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Config Validator | Setup & User Guide

Go from setup to proof-of-concept in under 1 hour

Table of Contents

Overview

As your business shifts towards an infrastructure-as-code workflow, security and cloud administrators are concerned about misconfigurations that may cause security and governance violations.

Cloud Administrators need to be able to put up guardrails that follow security best practices and help drive the environment towards programmatic security and governance while enabling developers to go fast.

Config Validator allows your administrators to enforce constraints that validate whether deployments can be provisioned while still enabling developers to move quickly within these safe guardrails. Validator accomplishes this through a three key components:

One way to define constraints

Constraints are defined so that they can work across an ecosystem of pre-deployment and monitoring tools. These constraints live in your organization's repository as the source of truth for your security and governance requirements. You can obtain constraints from the Policy Library, or build your own constraint templates.

Pre-deployment check

Check for constraint violations during pre-deployment and provide warnings or halt invalid deployments before they reach production. The pre-deployment logic that Config Validator uses will be built into a number of deployment tools. For details, check out Terraform Validator.

Ongoing monitoring

Frequently scan the platform for constraint violations and send notifications when a violation is found. The monitoring logic that Config Validator uses will be built into a number of monitoring tools. For example, check out How to Use Config Validator with Forseti.

The following guide will walk you through initial setup steps and instructions on how to use Config Validator. By the end, you will have a proof-of-concept to experiment with and to build your foundation upon.

How to set up constraints with Policy Library

Get started with the Policy Library repository

The Policy Library repository contains the following directories:

  • policies
    • constraints: This is initially empty. You should place your constraint files here.
    • templates: This directory contains pre-defined constraint templates.
  • validator: This directory contains the .rego files and their associated unit tests. You do not need to touch this directory unless you intend to modify existing constraint templates or create new ones. Running make build will inline the Rego content in the corresponding constraint template files.

Google provides a sample repository with a set of pre-defined constraint templates. You can duplicate this repository into a private repository. First you should create a new private git repository. For example, if you use GitHub then you can use the GitHub UI. Then follow the steps below to get everything setup.

Note: If you are planning on using the Policy Library Sync feature of Forseti, then you should also add a read-only user to the private repository which will be used by Forseti.

This policy library can also be made public, but it is not recommended. By making your policy library public, it would be allowing others to see what you are and ARE NOT scanning for.

Duplicate Policy Library Repository

To run the following commands, you will need to configure git to connect securely. It is recommended to connect with SSH. Here is a helpful resource for learning about how this works, including steps to set this up for GitHub repositories; other providers offer this feature as well.

export GIT_REPO_ADDR="[email protected]:${YOUR_GITHUB_USERNAME}/policy-library.git"
git clone --bare https://github.com/GoogleCloudPlatform/policy-library.git
cd policy-library.git
git push --mirror ${GIT_REPO_ADDR}
cd ..
rm -rf policy-library.git
git clone ${GIT_REPO_ADDR}

Setup Constraints

Then you need to examine the available constraint templates inside the templates directory. Pick the constraint templates that you wish to use, create constraint YAML files corresponding to those templates, and place them under policies/constraints. Commit the newly created constraint files to your Git repository. For example, assuming you have created a Git repository named "policy-library" under your GitHub account, you can use the following commands to perform the initial commit:

cd policy-library
# Add new constraints...
git add --all
git commit -m "Initial commit of policy library constraints"
git push -u origin master

Pull in latest changes from Public Repository

Periodically you should pull any changes from the public repository, which might contain new templates and Rego files.

git remote add public https://github.com/GoogleCloudPlatform/policy-library.git
git pull public master
git push origin master

Instantiate constraints

The constraint template library only contains templates. Templates specify the constraint logic, and you must create constraints based on those templates in order to enforce them. Constraint parameters are defined as YAML files in the following format:

apiVersion: constraints.gatekeeper.sh/v1alpha1
kind: # place constraint template kind here
metadata:
  name: # place constraint name here
spec:
  severity: # low, medium, or high
  match:
    ancestries: [] # put the constraint application ancestries here
    excludedAncestries: [] # optional, default is no exclusions
  parameters: # put the parameters defined in constraint template here

The ancestries field is specified in a path-like format. It specifies where in the GCP resources hierarchy the constraint is to be applied. For example:

Target Description
organizations/** All organizations
organizations/123/** Everything in organization 123
organizations/123/folders/** Everything in organization 123 that is under a folder
organizations/123/folders/456 Everything in folder 456 in organization 123
organizations/123/folders/456/projects/789 Everything in project 789 in folder 456 in organization 123

The excludedAncestries field follows the same pattern and has precedence over the ancestries field. If a resource is in both, it will be excluded.

