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Michael #1: Lock the Ghost
- The five core takeaways:
- PyPI "removal" doesn't delete distribution files. When a package is removed from PyPI, it disappears from the index and project page, but the actual distribution files remain accessible if you have a direct URL to them.
- uv.lock uniquely preserves access to ghost packages. Because uv.lock stores direct URLs to distribution files rather than relying on the index API at install time, uv sync can successfully install packages that have already been removed, even with cache disabled. No other Python lock file implementation tested behaved this way.
- This creates a supply chain attack vector. An attacker could upload a malicious package, immediately remove it to dodge automated security scanning, and still have it installable via a uv.lock file, or combine this with the xz-style strategy of hiding malicious additions in large, auto-generated lock files that nobody reviews.
- Removed package names can be hijacked with version collisions. When an owner removes a package, the name can be reclaimed by someone else who can upload different distribution types under the same version number, as happened with "umap." Lock files help until you regenerate them, then you're exposed.
- Your dependency scanning needs to cover lock files, not just manifest files. Scanning only pyproject.toml or requirements.txt misses threats embedded in lock files, which is where the actual resolved URLs and hashes live.
Brian #2: Fence for Sandboxing
- Suggested by Martin Häcker
- “Some coding platforms have since integrated built-in sandboxing (e.g., Claude Code) to restrict write access to directories and/or network connectivity. However, these safeguards are typically optional and not enabled by default.”
- “JY Tan (on cc) has extracted the sandboxing logic from Claude Code and repackaged it into a standalone Go binary.”
- Source code on GitHub: https://github.com/Use-Tusk/fence
- Related:
Michael #3: MALUS: Liberate Open Source
- via Paul Bauer
- The service will generate the specs of a library with one AI and build the newly licensed library using the specs with another AI circumventing the licensing and copyright rules.
- AI that has not been trained on open source reads the docs and API signature, creates a spec. Another AI processes that spec into working software.
- Is it a real site? Are they accepting real money, or are they just trying to cause a stir around copyright?
Brian #4: Harden your GitHub Actions Workflows with zizmor, dependency pinning, and dependency cooldowns
Extras
Brian:
Michael:
Joke: Can you?
