DAppSCAN: Building Large-Scale Datasets for Smart Contract Weaknesses in DApp Projects
Auteurs : Zibin Zheng, Jianzhong Su, Jiachi Chen, David Lo, Zhijie Zhong, Mingxi Ye
Résumé : The Smart Contract Weakness Classification Registry (SWC Registry) is a widely recognized list of smart contract weaknesses specific to the Ethereum platform. In recent years, significant research efforts have been dedicated to building tools to detect SWC weaknesses. However, evaluating these tools has proven challenging due to the absence of a large, unbiased, real-world dataset. To address this issue, we recruited 22 participants and spent 44 person-months analyzing 1,322 open-source audit reports from 30 security teams. In total, we identified 10,016 weaknesses and developed two distinct datasets, i.e., DAppSCAN-Source and DAppSCAN-Bytecode. The DAppSCAN-Source dataset comprises 25,077 Solidity files, featuring 1,689 SWC vulnerabilities sourced from 1,139 real-world DApp projects. The Solidity files in this dataset may not be directly compilable. To enable the dataset to be compilable, we developed a tool capable of automatically identifying dependency relationships within DApps and completing missing public libraries. By utilizing this tool, we created our DAPPSCAN-Bytecode dataset, which consists of 8,167 compiled smart contract bytecode with 895 SWC weaknesses. Based on the second dataset, we conducted an empirical study to assess the performance of five state-of-the-art smart contract vulnerability detection tools. The evaluation results revealed subpar performance for these tools in terms of both effectiveness and success detection rate, indicating that future development should prioritize real-world datasets over simplistic toy contracts.
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