mlsanityData to 7 Oct 2026

VulCurator: A Vulnerability-Fixing Commit Detector

arXiv 2209.03260 ↗First posted 7 Sep 2022cs.CR cs.AI cs.SEcited by 11

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Abstract (arXiv)

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.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 9 of its 27 references that are in the map. First posted on arXiv 7 Sep 2022.

Builds on

9 of 27 references.

References · 9

  1. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  2. 2016"Why Should I Trust You?": Explaining the Predictions of Any Classifiercited by 5,040
  3. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  4. 2020CodeBERT: A Pre-Trained Model for Programming and Natural Languagescited by 1,286
  5. 2021Applying CodeBERT for Automated Program Repair of Java Simple Bugscited by 44
  6. 2021SPI: Automated Identification of Security Patches via Commitscited by 19
  7. 2018A Practical Approach to the Automatic Classification of Security-Relevant Commitscited by 13
  8. 2021DeepCVA: Automated Commit-level Vulnerability Assessment with Deep Multi-task Learningcited by 11
  9. 2020Learning to Catch Security Patchescited by 6

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 4; 2025: 4; 2026: 1.

11 papers.