KVS: a tool for knowledge-driven vulnerability searching

Xingqi Cheng, Xiaobing Sun, Lili Bo, Ying Wei

Abstract

It is difficult to quickly locate and search for specific vulnerabilities and their solutions because vulnerability information is scattered in the existing vulnerability management library. To alleviate this problem, we extract knowledge from vulnerability reports and organize the vulnerability information into the form of a knowledge graph. Then, we implement a tool for knowledge-driven vulnerability searching, KVS. This tool mainly uses the BERT model to realize the vulnerability named entity recognition and construct the vulnerability knowledge graph (VulKG). Finally, we can search vulnerabilities of interest-based on VulKG. The URL of this tool is https://cinnqi.github.io/Neo4j-D3-VKG/. Video of our demo is available at https://youtu.be/FT1BaLUGPk0.

BibTeX

@inproceedings{Cheng-al:FSE22,
  author    = {Xingqi Cheng and
               Xiaobing Sun and
               Lili Bo and
               Ying Wei},
  title     = {{KVS:} a tool for knowledge-driven vulnerability searching},
  booktitle = {{ESEC/SIGSOFT} {FSE}},
  pages     = {1731--1735},
  publisher = {{ACM}},
  year      = {2022},
}

KVS: a tool for knowledge-driven vulnerability searching

Abstract

Related papers