FairChecker: Detecting Fund-Stealing Bugs in DeFi Protocols via Fairness Validation

Decentralized Finance (DeFi) is an emerging paradigm within the blockchain space that aims to revolutionize conventional financial systems by applying blockchain technology. The substantial value of digital assets managed by DeFi protocols makes it a lucrative target for attacks. Despite the human resources and the application of automated tools, frequent attacks still cause significant fund losses to DeFi participants. Existing tools primarily rely on oracles similar to those used in traditional software analysis, making it challenging for them to detect functional bugs specific to the DeFi domain. Since blockchain functions as a distributed ledger system, the foundation of any DeFi protocol is the accurate maintenance of key state variables representing user funds. If these variables are not properly updated or designed to reflect the intended flow of funds, attackers can exploit these flaws to steal assets. From the study of popular DeFi protocols, we observe that, in DeFi systems, to ensure a transaction does not misappropriate someone's fund, the direction of changes (increase or decrease) of values associated with the amount of asset or debt of a user has to adhere to some fairness properties. We propose a concept called fairness bug which allows attackers to gain profit without cost. We propose an inter-procedural and inter-contract static analysis technique that utilizes symbolic execution and an SMT solver to automatically detect fairness bugs in DeFi smart contracts. We have implemented our fairness-checking approach in our tool, named FairChecker. We evaluate our tool on a benchmark of 113 real-world DeFi protocols with 34 fairness bugs. The results show that our tool can detect 32 bugs with a recall of 94.1 % and a precision of 46.4 %, demonstrating its effectiveness.

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Publication Details

Published
2025-04-26
DOI
https://doi.org/10.1109/icse55347.2025.00134
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00
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article

FairChecker: Detecting Fund-Stealing Bugs in DeFi Protocols via Fairness Validation

Yi Sun, Xiangyu Zhang, Zhuo Zhang
Blockchain Technology Applications and Security
article

FairChecker: Detecting Fund-Stealing Bugs in DeFi Protocols via Fairness Validation

Yi Sun, Xiangyu Zhang, Zhuo Zhang
article en

Abstract

Decentralized Finance (DeFi) is an emerging paradigm within the blockchain space that aims to revolutionize conventional financial systems by applying blockchain technology. The substantial value of digital assets managed by DeFi protocols makes it a lucrative target for attacks. Despite the human resources and the application of automated tools, frequent attacks still cause significant fund losses to DeFi participants. Existing tools primarily rely on oracles similar to those used in traditional software analysis, making it challenging for them to detect functional bugs specific to the DeFi domain. Since blockchain functions as a distributed ledger system, the foundation of any DeFi protocol is the accurate maintenance of key state variables representing user funds. If these variables are not properly updated or designed to reflect the intended flow of funds, attackers can exploit these flaws to steal assets. From the study of popular DeFi protocols, we observe that, in DeFi systems, to ensure a transaction does not misappropriate someone's fund, the direction of changes (increase or decrease) of values associated with the amount of asset or debt of a user has to adhere to some fairness properties. We propose a concept called fairness bug which allows attackers to gain profit without cost. We propose an inter-procedural and inter-contract static analysis technique that utilizes symbolic execution and an SMT solver to automatically detect fairness bugs in DeFi smart contracts. We have implemented our fairness-checking approach in our tool, named FairChecker. We evaluate our tool on a benchmark of 113 real-world DeFi protocols with 34 fairness bugs. The results show that our tool can detect 32 bugs with a recall of 94.1 % and a precision of 46.4 %, demonstrating its effectiveness.

Purdue University West Lafayette (US)
Openalex Percentile: Top 79%
Blockchain Technology Applications and Security
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