geolocation +databases. + +In many jurisdictions, Internet Service Providers (ISPs) are required +to provide identification on a case by case basis of the “owner” of a +specific IP address for law enforcement purposes. This is a reasonably +expedient process for targeted investigations, but pervasive +surveillance requires something more efficient. This provides an +incentive for the attacker to secure the cooperation of the ISP in +order to automate this correlation. + +
+
+ +Even if the ISP does not cooperate, user identity can often be +obtained via inference. POP3 and IMAP are used +to retrieve mail from mail servers, while a variant of SMTP is used to +submit messages through mail servers. IMAP connections originate from +the client, and typically start with an authentication exchange in +which the client proves its identity by answering a password +challenge. The same holds for the SIP protocol and many +instant messaging services operating over the Internet using +proprietary protocols. + +The username is directly observable if any of these protocols operate +in cleartext; the username can then be directly associated with the +source address. + +
+
+ +SMTP requires that each successive SMTP relay adds a +“Received” header to the mail headers. The purpose of these headers is +to enable audit of mail transmission, and perhaps to distinguish +between regular mail and spam. Here is an extract from the headers of +a message recently received from the “perpass” mailing list: + + + Received: from 192-000-002-044.zone13.example.org (HELO ?192.168.1.100?) + (xxx.xxx.xxx.xxx) by lvps192-000-002-219.example.net with ESMTPSA + (DHE-RSA-AES256-SHA encrypted, authenticated); 27 Oct 2013 21:47:14 +0100 + Message-ID: <526D7BD2.7070908@example.org> + Date: Sun, 27 Oct 2013 20:47:14 +0000 + From: Some One <some.one@example.org> + + +This is the first “Received” header attached to the message by the +first SMTP relay; for privacy reasons, the field values have been +anonymized. We learn here that the message was submitted by “Some One” +on October 27, from a host behind a NAT (192.168.1.100) +that used the IP address 192.0.2.44. The information remained in the +message, and is accessible by all recipients of the “perpass” mailing +list, or indeed by any attacker that sees at least one copy of the +message. + +An attacker that can observe sufficient email traffic can regularly +update the mapping between public IP addresses and individual email +identities. Even if the SMTP traffic was encrypted on submission and +relaying, the attacker can still receive a copy of public mailing +lists like “perpass”. + +
+
+ +Many web sites only encrypt a small fraction of their transactions. A +popular pattern is to use HTTPS for the login information, and then +use a “cookie” to associate following clear-text transactions with the +user’s identity. Cookies are also used by various advertisement +services to quickly identify the users and serve them with +“personalized” advertisements. Such cookies are particularly useful if +the advertisement services want to keep tracking the user across +multiple sessions that may use different IP addresses. + +As cookies are sent in clear text, an attacker can build a database +that associates cookies to IP addresses for non-HTTPS traffic. If the +IP address is already identified, the cookie can be linked to the user +identify. After that, if the same cookie appears on a new IP address, +the new IP address can be immediately associated with the +pre-determined identity. + +
+
+ +An attacker can track traffic from an IP address not yet associated +with an individual to various public services (e.g. websites, mail +servers, game servers), and exploit patterns in the observed traffic +to correlate this address with other addresses that show similar +patterns. For example, any two addresses that show connections to the +same IMAP or webmail services, the same set of favorite websites, and +game servers at similar times of day may be associated with the same +individual. Correlated addresses can then be tied to an individual +through one of the techniques above, walking the “network graph” to +expand the set of attributable traffic. + +
+
