  Software vulnerabilities pose critical security and risk concerns for many
software systems. Many techniques have been proposed to effectively assess and
prioritize these vulnerabilities before they cause serious consequences. To
evaluate their performance, these solutions often craft their own experimental
datasets from limited information sources, such as MITRE CVE and NVD, lacking a
global overview of broad vulnerability intelligence. The repetitive data
preparation process further complicates the verification and comparison of new
solutions. To resolve this issue, in this paper, we propose VulZoo, a
comprehensive vulnerability intelligence dataset that covers 17 popular
vulnerability information sources. We also construct connections among these
sources, enabling more straightforward configuration and adaptation for
different vulnerability assessment tasks (e.g., vulnerability type prediction).
Additionally, 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 to
facilitate future research. We believe that VulZoo serves as a valuable input
to vulnerability assessment and prioritization studies. The dataset with
utility scripts is available at https://github.com/NUS-Curiosity/VulZoo.
