Enhancing Smart Contract Security Analysis with Execution Property Graphs

Smart contract vulnerabilities have led to significant financial losses, with their increasing complexity rendering outright prevention of hacks increasingly challenging. This trend highlights the crucial need for advanced forensic analysis and real-time intrusion detection, where dynamic analysis plays a key role in dissecting smart contract executions. Therefore, there is a pressing need for a unified and generic representation of smart contract executions, complemented by an efficient methodology that enables the modeling and identification of a broad spectrum of emerging attacks. We introduce Clue, a dynamic analysis framework specifically designed for the Ethereum virtual machine. Central to Clue is its ability to capture critical runtime information during contract executions, employing a novel graph-based representation, the Execution Property Graph. A key feature of Clue is its innovative graph traversal technique, which is adept at detecting complex attacks, including (read-only) reentrancy and price manipulation. Evaluation results reveal Clue's superior performance with high true positive rates and low false positive rates, outperforming state-of-the-art tools. Furthermore, Clue's efficiency positions it as a valuable tool for both forensic analysis and real-time intrusion detection.

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Publication Details

Journal
Proceedings of the ACM on software engineering.
Published
2025-06-22
DOI
https://doi.org/10.1145/3728924
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
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article

Enhancing Smart Contract Security Analysis with Execution Property Graphs

哲 田野, Dawn Song, Liyi Zhou, Kaihua Qin et al.
Proceedings of the ACM on software engineering.
Blockchain Technology Applications and Security
article

Enhancing Smart Contract Security Analysis with Execution Property Graphs

哲 田野, Dawn Song, Liyi Zhou, Kaihua Qin, Arthur Gervais, Zhun Wang, Chao Zhang, W. D. Li
article en

Abstract

Smart contract vulnerabilities have led to significant financial losses, with their increasing complexity rendering outright prevention of hacks increasingly challenging. This trend highlights the crucial need for advanced forensic analysis and real-time intrusion detection, where dynamic analysis plays a key role in dissecting smart contract executions. Therefore, there is a pressing need for a unified and generic representation of smart contract executions, complemented by an efficient methodology that enables the modeling and identification of a broad spectrum of emerging attacks. We introduce Clue, a dynamic analysis framework specifically designed for the Ethereum virtual machine. Central to Clue is its ability to capture critical runtime information during contract executions, employing a novel graph-based representation, the Execution Property Graph. A key feature of Clue is its innovative graph traversal technique, which is adept at detecting complex attacks, including (read-only) reentrancy and price manipulation. Evaluation results reveal Clue's superior performance with high true positive rates and low false positive rates, outperforming state-of-the-art tools. Furthermore, Clue's efficiency positions it as a valuable tool for both forensic analysis and real-time intrusion detection.

Proceedings of the ACM on software engineering.Vol. 2(ISSTA)
The University of Sydney (AU), Yale University (US), University College London (GB), University of California, Berkeley (US), Tsinghua University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 79%
Blockchain Technology Applications and Security
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Enhancing Smart Contract Security Analysis with Execution Property Graphs — 哲 田野, Dawn Song, et al. · Proceedings of the ACM on software engineering. (2025) | TGRS Research Map | TGRS