AINeutralarXiv – CS AI · 7h ago6/10
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SeClaw: Spec-Driven Security Task Synthesis for Evaluating Autonomous Agents
Researchers introduce SeClaw, a framework for systematically evaluating security vulnerabilities in autonomous LLM agents through specification-driven task synthesis and execution-based testing. The tool addresses gaps in current agent security benchmarks by providing scalable, reproducible assessment of unsafe behaviors across diverse risk scenarios.