As large language models (LLMs) are deployed as autonomous agents, safety failures increasingly involve consequential actions. We study agentic misalignment, where agents take harmful actions under goal conflicts and pressures. Using chain-of-thought (CoT) monitoring, we find that harmful execution is often preceded by...
Yu-Tong Zhang, Jianshuo Dong, Peng Xu et al.· 0 citations
This paper proposes LeakGauge, which probes this response by appending a suffix that gauges leakage behavior and mapping its prefill token probabilities to an attack-risk score, and shows that the risk score is sensitive to an internal leakage-related direction.
Maosen Zhang, Jianshuo Dong, Bo-Han Lu et al.· 1 citation
A probe-gated reasoning-based defense is introduced to bridge a knowledge-action gap in agentic LLMs when they are exposed to IPI attacks, and an analysis framework is introduced that identifies natural-language explanations strongly correlated with probe-captured signals.