Vulnerable Code

Vulnerable code research focuses on automatically identifying and repairing security flaws in software, aiming to improve software security and reduce the burden on developers. Current research heavily utilizes large language models (LLMs), often incorporating techniques like prompt tuning, multi-agent frameworks, and reinforcement learning with semantic rewards, to enhance vulnerability detection and code repair capabilities. These advancements are significant because they offer the potential for more efficient and effective automated security analysis and remediation, ultimately leading to more secure software systems.