Unlike the more common postinstall-hook supply-chain pattern, this campaign executes at module-load (import/require) time. When any consuming build or application imports a poisoned package, the injected block runs immediately. Because the trigger is an import rather than an install script, the common npm install –ignore-scripts mitigation does not neutralize it.

After loading a project, Cursor attempts to find git binaries at various locations including the current workspace. By creating a repository with a planted malicious git.exe in the root, the IDE will execute it with no user interaction and no prompting of the user. This occurs repeatedly on a cadence.

SymJack is a new attack technique targeting AI coding agents: a booby-trapped repository to trick your AI coding assistant into overwriting its own configuration through a disguised file copy, then run attacker code on the next restart. This is one technique that works against the whole category, don’t treat it as six separate bugs.

My personal conclusion can however not end up with anything else than that the big hype around this model so far was primarily marketing. I see no evidence that this setup finds issues to any particular higher or more advanced degree than the other tools have done before Mythos. Maybe this model is a little bit better, but even if it is, it is not better to a degree that seems to make a significant dent in code analyzing.

cross-posted from: https://lemmy.bestiver.se/post/1069240

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A minimal Node.js wrapper around ClamAV that scans any file and returns a typed Verdict Symbol:

• Verdict.Clean
• Verdict.Malicious
• Verdict.ScanError

Zero runtime dependencies. No daemon. No cloud. No native bindings. Works locally via clamscan or remotely via clamd TCP socket (Docker-friendly).

npm install pompelmi

Repo: https://github.com/pompelmi/pompelmi Issues, PRs, and stars all welcome — it's how open source stays alive.

Anthropic presents Mythos and Project Glasswing as evidence that advanced AI vulnerability research should be restricted. But our replication suggests a different conclusion: the capabilities Anthropic points to are already available in public models, so defenders should prepare for that reality instead.

cross-posted from: https://lemmy.bestiver.se/post/1051864

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The AI Security Institute (AISI) conducted evaluations of Anthropic’s Claude Mythos Preview (announced on 7th April) to assess its cybersecurity capabilities. Our results show that Mythos Preview represents a step up over previous frontier models in a landscape where cyber performance was already rapidly improving.