一句话：提出通过识别攻击者合约来检测可利用的智能合约重入漏洞，以降低现有工具的高误报率。
智能合约中的重入漏洞已造成数百万美元经济损失。然而现有智能合约漏洞检测工具在识别含重入漏洞的合约时误报率较高，而且检测出的重入合约中只有一小部分可被攻击者实际利用，导致这些工具在保护以太坊生态的实践中效果有限。该论文关注预谋攻击中的可利用重入漏洞，提出通过识别攻击者合约来检测此类漏洞，从而将检测重点从普通重入模式转向可实际利用的攻击场景。摘要未报告具体方法细节与定量评估结果，但其目标是减少误报并提升智能合约安全检测的实用性。
Reentrancy, a notorious vulnerability in smart contracts, has led to millions of dollars in financial loss. However, current smart contract vulnerability detection tools suffer from a high false positive rate in identifying contracts with reentrancy vulnerabilities. Moreover, only a small portion of the detected reentrant contracts can actually be exploited by hackers, making these tools less effective in securing the Ethereum ecosystem in practice.
@inproceedings{paperbot11420,
title = {Uncover the Premeditated Attacks: Detecting Exploitable Reentrancy Vulnerabilities by Identifying Attacker Contracts},
author = {Shuo Yang and Jiachi Chen and Mingyuan Huang and Zibin Zheng and Yuan Huang},
booktitle = {ICSE},
year = {2024},
doi = {10.1145/3597503.3639153}
}