A new technical paper titled “ThreatLens: LLM-guided Threat Modeling and Test Plan Generation for Hardware Security Verification” was published by researchers at University of Florida.
Abstract
“Current hardware security verification processes predominantly rely on manual threat modeling and test plan generation, which are labor-intensive, error-prone, and struggle to scale with increasing design complexity and evolving attack methodologies. To address these challenges, we propose ThreatLens, an LLM-driven multi-agent framework that automates security threat modeling and test plan generation for hardware security verification. ThreatLens integrates retrieval-augmented generation (RAG) to extract relevant security knowledge, LLM-powered reasoning for threat assessment, and interactive user feedback to ensure the generation of practical test plans. By automating these processes, the framework reduces the manual verification effort, enhances coverage, and ensures a structured, adaptable approach to security verification. We evaluated our framework on the NEORV32 SoC, demonstrating its capability to automate security verification through structured test plans and validating its effectiveness in real-world scenarios.”
Find the technical paper here. March 2025.
Saha, Dipayan, Hasan Al Shaikh, Shams Tarek, and Farimah Farahmandi. “ThreatLens: LLM-guided Threat Modeling and Test Plan Generation for Hardware Security Verification.” Cryptology ePrint Archive (2025).
Leave a Reply