+ +Moving back down the stack, technologies like Ethernet or Wi-Fi use MAC Addresses to identify link-level destinations. MAC Addresses assigned according to IEEE-802 standards are globally-unique identifiers for the device. If the link is publicly accessible, an attacker can eavesdrop and perform tracking. For example, the attacker can track the wireless traffic at publicly accessible Wi-Fi networks. Simple devices can monitor the traffic, and reveal which MAC Addresses are present. +Also, devices do not need to be connected to a network to expose link-layer identifiers. Active service discovery always discloses the MAC address of the user, and sometimes the SSIDs of previously visited networks. For instance, certain techniques such as the use of “hidden SSIDs” require the mobile device to broadcast the network identifier together with the device identifier. This combination can further expose the user to inference attacks, as more information can be derived from the combination of MAC address, SSID being probed, time and current location. For example, a user actively probing for a semi-unique SSID on a flight out of a certain city can imply that the user is no longer at the physical location of the corresponding AP. +Given that large-scale databases of the MAC addresses of wireless access points for geolocation purposes have been known to exist for some time, the attacker could easily build a database linking link-layer identifiers, time and device or user identities, and use it to track the movement of devices and of their owners. +On the other hand, if the network does not use some form of Wi-Fi encryption, or if the attacker can access the decrypted traffic, the analysis will also provide the correlation between link-layer identifiers such as MAC Addresses and IP addresses. Additional monitoring using techniques exposed in the previous sections will reveal the correlation between MAC addresses, IP addresses, and user identity. For instance, similarly to the use of web cookies, MAC addresses provide identity information that can be used to associate a user to different IP addresses. + +
+
+
+
+ +The situation in reality is more bleak than that suggested by an analysis of +our idealized attacker. Through revelations of sensitive documents in several +media outlets, the Internet community has been made aware of several +intelligence activities conducted by US and UK national intelligence agencies, +particularly the US National Security Agency (NSA) and the UK Government +Communications Headquarters (GCHQ). These documents have revealed methods that +these agencies use to attack Internet applications and obtain sensitive user +information. There is little reason to suppose that only the US or UK +governments are involved in these sorts of activities; the examples are just +ones that were disclosed. We note that these reports are primarily useful as +an illustration of the types of capabilities fielded by pervasive attackers as +of the date of the Snowden leaks in 2013. + +First, they confirm the deployment of large-scale passive +collection of Internet traffic, which confirms the existence of +pervasive passive attackers with at least the capabilities of our +idealized attacker. For example : + + + NSA’s XKEYSCORE system accesses data from multiple access points and +searches for “selectors” such as email addresses, at the scale of tens +of terabytes of data per day. + GCHQ’s Tempora system appears to have access to around 1,500 major cables +passing through the UK. + NSA’s MUSCULAR program has tapped cables between data centers +belonging to major service providers. + Several programs appear to perform wide-scale collection +of cookies in web traffic and location data from location-aware +portable devices such as smartphones. + + +However, the capabilities described by these reports go beyond those of our +idealized attacker. They include the compromise of cryptographic protocols, +including decryption of TLS-protected Internet sessions . +For example, the NSA BULLRUN project worked to undermine encryption through +multiple approaches, including covert modifications to cryptographic +software on end systems. + +Reported capabilities include the direct compromise of intermediate systems +and arrangements with service providers for bulk data and metadata +access , bypassing the need to capture +traffic on the wire. For example, the NSA PRISM program provides the +agency with access to many types of user data (e.g., email, chat, VoIP). + +The reported capabilities also include elements of active pervasive attack, +including: + + + Insertion of devices as a man-in-the-middle of Internet +transactions . For example, NSA’s QUANTUM system +appears to use several different techniques to hijack HTTP +connections, ranging from DNS response injection to HTTP 302 +redirects. + Use of implants on end systems to undermine security and anonymity +features . For example, QUANTUM is used to +direct users to a FOXACID server, which in turn delivers an implant +to compromise browsers of Tor users. + Use of implants on network elements from many major equipment providers, +including Cisco, Juniper, Huawei, Dell, and HP, as provided by the NSA’s +Advanced Network Technology group. + Use of botnet-scale collections of compromised hosts . + + +The scale of the compromise extends beyond the network to include subversion of the technical standards process itself. For example, there is suspicion that NSA modifications to the DUAL_EC_DRBG random number generator were made to ensure that keys generated using that generator could be predicted by NSA. This RNG was made part of NIST’s SP 800-90A, for which NIST