VulZoo: A Comprehensive Vulnerability Intelligence Dataset

Bonan Ruan, Jiahao Liu, Weibo Zhao, Zhenkai Liang

Abstract: Software vulnerabilities pose critical security and risk concerns. Many techniques are proposed to assess and prioritize vulnerabilities. To evaluate their performance, researchers often craft datasets from limited data sources, lacking a global overview of broad vulnerability intelligence. The repetitive data preparation process complicates the evaluation of new solutions. To solve this issue, we propose VulZoo, a comprehensive vulnerability intelligence dataset that covers 17 vulnerability data sources. We also construct connections among these sources, enabling more straightforward configuration and adaptation for different tasks. VulZoo provides utility scripts for automatic data synchronization and cleaning, relationship mining, and statistics generation. We make VulZoo publicly available and maintain it with incremental updates. We believe that VulZoo serves as a valuable input to vulnerability assessment and prioritization studies. The video is at https://youtu.be/EvoxQmUAHtw. The dataset is at https://github.com/NUS-Curiosity/VulZoo.