1 citations · 1 across the 3 of their papers we have counts for
4 papers
LogicScan: An LLM-driven Framework for Detecting Business Logic Vulnerabilities in Smart Contracts
Jiaqi Gao, Zijian Zhang, Yuqiang Sun +5
Business logic vulnerabilities have become one of the most damaging yet least understood classes of smart contract vulnerabilities. Unlike traditional bugs such as reentrancy or ar…
Towards Secure Program Partitioning for Smart Contracts with LLM's In-Context Learning
Ye Liu, Yuqing Niu, Chengyan Ma +5
Smart contracts are highly susceptible to manipulation attacks due to the leakage of sensitive information. Addressing manipulation vulnerabilities is particularly challenging beca…
Phantom Events: Demystifying the Issues of Log Forgery in Blockchain
Yixuan Liu, Yuxin Dong, Ye Liu +2
With the rapid development of blockchain technology, transaction logs play a central role in various applications, including decentralized exchanges, wallets, cross-chain bridges,…
Detecting Various DeFi Price Manipulations with LLM Reasoning
Juantao Zhong, Daoyuan Wu, Ye Liu +4
DeFi (Decentralized Finance) is one of the most important applications of today's cryptocurrencies and smart contracts. It manages hundreds of billions in Total Value Locked (TVL)…