EvoSafeHarness: Evolving Model- and Domain-Specific Harnesses for Securing Agents
Large Language Model (LLM) agents are turning language into real-world effects, making safety necessary against both indirect prompt injections and direct harmful requests. System-level safety harnesses add an enforcement layer beyond model-level defenses, but existing harnesses are usually designed once by experts and applied across heterogeneous models and domains. Effective
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Large Language Model (LLM) agents are turning language into real-world effects, making safety necessary against both indirect prompt injections and direct harmful requests. System-level safety harnesses add an enforcement layer beyond model-level defenses, but existing harnesses are usually designed once by experts and applied across heterogeneous models and domains. Effective
This research addresses a critical and growing concern in AI safety: how to effectively secure LLM agents operating in real-world environments. As agents become more autonomous, ensuring their safe and ethical operation through adaptive safety harnesses is paramount for deployment and public trust.