Source Code Vulnerability

Source code vulnerabilities, unintentional flaws in software code that can be exploited by cyberattacks, are a major research focus due to their significant security implications. Current research emphasizes automated detection methods, employing techniques like Large Language Models (LLMs), graph neural networks (GNNs), and various machine learning algorithms to analyze code structure and identify vulnerabilities, often using intermediate representations like LLVM IR. These efforts aim to improve the accuracy and efficiency of vulnerability detection, reducing the reliance on manual code review and ultimately enhancing software security. Improved datasets and refined code processing techniques are also key areas of ongoing development.