VulCurator: A Vulnerability-Fixing Commit Detector
Nguyen, Truong Giang, Le-Cong, Thanh, Kang, Hong Jin, Le, Xuan-Bach D., Lo, David
–arXiv.org Artificial Intelligence
Open-source software (OSS) vulnerability management process is important nowadays, as the number of discovered OSS vulnerabilities is increasing over time. Monitoring vulnerability-fixing commits is a part of the standard process to prevent vulnerability exploitation. Manually detecting vulnerability-fixing commits is, however, time consuming due to the possibly large number of commits to review. Recently, many techniques have been proposed to automatically detect vulnerability-fixing commits using machine learning. These solutions either: (1) did not use deep learning, or (2) use deep learning on only limited sources of information. This paper proposes VulCurator, a tool that leverages deep learning on richer sources of information, including commit messages, code changes and issue reports for vulnerability-fixing commit classifica- tion. Our experimental results show that VulCurator outperforms the state-of-the-art baselines up to 16.1% in terms of F1-score. VulCurator tool is publicly available at https://github.com/ntgiang71096/VFDetector and https://zenodo.org/record/7034132#.Yw3MN-xBzDI, with a demo video at https://youtu.be/uMlFmWSJYOE.
arXiv.org Artificial Intelligence
Sep-7-2022
- Country:
- North America > United States (0.46)
- Oceania > Australia (0.28)
- Genre:
- Research Report > New Finding (0.66)
- Industry:
- Information Technology > Security & Privacy (1.00)
- Technology: