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Aardvark - Multi-Account AWS IAM Access Advisor API

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<img align="center" alt="Aardvark Logo" src="docs/images/aardvark_logo.jpg" width="10%" display="block">

Aardvark is a multi-account AWS IAM Access Advisor API (and caching layer).

Install:

Ensure that you have Python 3.6 or later. Python 2 is no longer supported.

git clone https://github.com/Netflix-Skunkworks/aardvark.git
cd aardvark
python3 -m venv env
. env/bin/activate
python setup.py develop

Known Dependencies

Configure Aardvark

The Aardvark config wizard will guide you through the setup.

% aardvark config

Aardvark can use SWAG to look up accounts. https://github.com/Netflix-Skunkworks/swag-client
Do you use SWAG to track accounts? [yN]: no
ROLENAME: Aardvark
DATABASE [sqlite:////home/github/aardvark/aardvark.db]:
# Threads [5]:

>> Writing to config.py

Create the DB tables

aardvark create_db

IAM Permissions:

Aardvark needs an IAM Role in each account that will be queried. Additionally, Aardvark needs to be launched with a role or user which can sts:AssumeRole into the different account roles.

AardvarkInstanceProfile:

AardvarkRole:

iam:GenerateServiceLastAccessedDetails
iam:GetServiceLastAccessedDetails
iam:listrolepolicies
iam:listroles
iam:ListUsers
iam:ListPolicies
iam:ListGroups

So if you are monitoring n accounts, you will always need n+1 roles. (n AardvarkRoles and 1 AardvarkInstanceProfile).

Note: For locally running aardvark, you don't have to take care of the AardvarkInstanceProfile. Instead, just attach a policy which contains "sts:AssumeRole" to the user you are using on the AWS CLI to assume Aardvark Role. Also, the same user should be mentioned in the trust policy of Aardvark Role for proper assignment of the privileges.

Gather Access Advisor Data

You'll likely want to refresh the Access Advisor data regularly. We recommend running the update command about once a day. Cron works great for this.

Without SWAG:

If you don't have SWAG you can pass comma separated account numbers:

aardvark update -a 123456789012,210987654321

With SWAG:

Aardvark can use SWAG to look up accounts, so you can run against all with:

aardvark update

or by account name/tag with:

aardvark update -a dev,test,prod

API

Start the API

aardvark start_api -b 0.0.0.0:5000

In production, you'll likely want to have something like supervisor starting the API for you.

Use the API

Swagger is available for the API at <Aardvark_Host>/apidocs/#!.

Aardvark responds to get/post requests. All results are paginated and pagination can be controlled by passing count and/or page arguments. Here are a few example queries:

curl localhost:5000/api/1/advisors
curl localhost:5000/api/1/advisors?phrase=SecurityMonkey
curl localhost:5000/api/1/advisors?arn=arn:aws:iam::000000000000:role/SecurityMonkey&arn=arn:aws:iam::111111111111:role/SecurityMonkey
curl localhost:5000/api/1/advisors?regex=^.*Monkey$

Docker

Aardvark can also be deployed with Docker and Docker Compose. The Aardvark services are built on a shared container. You will need Docker and Docker Compose installed for this to work.

To configure the containers for your set of accounts create a .env file in the root of this directory. Define the environment variables within this file. This example uses AWS Access Keys. We recommend using instance roles in production.

AARDVARK_ROLE=Aardvark
AARDVARK_ACCOUNTS=<account id>
AWS_DEFAULT_REGION=<aws region>
AWS_ACCESS_KEY_ID=<your access key>
AWS_SECRET_ACCESS_KEY=<you secret key>
NameServiceDescription
AARDVARK_ROLEcollectorThe name of the role for Aardvark to assume so that it can collect the data.
AARDVARK_ACCOUNTScollectorOptional if using SWAG, otherwise required. Set this to a list of SWAG account name tags or a list of AWS account numbers from which to collect Access Advisor records.
AWS_ARN_PARTITIONcollectorRequired if not using an AWS Commercial region. For example, aws-us-gov. By default, this is aws.
AWS_DEFAULT_REGIONcollectorRequired if not running on an EC2 instance with an appropriate Instance Profile. Set these to the credentials of an AWS IAM user with permission to sts:AssumeRole to the Aardvark audit role.
AWS_ACCESS_KEY_IDcollectorRequired if not running on an EC2 instance with an appropriate Instance Profile. Set these to the credentials of an AWS IAM user with permission to sts:AssumeRole to the Aardvark audit role.
AWS_SECRET_ACCESS_KEYcollectorRequired if not running on an EC2 instance with an appropriate Instance Profile. Set these to the credentials of an AWS IAM user with permission to sts:AssumeRole to the Aardvark audit role.
AARDVARK_DATABASE_URIcollector and apiserverSpecify a custom database URI supported by SQL Alchemy. By default, this will use the AARDVARK_DATA_DIR value to create a SQLLite Database. Example: sqlite:///$AARDVARK_DATA_DIR/aardvark.db

Once this file is created, then build the containers and start the services. Aardvark consists of three services:

# build the containers
docker-compose build

# start up the containers
docker-compose up

Finally, to clean up the environment

# bring down the containers
docker-compose down

# remove the containers
docker-compoes rm

Notes

Threads

Aardvark will launch the number of threads specified in the configuration. Each of these threads will retrieve Access Advisor data for an account and then persist the data.

Database

The regex query is only supported in Postgres (natively) and SQLite (via some magic courtesy of Xion in the sqla_regex file).

TLS

We recommend enabling TLS for any service. Instructions for setting up TLS are out of scope for this document.

Signals

New in v0.3.1

Aardvark uses Blinker for signals in its update process. These signals can be used for things like emitting metrics, additional logging, or taking more actions on accounts. You can use them by writing a script that defines your handlers and calls aardvark.manage.main(). For example, create a file called signals_example.py with the following contents:

import logging

from aardvark.manage import main
from aardvark.updater import AccountToUpdate

logger = logging.getLogger('aardvark_signals')


@AccountToUpdate.on_ready.connect
def handle_on_ready(sender):
    logger.info(f"got on_ready from {sender}")


@AccountToUpdate.on_complete.connect
def handle_on_complete(sender):
    logger.info(f"got on_complete from {sender}")


if __name__ == "__main__":
    main()

This file can now be invoked in the same way as manage.py:

python signals_example.py update -a cool_account

The log output will be similar to the following:

INFO: getting bucket swag-bucket
INFO: Thread #1 updating account 123456789012 with all arns
INFO: got on_ready from <aardvark.updater.AccountToUpdate object at 0x10c379b50>
INFO: got on_complete from <aardvark.updater.AccountToUpdate object at 0x10c379b50>
INFO: Thread #1 persisting data for account 123456789012
INFO: Thread #1 FINISHED persisting data for account 123456789012

Available signals

ClassSignals
manage.UpdateAccountThreadon_ready, on_complete, on_failure
updater.AccountToUpdateon_ready, on_complete, on_error, on_failure

TODO:

See TODO