Efficiently Detecting Reentrancy Vulnerabilities in Complex Smart Contracts
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866914718024728576 |
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| author | Wang, Zexu Chen, Jiachi Wang, Yanlin Zhang, Yu Zhang, Weizhe Zheng, Zibin |
| author_facet | Wang, Zexu Chen, Jiachi Wang, Yanlin Zhang, Yu Zhang, Weizhe Zheng, Zibin |
| contents | Reentrancy vulnerability as one of the most notorious vulnerabilities, has been a prominent topic in smart contract security research. Research shows that existing vulnerability detection presents a range of challenges, especially as smart contracts continue to increase in complexity. Existing tools perform poorly in terms of efficiency and successful detection rates for vulnerabilities in complex contracts. To effectively detect reentrancy vulnerabilities in contracts with complex logic, we propose a tool named SliSE. SliSE's detection process consists of two stages: Warning Search and Symbolic Execution Verification. In Stage I, SliSE utilizes program slicing to analyze the Inter-contract Program Dependency Graph (I-PDG) of the contract, and collects suspicious vulnerability information as warnings. In Stage II, symbolic execution is employed to verify the reachability of these warnings, thereby enhancing vulnerability detection accuracy. SliSE obtained the best performance compared with eight state-of-the-art detection tools. It achieved an F1 score of 78.65%, surpassing the highest score recorded by an existing tool of 9.26%. Additionally, it attained a recall rate exceeding 90% for detection of contracts on Ethereum. Overall, SliSE provides a robust and efficient method for detection of Reentrancy vulnerabilities for complex contracts. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_11254 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Efficiently Detecting Reentrancy Vulnerabilities in Complex Smart Contracts Wang, Zexu Chen, Jiachi Wang, Yanlin Zhang, Yu Zhang, Weizhe Zheng, Zibin Software Engineering Reentrancy vulnerability as one of the most notorious vulnerabilities, has been a prominent topic in smart contract security research. Research shows that existing vulnerability detection presents a range of challenges, especially as smart contracts continue to increase in complexity. Existing tools perform poorly in terms of efficiency and successful detection rates for vulnerabilities in complex contracts. To effectively detect reentrancy vulnerabilities in contracts with complex logic, we propose a tool named SliSE. SliSE's detection process consists of two stages: Warning Search and Symbolic Execution Verification. In Stage I, SliSE utilizes program slicing to analyze the Inter-contract Program Dependency Graph (I-PDG) of the contract, and collects suspicious vulnerability information as warnings. In Stage II, symbolic execution is employed to verify the reachability of these warnings, thereby enhancing vulnerability detection accuracy. SliSE obtained the best performance compared with eight state-of-the-art detection tools. It achieved an F1 score of 78.65%, surpassing the highest score recorded by an existing tool of 9.26%. Additionally, it attained a recall rate exceeding 90% for detection of contracts on Ethereum. Overall, SliSE provides a robust and efficient method for detection of Reentrancy vulnerabilities for complex contracts. |
| title | Efficiently Detecting Reentrancy Vulnerabilities in Complex Smart Contracts |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2403.11254 |