Skip to main content

AWS Attack Automation

Timberlake is an AWS attack automation utility that can execute one or more test cases. You can read the release blog here: link

Test cases are individual YAML documents that define the setup, execution, and cleanup steps for an attack procedure. These documents contain both metadata about the attack (e.g. MITRE mappings, permissions) as well as Python code for executing the attack.

Timberlake is designed with modularity in mind. Test cases are defined and managed outside the tool and can be swapped around as needed for different execution scenarios.

Notable features of Timberlake:

  • Support for multiple credential profiles
  • Premade operations avaiable to all test cases (e.g. compound API actions, canned policies, etc)
  • API-level logging, including parameters
  • VECTR integration for tracking attack details

Example use can be found in examples

Note: Test cases should ideally be run in a non-production account

Install

pip install dist/*.whl

PyPI

pip install timberlake

Then install the following dependencies:

pip install git+https://github.com/SecurityRiskAdvisors/py-attire-schema.git

Usage

usage: timberlake [-h] -c CONFIG [-p PHASES] [-a ARGS]

optional arguments:
  -h, --help            show this help message and exit
  -c CONFIG, --config CONFIG
                        config file path
  -p {execution,setup,cleanup} [{execution,setup,cleanup} ...], --phases {execution,setup,cleanup} [{execution,setup,cleanup} ...]
                        list of phases to execute; default = all
  -a ARGS, --args ARGS  args file path
  • Config : path to config file; must exist
  • Phases : one or more phase names to execute; order doesn't matter
  • Args : YAML document of key-value pairs to override test case args

Details

Annotated schemas

Refer to test-case-schema.yml for test case schema details

Refer to config.yml for config file schema details

Attack sequencing

Basic execution

Basic execution mode refers to execution without using the VECTR integrations. The execution sequence is as follows:

  1. Collect test cases
  2. Run pre-execution hooks (e.g logging)
  3. Run test case blocks by phase (setup -> execution -> cleanup)
  4. Run post-execution hooks
  5. Exit

Execution details are logged to the TIMBERLAKE_LOGFILE location.

VECTR execution

VECTR execution mode refers to execution with added VECTR integration (via GraphQL). The excution sequence is as follows:

  1. Collect test cases
  2. Create assessment groups and campaigns in VECTR
  3. Run pre-execution hooks (e.g logging)
  4. Run test case blocks by phase (setup -> execution -> cleanup)
  5. Create test case in VECTR
    • all test cases are tagged with "timberlake"
    • test cases with errors are tagged with "error"
  6. Run post-execution hooks
  7. Write ATTiRe log to location specified in config. Details captured in ATTiRe log:
    • Cloud control plane API call details
  8. Exit

Note: Only code blocks in the execution phase create a test case and ATTiRe log

See also

  • https://github.com/FSecureLABS/leonidas : is a very similar concept, but test cases are performed as Lambda functions; test case schema is conceptually similar to what this tool wants to do and was a source of design inspiration

Metadata

Release files for timberlake 1.0.6

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for timberlake 1.0.6
File Interpreter ABI Platform Actions
timberlake-1.0.6-py3-none-any.whl Python 3 none any Details for timberlake-1.0.6-py3-none-any.whl

Release files / timberlake-1.0.6-py3-none-any.whl

Download URL timberlake-1.0.6-py3-none-any.whl
Size 24.3 kB
Tags Python 3
SHA-256 checksum
How to use checksums
3dd87a68e5adb994cebcadc3ebeb78ded26351dee3fd4e0ec334fcc24931677e
BLAKE2b-256 checksum
How to use checksums
8499896dad76ecb01fbd376b08ea7e74186b58f1b098c15fb7112b728158f109
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.13.7

Security for timberlake 1.0.6

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page