3 papers
cs.CR2026
ProveRAG: Provenance-Driven Vulnerability Analysis with Automated Retrieval-Augmented LLMs
Reza Fayyazi, Stella Hoyos Trueba, Michael Zuzak +1
In cybersecurity, security analysts constantly face the challenge of mitigating newly discovered vulnerabilities in real-time, with over 300,000 vulnerabilities identified since 19…
cs.CR2025
Guided Reasoning in LLM-Driven Penetration Testing Using Structured Attack Trees
Katsuaki Nakano, Reza Fayyazi, Shanchieh Jay Yang +1
Recent advances in Large Language Models (LLMs) have driven interest in automating cybersecurity penetration testing workflows, offering the promise of faster and more consistent v…
cs.CR2025
LLM Embedding-based Attribution (LEA): Quantifying Source Contributions to Generative Model's Response for Vulnerability Analysis
Reza Fayyazi, Michael Zuzak, Shanchieh Jay Yang
Large Language Models (LLMs) are increasingly used for cybersecurity threat analysis, but their deployment in security-sensitive environments raises trust and safety concerns. With…