ALIBI: Adaptive Agentic Attacks on LLM-Based Vulnerability Detectors via Adversarial Code Comments

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arXiv:2607.24964v1 Announce Type: new Abstract: Large language models are increasingly deployed for security-sensitive tasks such as vulnerability detection and code review. Their reliance on natural-language context embedded in source code exposes a previously underexplored attack surface: adversarial comments that can influence a detector's reasoning without changing program behavior. We study LLM-based vulnerability detectors against a new adversary: a coding agent that implements new functi