智能合约静态分析中的隐含约束实证研究

Tingting Yin, Chao Zhang, Yuandong Ni, Yixiong Wu, Taiyu Wong, Xiapu Luo, Zheming Li, Yu Guo
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引用次数: 0

摘要

智能合约通常与金融相关,这使它们成为有吸引力的攻击目标。已经开发了许多静态分析工具来促进合同审计过程,但并非所有工具都考虑到智能合约的两个特殊特征:(1)外部变量,如时间,受到现实世界因素的限制;(2)内部变量在执行之间持续存在。由于这些特性将隐式约束导入到契约中,因此它们会显著影响静态工具的性能,例如在可达性分析中导致错误并导致误报。本文从三个方面对隐式约束进行了系统的研究。首先,我们总结了智能合约中的隐式约束。其次,我们评估了这些约束对最先进的静态工具的影响。第三,我们提出了一种轻量级但有效的缓解方法ConSym来处理这些约束,并将其集成到OSIRIS中。评估结果表明,ConSym可以过滤掉96%的假阳性,减少三分之二的假阴性。
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An Empirical Study on Implicit Constraints in Smart Contract Static Analysis
Smart contracts are usually financial-related, which makes them attractive attack targets. Many static analysis tools have been developed to facilitate the contract audit process, but not all of them take account of two special features of smart contracts: (1) The external variables, like time, are constrained by real-world factors; (2) The internal variables persist between executions. Since these features import implicit constraints into contracts, they significantly affect the performance of static tools, such as causing errors in reachability analysis and resulting in false positives. In this paper, we conduct a systematic study on implicit constraints from three aspects. First, we summarize the implicit constraints in smart contracts. Second, we evaluate the impact of such constraints on the state-of-the-art static tools. Third, we propose a lightweight but effective mitigation method named ConSym to deal with such constraints and integrate it into OSIRIS. The evaluation result shows that ConSym can filter out 96% of false positives and reduce false negatives by two-thirds.
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