AI Breakthroughs
SHE evolves agent safety harnesses from failure trajectories, cutting ASR 3.1x
By Arjun
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13 Aug 8:08 PM
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Via arXiv
Researchers from Shanghai AI Laboratory, Fudan, SJTU, and HKUST propose SHE, a framework that treats the agent harness as an evolving safety system rather than a fixed scaffold. SHE splits the harness into a system prompt, rule bank, safety memory, and tool policy, then routes failure trajectories into localized edits that pass a safety-utility check. On Agent-SafetyBench, SHE cut attack success roughly 3.1 times versus a static SafeHarness baseline while raising benign utility, and the evolved harness transferred to held-out AgentHarm and across agent models. Results are benchmark-bound and harness edits can still trade off usefulness, so production gains will need live monitoring.
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