ASE2024
AdvSCanner: Generating Adversarial Smart Contracts to Exploit Reentrancy Vulnerabilities Using LLM and Static Analysis
Yin Wu, Xiaofei Xie, Chenyang Peng, Dijun Liu, Hao Wu, Ming Fan, Ting Liu, Haijun Wang
9 citations
Abstract
Smart contracts are prone to vulnerabilities, with reentrancy attacks posing significant risks due to their destructive potential. While various methods exist for detecting reentrancy vulnerabilities in smart contracts, such as static analysis, these approaches often suffer from high false positive rates and lack the ability to directly illustrate how vulnerabilities can be exploited in attacks.