AI RESEARCH

SLEIGHT-Bench: A Benchmark of Evasion Attacks Against Agent Monitors

arXiv CS.AI

ArXi:2605.16626v2 Announce Type: replace-cross Since autonomous coding agents generate complex behaviors at high-volume, we may want to use other LLMs to monitor actions to reduce the risk from dangerous misaligned behavior. To better understand the limitations of such monitors against the diverse attack strategies that a coding agent could use, we present SLEIGHT-Bench (Subtle Low-itEration Insight-Guided Harmful Transcripts), a benchmark of synthetic transcripts containing 40 attacks across 11 categories, each showing a coding agent covertly pursuing a harmful objective (e.g.