Ret2BERT is a tool designed to identify potential vulnerabilities in C programming, which hackers might exploit for attacks. By combining artificial intelligence (natural language processing) with cybersecurity expertise, it can intelligently analyze code to help developers and cybersecurity researchers detect issues more quickly and accurately, thereby enhancing software security.
The design philosophy of Ret2BERT is to leverage AI and deep learning to replace traditional analysis methods for vulnerability detection. Currently, Ret2BERT utilizes synthetic datasets generated by LLMs (such as ChatGPT) and fine-tunes them based on CodeBERT. CodeBERT, a state-of-the-art (SOTA) language model built on the Transformer architecture, captures semantic and syntactic information in code, supporting vulnerability analysis and detection.