Literature review on vulnerability detection using NLP technology
It provides a survey for researchers in software security, but it is incremental as it only summarizes prior work without introducing novel findings.
This paper reviews recent advancements in automated vulnerability detection by applying NLP technologies like CodeBERT to analyze source code, summarizing existing methods without presenting new experimental results.
Vulnerability detection has always been the most important task in the field of software security. With the development of technology, in the face of massive source code, automated analysis and detection of vulnerabilities has become a current research hotspot. For special text files such as source code, using some of the hottest NLP technologies to build models and realize the automatic analysis and detection of source code has become one of the most anticipated studies in the field of vulnerability detection. This article does a brief survey of some recent new documents and technologies, such as CodeBERT, and summarizes the previous technologies.