Year: 2025
Type: preprint
Abstract: With the rapid development of blockchain technology, transaction logs play a central role in various applications, including decentralized exchanges, wallets, cross-chain bridges, and other third-party services. However, these logs, particularly those based on smart contract events, are highly susceptible to manipulation and forgery, creating substantial security risks across the ecosystem. To address this issue, we present the first in-depth security analysis of transaction log forgery in EVM-based blockchains, a phenomenon we term Phantom Events. We systematically model five types of attacks and propose a tool designed to detect event forgery vulnerabilities in smart contracts. Our evaluation demonstrates that our approach outperforms existing tools in identifying potential phantom events. Furthermore, we have successfully identified real-world instances for all five types of attacks across multiple decentralized applications. Finally, we call on community developers to take proactive steps to address these critical security vulnerabilities.
Source: arXiv (Cornell University)
Authors: Liu, Yixuan, Dong, Yuxin, Liu, Ye, Luo, Xiapu, Li, Yi
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4407764306