Year: 2025
Type: article
Abstract: The Web3 ecosystem is increasingly evolving to include multiple chains, with decentralized applications (dApps) distributed across different blockchains. This has driven the need for cross-chain bridges to enable blockchain interoperability. However, this opens up novel attack surface, and media outlets have reported serious attacks related to cross-chain bridges. Nevertheless, few prior works have studied cross-chain bridges and their related transactions, especially from a security perspective. To fill the void, this paper presents the first comprehensive analysis of cross-chain transactions. We first build a cross-chain transaction dataset based on semantic analysis of popular cross-chain bridges, covering 13 decentralized bridges and 7 representative blockchains, with over 80 million transactions in total. Based on this comprehensive dataset, we study the landscape of cross-chain transactions from several angles, including token usage, user profile and the purposes of transactions. We further observe that cross-chain bridges can be abused for malicious/aggressive purposes. Thus we design an automated detector and deploy it in-the-wild to flag misbehaviors from millions of cross-chain transactions. We identify hundreds of abnormal transactions related to exploits and arbitrages, etc. Our research underscores the importance of the cross-chain ecosystem, and offers an effective detector for pinpointing security threats.
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4411411480