The schema of the parameters field is defined in the constraint template, using the OpenAPI V3 schema. This is the same validation schema in Kubernetes's custom resource definition. Every template contains a validation section that looks like the following:

validation:
  openAPIV3Schema:
    properties:
      mode:
        type: string
      instances:
        type: array
        items: string

According to the template above, the parameter field in the constraint file should contain a string named mode and a string array named instances. For example:

parameters:
  mode: allowlist
  instances:
    - //compute.googleapis.com/projects/test-project/zones/us-east1-b/instances/one
    - //compute.googleapis.com/projects/test-project/zones/us-east1-b/instances/two

These parameters specify that two VM instances may have external IP addresses. The are exempt from the constraint since they are allowlisted.

Here is a complete example of a sample external IP address constraint file:

apiVersion: constraints.gatekeeper.sh/v1alpha1
kind: GCPExternalIpAccessConstraintV1
metadata:
  name: forbid-external-ip-allowlist
spec:
  severity: high
  match:
    ancestries: ["organizations/**"]
  parameters:
    mode: "allowlist"
    instances:
    - //compute.googleapis.com/projects/test-project/zones/us-east1-b/instances/one
    - //compute.googleapis.com/projects/test-project/zones/us-east1-b/instances/two

How to validate policies

Follow the instructions to validate policies in your local or production environments.

How to Use Config Validator with Forseti

Deploy Forseti

Follow the documentation on the Forseti Security website to deploy Forseti on GCE. As part of the Terraform configuration, you will need to enable Config Validator. Follow the documentation on the Forseti Security website to set up Config Validator.

Provide Policies to Forseti Server

The recommended practice is to store the Policy Library in a VCS such as GitHub or other git repository. This supports the idea of policy as code and requires work to setup the repository and connect it with Forseti. Once the repository is setup, then Forseti will automatically sync policy updates to the Forseti Server to be used by future scans.

The default behavior of Forseti is to sync the Policy Library from the Forseti Server GCS bucket. This requires little setup, but involves manual work to create the folder and copy the policies to GCS.

Follow the documentation on the Forseti Security website to sync policies from the GCS to the Forseti server, and from Git Repository to the Forseti server.

End to end workflow with sample constraint

In this section, you will apply a constraint that enforces IAM policy member domain restriction using Cloud Shell.

First click on this link to open a new Cloud Shell session. The Cloud Shell session has Terraform pre-installed and the Policy Library repository cloned. Once you have the session open, the next step is to copy over the sample IAM domain restriction constraint:

cp samples/iam_service_accounts_only.yaml policies/constraints

Let's take a look at this constraint:

apiVersion: constraints.gatekeeper.sh/v1alpha1
kind: GCPIAMAllowedPolicyMemberDomainsConstraintV1
metadata:
  name: service_accounts_only
spec:
  severity: high
  match:
    ancestries: ["organizations/**"]
  parameters:
    domains:
      - gserviceaccount.com

It specifies that only members from gserviceaccount.com domain can be present in an IAM policy. To verify that it works, let's attempt to create a project. Create the following Terraform main.tf file:

provider "google" {
  version = "~> 1.20"
  project = "your-terraform-provider-project"
}

resource "random_id" "proj" {
  byte_length = 8
}

resource "google_project" "sample_project" {
  project_id      = "validator-${random_id.proj.hex}"
  name            = "config validator test project"
}

resource "google_project_iam_binding" "sample_iam_binding" {
  project = "${google_project.sample_project.project_id}"
  role    = "roles/owner"

  members = [
    "user:your-email@your-domain"
  ]
}

Make sure to specify your Terraform provider project and email address. Then initialize Terraform and generate a Terraform plan:

terraform init
terraform plan -out=test.tfplan
terraform show -json ./test.tfplan > ./tfplan.json

Since your email address is in the IAM policy binding, the plan should result in a violation. Let's try this out:

gcloud beta terraform vet tfplan.json --policy-library=policy-library

The Terraform validator should return a violation. As a test, you can relax the constraint to make the violation go away. Edit the policy-library/policies/constraints/iam_service_accounts_only.yaml file and append your email domain to the domains allowlist:

apiVersion: constraints.gatekeeper.sh/v1alpha1
kind: GCPIAMAllowedPolicyMemberDomainsConstraintV1
metadata:
  name: service_accounts_only
spec:
  severity: high
  match:
    ancestries: ["organizations/**"]
  parameters:
    domains:
      - gserviceaccount.com
      - your-domain-here

Then run Terraform plan and validate the output again:

terraform plan -out=test.tfplan
terraform show -json ./test.tfplan > ./tfplan.json
gcloud beta terraform vet tfplan.json --policy-library=policy-library

The command above should result in no violations found.

Contact Info

Questions or comments? Please contact [email protected].