dirty-waters 0.2.0

Automatically detect software supply chain smells and issues

dirty-waters

Dirty-waters automatically finds software supply chain issues in software projects by analyzing the available metadata of all dependencies, transitively.

Reference: Dirty-Waters: Detecting Software Supply Chain Smells, Technical report 2410.16049, arXiv, 2024.

By using dirty-waters, you identify the shady areas of your supply chain, which would be natural target for attackers to exploit.

Kinds of problems identified by dirty-waters

• Dependencies with no link to source code repositories (high severity)
• Dependencies with no tag / commit sha for release, impossible to have reproducible builds (high severity)
• Deprecated Dependencies (medium severity)
• Depends on a fork (medium severity)
• Dependencies with no build attestation (low severity)

Additionally, dirty-waters gives a supplier view on the dependency trees (who owns the different dependencies?)

dirty-waters is developed as part of the Chains research project.

NPM Support

Installation

To set up the Dirty-Waters, follow these steps:

1. Clone the repository:

git clone https://github.com/chains-project/dirty-waters.git
cd dirty-waters

2. Set up a virtual environment and install dependencies:

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
cd tool

In alternative, you may also use the Nix flake present in this repository.

3. Set up the GitHub API token (ideally, in a .env file):

export GITHUB_API_TOKEN=<your_token>

Usage

Run the tool using the following command structure:

python main.py -p <project_repo_name> -v <release_version_old> -s -pm <package_manager> [-vn <release_version_new>] [-d]

Arguments:

usage: main.py [-h] -p PROJECT_REPO_NAME -v RELEASE_VERSION_OLD [-vn RELEASE_VERSION_NEW] -s [-d] -pm
               {yarn-classic,yarn-berry,pnpm} [--pnpm-scope]

options:
  -p PROJECT_REPO_NAME, --project-repo-name PROJECT_REPO_NAME
                        Specify the project repository name. Example: MetaMask/metamask-extension
  -v RELEASE_VERSION_OLD, --release-version-old RELEASE_VERSION_OLD
                        The old release tag of the project repository. Example: v10.0.0
  -vn RELEASE_VERSION_NEW, --release-version-new RELEASE_VERSION_NEW
                        The new release version of the project repository.
  -s, --static-analysis
                        Run static analysis and generate a markdown report of the project
  -d, --differential-analysis
                        Run differential analysis and generate a markdown report of the project
  -pm {yarn-classic,yarn-berry,pnpm,npm}, --package-manager {yarn-classic,yarn-berry,pnpm,npm}
                        The package manager used in the project.
  --pnpm-scope          Extract dependencies from pnpm with a specific scope
                        using 'pnpm list --filter <scope> --depth Infinity'
                        command. Configure the scope in tool_config.py file.

Example usage:

1. Software supply chain smell analysis:

python3 main.py -p MetaMask/metamask-extension -v v11.11.0 -s -pm yarn-berry

• Example output: Software Supply Chain Smells Report Example

2. Differential analysis:

python3 main.py -p MetaMask/metamask-extension -v v11.11.0 -vn v11.12.0 -s -d -pm yarn-berry

Notes:

• -v should be the version of GitHub release, e.g. for this release, the value should be v11.11.0, not Version 11.11.0 or 11.11.0.
• The -s flag is required for all analyses.
• When using -d for differential analysis, both -v and -vn must be specified.

Java Support

Installation

Usage

Usage: Example reports: TODO add link

Academic Work

• Dirty-Waters: Detecting Software Supply Chain Smells

Other issues not handled by dirty-waters

• Missing dependencies: simply run mvn/pip/... install :)
• Bloated dependencies: we recommend DepClean for Java, depcheck for NPM
• Version constraint inconsistencies: we recommend pipdeptree for Python

License

MIT License.