Commit-Level, Neural Vulnerability Detection and Assessment

Yi Li, Aashish Yadavally, Jiaxing Zhang, Shaohua Wang, Tien N. Nguyen

Abstract

Software Vulnerabilities (SVs) are security flaws that are exploitable in cyber-attacks. Delay in the detection and assessment of SVs might cause serious consequences due to the unknown impacts on the attacked systems. The state-of-the-art approaches have been proposed to work directly on the committed code changes for early detection. However, none of them could provide both commit-level vulnerability detection and assessment at once. Moreover, the assessment approaches still suffer low accuracy due to limited representations for code changes and surrounding contexts.

BibTeX

@inproceedings{Li-al:FSE23,
  author    = {Yi Li and
               Aashish Yadavally and
               Jiaxing Zhang and
               Shaohua Wang and
               Tien N. Nguyen},
  title     = {{Commit-Level,} Neural Vulnerability Detection and Assessment},
  booktitle = {{ESEC/SIGSOFT} {FSE}},
  pages     = {1024--1036},
  publisher = {{ACM}},
  year      = {2023},
}

Commit-Level, Neural Vulnerability Detection and Assessment

Abstract

Related papers