acknowledges NSA’s assistance. There have also been reports that the NSA paid RSA Security for a related contract with the result that the curve became the default in the RSA BSAFE product line. + +We use the term “pervasive attack” to collectively +describe these operations. The term “pervasive” is used because the +attacks are designed to indiscriminately gather as much data as +possible and to apply selective analysis on targets after the fact. +This means that all, or nearly all, Internet communications are +targets for these attacks. To achieve this scale, the attacks are +physically pervasive; they affect a large number of Internet +communications. They are pervasive in content, consuming and +exploiting any information revealed by the protocol. And they are +pervasive in technology, exploiting many different vulnerabilities in +many different protocols. + +Again, it’s important to note that, although the attacks mentioned above were +executed by NSA and GCHQ, there are many other organizations that can mount +pervasive surveillance attacks. Because of the resources required to achieve +pervasive scale, these attacks are most commonly undertaken by nation-state +actors. For example, the Chinese Internet filtering system known as the +“Great Firewall of China” uses several techniques that are similar to the +QUANTUM program, and which have a high degree of pervasiveness with regard to +the Internet in China. Therefore, legal restrictions in any one jurisdiction on pervasive monitoring activities cannot eliminate the risk of pervasive attack to the Internet as a whole. + +
+
+ +Given these disclosures, we must consider a broader threat model. + +Pervasive surveillance aims to collect information across a large +number of Internet communications, analyzing the collected +communications to identify information of interest within individual +communications, or inferring information from correlated +communications. This analysis sometimes benefits from decryption of +encrypted communications and deanonymization of anonymized +communications. As a result, these attackers desire both access to +the bulk of Internet traffic and to the keying material required to +decrypt any traffic that has been encrypted. Even if keys are not +available, note that the presence of a communication and the fact that +it is encrypted may both be inputs to an analysis, even if the +attacker cannot decrypt the communication. + +The attacks listed above highlight new avenues both for access to +traffic and for access to relevant encryption keys. They further +indicate that the scale of surveillance is sufficient to provide a +general capability to cross-correlate communications, a threat not +previously thought to be relevant at the scale of the Internet. + +
+ + + Attack Class + Capability + Passive observation + Directly capture data in transit + Passive inference + Infer from reduced/encrypted data + Active + Manipulate / inject data in transit + Static key exfiltration + Obtain key material once / rarely + Dynamic key exfiltration + Obtain per-session key material + Content exfiltration + Access data at rest + + +Security analyses of Internet protocols commonly consider two classes +of attacker: Passive pervasive attackers, who can simply listen in on +communications as they transit the network, and active pervasive +attackers, who can modify or delete packets in addition to simply +collecting them. + +In the context of pervasive passive surveillance, these attacks take +on an even greater significance. In the past, these attackers were +often assumed to operate near the edge of the network, where attacks +can be simpler. For example, in some LANs, it is simple for any node +to engage in passive listening to other nodes’ traffic or inject +packets to accomplish active pervasive attacks. However, as we now +know, both passive and active pervasive attacks are undertaken by +pervasive attackers closer to the core of the network, greatly +expanding the scope and capability of the attacker. + +Eavesdropping and observation at a larger scale make passive inference +attacks easier to carry out: a passive pervasive attacker with access to a +large portion of the Internet can analyze collected traffic to create +a much more detailed view of individual behavior than an attacker that +collects at a single point. Even the usual claim that encryption +defeats passive pervasive attackers is weakened, since a pervasive flow +access attacker can infer relationships from correlations over large +numbers of sessions, e.g., pairing encrypted sessions with unencrypted +sessions from the same host, or performing traffic fingerprinting +between known and unknown encrypted sessions. Reports on the NSA +XKEYSCORE system would indicate it is an example of such an attacker. + +An active pervasive attacker likewise has capabilities +beyond those of a localized active attacker. Flow +modification attacks are