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Efficiently Detecting Reentrancy Vulnerabilities in Complex Smart Contracts

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arxiv 2403.11254 v1 pith:NRFRZPK4 submitted 2024-03-17 cs.SE

classification cs.SE
keywords detectioncontractsslisevulnerabilitiescomplexreentrancyvulnerabilityexisting
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. The Dark Side of Upgrades: Uncovering Security Risks in Smart Contract Upgrades

    cs.CR 2025-08 unverdicted novelty 7.0 of 10

    A large-scale study of upgraded smart contracts finds eight upgrade-related risk types, four of which are publicly overlooked and unmitigated, and reports 31,407 detected issue instances.

  2. Building Reuse-Sensitive Control Flow Graphs (CFGs) for EVM Bytecode

    cs.SE 2025-05 conditional novelty 7.0 of 10

    Esuer constructs reuse-sensitive CFGs for EVM bytecode by tainting pre-pushed jump operands and cloning reused basic blocks, improving precision and downstream vulnerability detection.

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