<ul><li>Researchers at the University of Florida have developed ThreatLens, an LLM-driven multi-agent framework for automating hardware security threat modeling and test plan generation.</li><li>The current hardware security verification processes rely on labor-intensive manual efforts, which struggle to scale with increasing design complexity and evolving attack methodologies.</li><li>ThreatLens integrates retrieval-augmented generation (RAG), LLM-powered reasoning, and user feedback to automate threat assessment and generate practical test plans.</li><li>The framework reduces manual verification effort, enhances coverage, and ensures a structured, adaptable approach to hardware security verification.</li></ul>

LLM-based Agentic Framework Automating HW Security Threat Modeling And Test Plan Generation (U. of Florida)

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