LLM framework automates vulnerability analysis reports

Researchers have developed RAVEN, a framework that uses Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) to automatically create detailed vulnerability analysis reports. RAVEN synthesizes reports based on vulnerable source code, following the Google Project Zero Root Cause Analysis template. The system includes agents for exploration, knowledge retrieval, impact assessment, and report generation, along with an LLM Judge for quality evaluation. Initial testing on 105 code samples showed an average quality score of 54.21%. AI

IMPACT Automates the generation of detailed vulnerability reports, potentially speeding up security analysis and documentation.

RANK_REASON The cluster contains a research paper detailing a novel framework for vulnerability analysis using LLMs and RAG. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• Google Project Zero
• Large Language Models
• NIST-SARD
• Parteek Jamwal
• RAVEN
• Retrieval Augmented Generation

• paper
• safety

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