Automated Attack Synthesis for Constant Product Market Makers
<|reference_start|>Automated Attack Synthesis for Constant Product Market Makers: Decentralized Finance enables many novel applications that were impossible in traditional finances. However, it also introduces new types of vulnerabilities, such as composability bugs. The composability bugs refer to issues that lead to erroneous behaviors when multiple smart contracts operate together. One typical example of composability bugs is those between token contracts and Constant Product Market Makers (CPMM), the most widely used model for Decentralized Exchanges. Since 2022, 23 exploits of such kind have resulted in a total loss of 2.2M USD. BlockSec, a smart contract auditing company, once reported that 138 exploits of such kind occurred just in February 2023. We propose CPMM-Exploiter, which automatically detects and generates end-to-end exploits for CPMM composability bugs. Generating such end-to-end exploits is challenging due to the large search space of multiple contracts and various fees involved with financial services. To tackle this, we investigated real-world exploits regarding these vulnerabilities and identified that they arise due to violating two safety invariants. Based on this observation, we implemented CPMM-Exploiter, a new grammar-based fuzzer targeting the detection of these bugs. CPMM-Exploiter uses fuzzing to find transactions that break the invariants. It then refines these transactions to make them profitable for the attacker. We evaluated CPMM-Exploiter on two real-world exploit datasets. CPMM-Exploiter obtained recalls of 0.91 and 0.89, respectively, while five baselines achieved maximum recalls of 0.36 and 0.58, respectively. We further evaluated CPMM-Exploiter by running it on the latest blocks of the Ethereum and Binance networks. It successfully generated 18 new exploits, which can result in 12.9K USD profit in total.<|reference_end|>
@article{han2024automated,
    title={Automated Attack Synthesis for Constant Product Market Makers},
    author={Sujin Han, Jinseo Kim, Sung-Ju Lee, Insu Yun},
    journal={arXiv preprint arXiv:2404.05297},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.05297},
    primaryClass={cs.CR cs.SE}
}