pith. sign in

arxiv: 2209.03260 · v1 · pith:PJNMITHDnew · submitted 2022-09-07 · 💻 cs.CR · cs.AI· cs.SE

VulCurator: A Vulnerability-Fixing Commit Detector

classification 💻 cs.CR cs.AIcs.SE
keywords vulnerability-fixingcommitslearningvulcuratorcommitdeephttpsinformation
0
0 comments X
read the original abstract

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.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.