often limited by network topology, for +example by a requirement that the attacker be able to see a targeted +session as well as inject packets into it. A pervasive flow +modification attacker with access at multiple points within the core +of the Internet is able to overcome these topological limitations and +perform attacks over a much broader scope. Being positioned in the +core of the network rather than the edge can also enable an active +pervasive attacker to reroute targeted traffic, amplifying the +ability to perform both eavesdropping and traffic injection. +Active pervasive attackers can also benefit from passive pervasive +collection to identify vulnerable hosts. + +While not directly related to pervasiveness, attackers that are in a +position to mount a active pervasive attack are also often +in a position to subvert authentication, a traditional protection +against such attacks. Authentication in the Internet is often +achieved via trusted third party authorities such as the Certificate +Authorities (CAs) that provide web sites with authentication +credentials. An attacker with sufficient resources may also be able to +induce an authority to grant credentials for an identity of the +attacker’s choosing. If the parties to a communication will trust +multiple authorities to certify a specific identity, this attack may +be mounted by suborning any one of the authorities (the proverbial +“weakest link”). Subversion of authorities in this way can allow an +active attack to succeed in spite of an authentication +check. + +Beyond these three classes (observation, inference, and active), +reports on the BULLRUN effort to defeat encryption and the PRISM +effort to obtain data from service providers suggest three more +classes of attack: + + + Static key exfiltration + Dynamic key exfiltration + Content exfiltration + + +These attacks all rely on a collaborator providing the attacker with +some information, either keys or data. These attacks have not +traditionally been considered in scope for the Security Considerations +sections of IETF protocols, as they occur outside the protocol. + +The term “key exfiltration” refers to the transfer of keying material +for an encrypted communication from the collaborator to the attacker. +By “static”, we mean that the transfer of keys happens once, or +rarely, typically of a long-lived key. For example, this case would +cover a web site operator that provides the private key corresponding +to its HTTPS certificate to an intelligence agency. + +“Dynamic” key exfiltration, by contrast, refers to attacks in which +the collaborator delivers keying material to the attacker frequently, +e.g., on a per-session basis. This does not necessarily imply +frequent communications with the attacker; the transfer of keying +material may be virtual. For example, if an endpoint were modified in +such a way that the attacker could predict the state of its +psuedorandom number generator, then the attacker would be able to +derive per-session keys even without per-session communications. + +Finally, content exfiltration is the attack in which the collaborator +simply provides the attacker with the desired data or metadata. Unlike +the key exfiltration cases, this attack does not require the attacker +to capture the desired data as it flows through the network. The exfiltration +is of data at rest, rather than data in transit. This increases the scope of data +that the attacker can obtain, since the attacker can access historical +data – the attacker does not have to be listening +at the time the communication happens. + +Exfiltration attacks can be accomplished via attacks against one of +the parties to a communication, i.e., by the attacker stealing the +keys or content rather than the party providing them willingly. In +these cases, the party may not be aware that they are collaborating, +at least at a human level. Rather, the subverted technical assets are +“collaborating” with the attacker (by providing keys/content) without +their owner’s knowledge or consent. + +Any party that has access to encryption keys or unencrypted data can +be a collaborator. While collaborators are typically the endpoints of +a communication (with encryption securing the links), intermediaries +in an unencrypted communication can also facilitate content +exfiltration attacks as collaborators by providing the attacker access +to those communications. For example, documents describing the NSA +PRISM program claim that NSA is able to access user data directly from +servers, where it is stored unencrypted. In these cases, the operator +of the server would be a collaborator, if an unwitting one. By +contrast, in the NSA MUSCULAR program, a set of collaborators enabled +attackers to access the cables connecting data centers used by service +providers such as Google and Yahoo. Because communications among +these data centers were not encrypted, the collaboration by an +intermediate entity allowed NSA to collect unencrypted user data. + +
+
+ + + Attack Class + Cost / Risk to Attacker + Passive observation + Passive data access + Passive inference + Passive data access + processing + Active + Active data access + processing + Static key exfiltration + One-time interaction + Dynamic key exfiltration + Ongoing interaction / code change + Content exfiltration + Ongoing, bulk interaction + + +Each of the attack types discussed in the previous section entails +certain costs and risks. These costs differ by attack, and can be +helpful in guiding response to pervasive attack. + +Depending on the attack, the attacker may be exposed to several types +of risk, ranging from simply losing access to arrest or prosecution. +In order for any of these negative consequences to occur, however, the +attacker must first be discovered and identified. So the primary risk +we focus on here is the risk of discovery and attribution. + +A passive pervasive attack is the simplest to mount in some ways. The base +requirement is that the attacker obtain physical access to a +communications medium and extract communications from it. For +example, the attacker might tap a fiber-optic cable, acquire a mirror +port on a switch, or listen to a wireless signal. The need for these +taps to have physical access or proximity to a link exposes the +attacker to the risk that the taps will be discovered. For example, a +fiber tap or mirror port might be discovered by network operators +noticing increased attenuation in the fiber or a change in switch +configuration. Of course, passive pervasive attacks may be accomplished +with the cooperation of the network operator, in which case there is a +risk that the attacker’s interactions with the network operator will +be exposed. + +In many ways, the costs and risks for an active pervasive attack are +similar to those for a passive pervasive attack, with a few additions. An +active attacker requires more robust network access than a +passive attacker, since for example they will often need to +transmit data as well as receive it. In the wireless example above, +the attacker would need to act as an transmitter as well as receiver, +greatly increasing the probability the attacker will be discovered +(e.g., using direction-finding technology). Active attacks +are also much more observable at higher layers of the network. For +example, an active attacker that attempts to use a +mis-issued certificate could be detected via Certificate Transparency +. + +In terms of raw implementation complexity, passive pervasive attacks require +only enough processing to extract information from the network and +store it. Active pervasive attacks, by contrast, often depend on +winning race conditions to inject packets into active connections. So +active pervasive attacks in the core of the network require +processing hardware to that can operate at line speed (roughly 100Gbps +to 1Tbps in the core) to identify opportunities for attack and insert +attack traffic in a high-volume traffic. Key exfiltration attacks +rely on passive pervasive attack for access to encrypted data, with the +collaborator providing keys to decrypt the data. So the attacker +undertakes the cost and risk of a passive pervasive attack, as well as +additional risk of discovery via the interactions that the attacker +has with the collaborator. + +Some active attacks are more expensive than others. For example, active +man-in-the-middle (MITM) attacks require access to one or more points on a +communication’s network path that allow visibility of the entire session and +the ability to modify or drop legitimate packets in favor of the attacker’s +packets. A similar but weaker form of attack, called an active +man-on-the-side (MOTS), requires access to only part of the session. In an +active MOTS attack, the attacker need only be able to inject or modify traffic +on the network element the attacker has access to. While this may not allow +for full control of a communication session (as in an MITM attack), the +attacker can perform a number of powerful attacks, including but not limited +to: injecting packets that could terminate the session (e.g., TCP RST +packets), sending a fake DNS reply to redirect ensuing TCP connections to an +address of the attacker’s choice (i.e., winning a “DNS response race”), and +mounting an HTTP Redirect attack by observing a TCP/HTTP connection to a +target address and injecting a TCP data packet containing an HTTP redirect. +For example, the system dubbed by researchers as China’s “Great Cannon” + can operate in ful MITM mode to accomplish very complex +attacks that can modify content in transit while the well-known Great Firewall +of China is a MOTS system that focuses on blocking access to certain kinds of +traffic and destinations via TCP RST packet injection. + +In this sense, static exfiltration has a lower risk profile than +dynamic. In the