Phantom Events: Demystifying the Issues of Log Forgery in Blockchain

TL;DR

This paper analyzes the security vulnerabilities of transaction logs in EVM-based blockchains, introduces Phantom Events as a new threat, and presents a detection tool that outperforms existing solutions, revealing real-world attack instances.

Contribution

It provides the first comprehensive security analysis of log forgery in EVM blockchains, models attack types, and develops a detection tool that identifies vulnerabilities more effectively.

Findings

Identified five attack types of log forgery in EVM blockchains.

Developed a tool that outperforms existing methods in detecting phantom events.

Discovered real-world instances of log forgery across multiple decentralized applications.

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.