一句话：构建智能合约安全审计报告聚合、解析与查询的数据集与工具，支持大规模漏洞实证研究。
智能合约安全审计报告包含丰富的漏洞与代码质量信息，但分散在不同来源和格式中，难以进行大规模分析。本文提出 SCAR（Smart Contract Audit Repository），一个开源数据集与工具，可自动聚合并结构化这些审计报告。SCAR 爬取领先安全公司（如 OpenZeppelin）和社区竞赛（如 Code4rena）的报告，将其解析为结构化 JSON schema，并提供可查询 API。其流水线包括爬虫、文本挖掘模块和 Web API，其中文本挖掘模块用于标准化发现，如漏洞类型、严重性和代码引用。SCAR 已收录数百份审计、覆盖数千个问题，支持对智能合约漏洞进行大规模实证研究。项目仓库已在 GitHub 开源，并提供演示视频。
Smart contract security audit reports contain rich information about vulnerabilities and code quality issues in Web3 projects. However, these reports are scattered across different sources and formats, making large-scale analysis difficult. We present SCAR (Smart Contract Audit Repository), an open-source dataset and tool that automatically aggregates these audit reports. SCAR crawls reports from leading security firms (e.g., OpenZeppelin) and community contests (e.g., Code4rena), parses them into a structured JSON schema, and offers a queryable API for accessing the data. Its pipeline includes a crawler, a text-mining module to standardize findings (e.g., vulnerability types, severity, code references), and a web API for retrieving insights. With hundreds of audits covering thousands of issues, SCAR enables empirical studies of smart contract vulnerabilities at scale. The SCAR project repository is available on GitHub, and the screencast demo is available at this link.