pip-audit VS in-toto

Next up is making sure, none of the dependencies used throughout the project brings with it any already identified security issue. The makefile target audit, invokes the handy tool pip-audit.

Here is my "one true" Makefile for Python projects[1]. The skeleton gets tweaked slightly each time, but it's served me well for 4+ years.

[1]: https://github.com/pypa/pip-audit/blob/main/Makefile

Why use this over the established https://pypi.org/project/pip-audit/ ?

https://pypi.org/project/pip-audit/ details usage and the GitHub Action install.

If it's pure Python, the only packaging file you need is `pyproject.toml`. You can fill that file with packaging metadata per PEP 518 and PEP 621, including using modern build tooling like flit[1] for the build backend and build[2] for the frontend.

With that, you entire package build (for all distribution types) should be reducible to `python -m build`. Here's an example of a full project doing everything with just `pyproject.toml`[3] (FD: my project).

[1]: https://github.com/pypa/flit

[2]: https://github.com/pypa/build

[3]: https://github.com/pypa/pip-audit

- repo: https://github.com/trailofbits/pip-audit rev: v2.4.3 hooks: - id: pip-audit args: [ "-r", "requirements.txt" ] ci: # Leave pip-audit to only run locally and not in CI # pre-commit.ci does not allow network calls skip: [ pip-audit ]

This is really nicely written; kudos to the author for compiling a great deal of information in a readable format.

If I can be forgiven one nitpick: Poetry does not use a PEP 518-style[1] build configuration by default, which means that its use of `pyproject.toml` is slightly out of pace with the rest of the Python packaging ecosystem. That isn't to say that it isn't excellent, because it is! But you the standards have come a long way, and you can now use `pyproject.toml` with any build backend as long as you use the standard metadata.

By way of example, here's a project that's completely PEP 517 and PEP 518 compatible without needing a setup.py or setup.cfg[2]. Everything goes through pyproject.toml.

[1]: https://peps.python.org/pep-0518/

[2]: https://github.com/trailofbits/pip-audit/blob/main/pyproject...

Checking could be done if something like this eventually shows up in safety or pip-audit.

Something like python's pip-audit. For commercial solutions I know there's Snyk and Jfrog we can always purchase, but I'm interested to see if there's an open-source tool that can do this.

The things you mentioned are not solved by a typical "SBOM" but e.g. CycloneDX has extra fields to record provenance and pedigree and things like in-toto (https://in-toto.io/) or SLSA (https://slsa.dev/) also aim to work in this field.

I've spent the last six months in this field and people will tell you that this or that is an industry best practice or "a standard" but in my experience none of that is true. Everyone is still trying to figure out how best to protect the software supply chain security and things are still very much in flux.

in-toto is an open source project that focuses on the attestation part of software supply chain security. You use it to define a “layout” for a project, i.e., how the different components should fit together. A project ships this definition with its code, and then another user of that software can compare what they have with the attached definition to see if it matches the structure and contents they expect. If it doesn’t, then this could point to external tampering or other issues.

But it's not all doom and gloom because the industry is evolving. Companies like Google are formulating tools like scorecard to heuristically reduce risk by encouraging you to rely on trustable dependencies only. There's also more complex tools like in-toto that actually look at the integrity of your supply chain (don't ask me how this one works, I just know that people like it).