Please report security issues privately via GitHub's Report a vulnerability (Security → Advisories) rather than opening a public issue. Include steps to reproduce and, where possible, a proof of concept. We aim to acknowledge reports within a few days.

This project is a defensive tool — a firewall for LLM traffic. Relevant reports include:

• Detection bypasses (a prompt-injection / secret / PII / harmful-content payload that evades a detector it should catch), with a concrete example.
• Over-defense regressions (benign inputs wrongly blocked) that materially raise the false-positive rate.
• Memory-safety, denial-of-service, or request-smuggling issues in the proxy.

• The default build is regex + heuristics only; higher recall requires the optional --features ml stage. A "miss" that the ML stage catches is a documented tradeoff, not a vulnerability.
• Detection is probabilistic. No classifier is perfect; see docs/methodology.md for measured recall and false-positive rates and their honest limits.
• The content-moderation layer is not a full safety system and makes no claim to detect illegal material (e.g. CSAM).