LLM-Assisted Vulnerability Research Technical Guide

This technical guide presents findings from research conducted by Bishop Fox on the use of large language models (LLMs) in vulnerability research, specifically focusing on patch differential analysis. The document outlines two approaches to LLM application: holistic and targeted. The targeted approach aims to augment human capabilities rather than replace them, with applications including programming assistance and standardizing LLM access to external services. The guide details experiments designed to assess how effectively LLMs can enhance standard methodologies in vulnerability research. It describes the methodology, results, and insights gained from testing LLMs on various high-impact Common Vulnerabilities and Exposures (CVEs). The results indicate that LLMs can significantly improve the efficiency of vulnerability analysis, although challenges remain, particularly with complex vulnerabilities. The guide emphasizes the importance of ongoing research to refine methodologies and improve the reliability of LLMs in this critical area of offensive security.