SoK：去中心化金融中地毯式抽款的原因、数据集和检测工具的综合分析
SoK: Comprehensive Analysis of Rug Pull Causes, Datasets, and Detection Tools in DeFi
AI总结：
本文系统分析了DeFi中地毯式抽款的根本原因，提出包含34个原因的分类法，评估并构建了更全面的数据集，同时指出现有检测工具与实际风险间存在显著差距。
摘要：
地毯式抽款对加密货币生态系统构成了严重威胁，导致了巨大的财务损失，并破坏了对去中心化金融（DeFi）项目的信任。随着新型地毯式抽款模式的出现，关于地毯式抽款的研究已经过时。为了填补这一空白，我们首先对文献综述进行了广泛分析，涵盖了学术和行业来源。通过审查关于地毯式抽款项目的现有学术文章和工业讨论，我们提出了一个包含34个根本原因的分类法，并引入了受行业来源启发的六个新类别：销毁、隐藏所有者、所有权转移、未验证合约、外部调用和虚假LP锁定。基于开发的分类法，我们评估了当前的地毯式抽款数据集，并探索了现有检测机制的有效性和局限性。我们的评估表明，记录了2,448个实例的现有数据集仅解决了34个根本原因中的7个，覆盖率仅为20%。这表明现有的开源数据集需要改进以研究地毯式抽款。作为回应，我们构建了一个包含2,360个实例的更全面的数据集，尽最大努力将覆盖率扩大到54%。此外，对14个检测工具的检查表明，它们可以识别34个根本原因中的25个，覆盖率为73.5%。现有工具无法覆盖九个根本原因（虚假LP锁定、隐藏费用、销毁代币、虚假资金转账、所有权转移、流动性池阻断、冻结账户、洗售交易和对冲）。我们的工作表明，当前的研究和检测工具与地毯式抽款的实际情况之间存在显著差距。
英文摘要：
Rug pulls pose a grave threat to the cryptocurrency ecosystem, leading to substantial financial loss and undermining trust in decentralized finance (DeFi) projects. With the emergence of new rug pull patterns, research on rug pull is out of state. To fill this gap, we first conducted an extensive analysis of the literature review, encompassing both scholarly and industry sources. By examining existing academic articles and industrial discussions on rug pull projects, we present a taxonomy inclusive of 34 root causes, introducing six new categories inspired by industry sources: burn, hidden owner, ownership transfer, unverified contract, external call, and fake LP lock. Based on the developed taxonomy, we evaluated current rug pull datasets and explored the effectiveness and limitations of existing detection mechanisms. Our evaluation indicates that the existing datasets, which document 2,448 instances, address only 7 of the 34 root causes, amounting to a mere 20% coverage. It indicates that existing open-source datasets need to be improved to study rug pulls. In response, we have constructed a more comprehensive dataset containing 2,360 instances, expanding the coverage to 54% with the best effort. In addition, the examination of 14 detection tools showed that they can identify 25 of the 34 root causes, achieving a coverage of 73.5%. There are nine root causes (Fake LP Lock, Hidden Fee, and Destroy Token, Fake Money Transfer, Ownership Transfer, Liquidity Pool Block, Freeze Account, Wash-Trading, Hedge) that the existing tools cannot cover. Our work indicates that there is a significant gap between current research and detection tools, and the actual situation of rug pulls.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
