ACOFuzz: An ant colony algorithm-based fuzzer for smart contracts

In today's blockchain landscape, smart contracts are assuming a pivotal role, albeit accompanied by a heightened risk of exploitation by attackers. As smart contracts grow in complexity, vulnerabilities lurking within deeper layers of code become more prevalent. Existing analysis tools primaril...

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Published inBlockchain. Research and applications Online Vol. 6; no. 3; p. 100279
Main Authors Feng, Peixuan, Cao, Wenrui, Lu, Siqi, Wang, Yongjuan, Xue, Haoyuan, Yang, Runnan
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.09.2025
Elsevier
Subjects
Online AccessGet full text
ISSN2096-7209
2666-9536
2666-9536
DOI10.1016/j.bcra.2025.100279

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Abstract In today's blockchain landscape, smart contracts are assuming a pivotal role, albeit accompanied by a heightened risk of exploitation by attackers. As smart contracts grow in complexity, vulnerabilities lurking within deeper layers of code become more prevalent. Existing analysis tools primarily focus on data flow and a priori knowledge based on symbolic execution as a test case generation strategy, often falling short in uncovering vulnerabilities nested within intricate conditional statements. To address this challenge, we present ACOFuzz, an advanced fuzzer for Ethereum smart contracts. ACOFuzz employs the ant colony optimization (ACO) algorithm to traverse the control flow graph (CFG) of smart contracts, systematically exploring execution paths and generating test cases. Subsequently, it strategically directs the search towards paths that are more susceptible to vulnerabilities within the CFG, leveraging block coverage data obtained from executing the test cases. In a comprehensive evaluation, we demonstrate that ACOFuzz excels in covering a wider array of paths within a contract while exhibiting enhanced accuracy in pinpointing specific vulnerabilities compared to contemporary fuzzers.
AbstractList In today's blockchain landscape, smart contracts are assuming a pivotal role, albeit accompanied by a heightened risk of exploitation by attackers. As smart contracts grow in complexity, vulnerabilities lurking within deeper layers of code become more prevalent. Existing analysis tools primarily focus on data flow and a priori knowledge based on symbolic execution as a test case generation strategy, often falling short in uncovering vulnerabilities nested within intricate conditional statements. To address this challenge, we present ACOFuzz, an advanced fuzzer for Ethereum smart contracts. ACOFuzz employs the ant colony optimization (ACO) algorithm to traverse the control flow graph (CFG) of smart contracts, systematically exploring execution paths and generating test cases. Subsequently, it strategically directs the search towards paths that are more susceptible to vulnerabilities within the CFG, leveraging block coverage data obtained from executing the test cases. In a comprehensive evaluation, we demonstrate that ACOFuzz excels in covering a wider array of paths within a contract while exhibiting enhanced accuracy in pinpointing specific vulnerabilities compared to contemporary fuzzers.
ArticleNumber 100279
Author Lu, Siqi
Yang, Runnan
Wang, Yongjuan
Cao, Wenrui
Feng, Peixuan
Xue, Haoyuan
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  organization: Henan Armed Police Corps Hospital, Zhengzhou 450000, China
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Snippet In today's blockchain landscape, smart contracts are assuming a pivotal role, albeit accompanied by a heightened risk of exploitation by attackers. As smart...
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Index Database
Publisher
StartPage 100279
SubjectTerms Ant colony optimization
Fuzz testing
Smart contract
Test case
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Title ACOFuzz: An ant colony algorithm-based fuzzer for smart contracts
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