Lambda function to "rip apart" a CloudFormation template and check it for security compliance.
Sample pipeline with CFripper
CFripper is a Python tool that aims to prevent vulnerabilities from getting to production infrastructure through vulnerable CloudFormation scripts. As with the other security tools that we use at Skyscanner, CFripper is part of the CI/CD pipeline. It runs just before a CloudFormation stack is deployed or updated and if the CloudFormation script fails to pass the security check it fails the deployment and notifies the team that owns the stack. This is an example of how you might set up CFripper as an AWS Lambda:
Another approach that we use at Skyscanner is the Infrastructure as Code pipeline. Code is built and tested using drone and then our internal CD tool deals with calling CFripper to validate the script and then trigger the deployment of the infrastructure provided that the CloudFormation script is valid:
The project comes with a set of commands you can use to run common operations:
make install: Installs run time dependencies.
make install-dev: Installs dev dependencies together with run time dependencies.
make freeze: Freezes dependencies from
requirements.txt(including transitive ones).
make lint: Runs static analysis.
make coverage: Runs all tests collecting coverage.
make test: Runs
Running the simulator
To run the simulator make sure you have the dependencies installed using
make install-dev and run
You can add more scripts to the test set in
Be sure to also add them in the
scripts dictionary with their name, service name and project so that the simulator can pick them up.
To add custom rules first extend the Rule class. Then implement the
invoke method by adding your logic.
CFripper uses pycfmodel to create a Python model of the CloudFormation script. This model is passed to the
invoke function as the
resources parameter. You can use the model's iterate through the resources and other objects of the model and use the helper functions to perform various checks. Look at the current rules for examples.
By default, each rule has
MONITOR_MODE set to false. Monitor model will return the failed rules in another field in the response, instead in the main "failed rules". This way new rules can be tested before they are removed from monitor mode and start triggering alarms.
See CONTRIBUTING.md file to add a contribution.
Some of our rules were inspired by cfn-nag. We also use their example scripts in our test cases.
We use aws-cfn-template-flip to convert CloudFormation scripts before transforming them into a Python model.