Security Patch

Security patch detection and tracing are crucial for mitigating software vulnerabilities, yet identifying patches remains challenging due to inconsistent reporting practices and the sheer volume of code changes. Current research focuses on automated methods, employing techniques like large language models (LLMs) to analyze vulnerability reports and code commits, and leveraging both code-based and behavioral data (e.g., commit patterns) to identify patches even without explicit vulnerability disclosures. These advancements improve the efficiency and accuracy of patch identification, ultimately enhancing software security and reducing the risk of exploitation.