static case, the attacker need only interact with the +collaborator a small number of times, possibly only once, say to +exchange a private key. In the dynamic case, the attacker must have +continuing interactions with the collaborator. As noted above these +interactions may be real, such as in-person meetings, or virtual, such as +software modifications that render keys available to the attacker. +Both of these types of interactions introduce a risk that they will be +discovered, e.g., by employees of the collaborator organization +noticing suspicious meetings or suspicious code changes. + +Content exfiltration has a similar risk profile to dynamic key +exfiltration. In a content exfiltration attack, the attacker saves +the cost and risk of conducting a passive pervasive attack. The risk of +discovery through interactions with the collaborator, however, is +still present, and may be higher. The content of a communication is +obviously larger than the key used to encrypt it, often by several +orders of magnitude. So in the content exfiltration case, the +interactions between the collaborator and the attacker need to be much +higher-bandwidth than in the key exfiltration cases, with a +corresponding increase in the risk that this high-bandwidth channel +will be discovered. + +It should also be noted that in these latter three exfiltration cases, +the collaborator also undertakes a risk that his collaboration with +the attacker will be discovered. Thus the attacker may have to incur +additional cost in order to convince the collaborator to participate +in the attack. Likewise, the scope of these attacks is limited to +case where the attacker can convince a collaborator to participate. +If the attacker is a national government, for example, it may be able +to compel participation within its borders, but have a much more +difficult time recruiting foreign collaborators. + +As noted above, the collaborator in an exfiltration attack can be +unwitting; the attacker can steal keys or data to enable the attack. +In some ways, the risks of this approach are similar to the case of an +active collaborator. In the static case, the attacker needs to steal +information from the collaborator once; in the dynamic case, the +attacker needs to continued presence inside the collaborators systems. +The main difference is that the risk in this case is of automated +discovery (e.g., by intrusion detection systems) rather than discovery +by humans. + +
+
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+ +This document describes a threat model for pervasive surveillance +attacks. Mitigations are to be given in a future document. + +
+
+ +This document has no actions for IANA. + +
+
+ +Jari Arkko (IETF Chair) + Mary Barnes + Marc Blanchet + Ralph Droms + Ted Hardie + Joe Hildebrand + Russ Housley + Erik Nordmark + Robert Sparks + Andrew Sullivan + Dave Thaler + Brian Trammell + Suzanne Woolf + +
+
+ +Thanks to Dave Thaler for the list of attacks and taxonomy; to Security Area +Directors Stephen Farrell, Sean Turner, and Kathleen Moriarty for starting and +managing the IETF’s discussion on pervasive attack; and to Stephan Neuhaus, +Mark Townsley, Chris Inacio, Evangelos Halepilidis, Bjoern Hoehrmann, Aziz +Mohaisen, Russ Housley, Joe Hall, Andrew Sullivan, the IEEE 802 Privacy +Executive Committee SG, and the IAB Privacy and Security Program for their +input. + +
+ + + + + + + + +&RFC6973; + + + + + + + + + How the NSA is still harvesting your online data + + The Guardian + + + + + + + NSA's Prism surveillance program: how it works and what it can do + + The Guardian + + + + + + + XKeyscore: NSA tool collects 'nearly everything a user does on the internet' + + The Guardian + + + + + + + How does GCHQ's internet surveillance work? + + The Guardian + + + + + + + N.S.A. Able to Foil Basic Safeguards of Privacy on Web + + The New York Times + + + + + + + Project Bullrun – classification guide to the NSA's decryption program + + The Guardian + + + + + + + Revealed: how US and UK spy agencies defeat internet privacy and security + + The Guardian + + + + + + + How the NSA Attacks Tor/Firefox Users With QUANTUM and FOXACID + + + + + + + + + 'Tor Stinks' presentation – read the full document + + The Guardian + + + + + + + NSA collecting phone records of millions of Verizon customers daily + + The Guardian + + + + + + + NSA Prism program taps in to user data of Apple, Google and others + + The Guardian + + + + + + + Sigint – how the NSA collaborates with technology companies + + The Guardian + + + + + + + NSA's Secret Toolbox: Unit Offers Spy Gadgets for Every Need + + + + + + + + + The Digital Arms Race: NSA Preps America for Future Battle + + + + + + + + + China's Great Cannon + + + + + + +&RFC1035; +&RFC1918; +&RFC1939; +&RFC3261; +&RFC3365; +&RFC3501; +&RFC4033; +&RFC4303; +&RFC4949; +&RFC5246; +&RFC5321; +&RFC6962; +&RFC7011; +&RFC7258; +&I-D.ietf-dprive-problem-statement; + + + + + + + + +