Uncovering Hidden Proxy Smart Contracts for Finding Collision Vulnerabilities in Ethereum
Paper i proceeding, 2025

The proxy design pattern allows Ethereum smart contracts to be simultaneously immutable and upgradeable, in which an original contract is split into a proxy contract containing the data storage and a logic contract containing the implementation logic. This architecture is known to have security issues, namely function collisions and storage collisions between the proxy and logic contracts, and has been exploited in real-world incidents to steal users' millions of dollars worth of digital assets. In response to this concern, several previous works have sought to identify proxy contracts in Ethereum and detect their collisions. However, they all fell short due to their limited coverage, often restricting analysis to only contracts with available source code or past transactions.To bridge this gap, we present Proxion, an automated cross-contract analyzer that identifies all proxy smart contracts and their collisions in Ethereum. What sets Proxion apart is its ability to analyze hidden smart contracts that lack both source code and past transactions. Equipped with various techniques to enhance efficiency and accuracy, Proxion outperforms the state-of-the-art tools, notably identifying millions more proxy contracts and thousands of unreported collisions. We apply Proxion to analyze over 36 million alive contracts from 2015 to 2023, revealing that 54.2% of them are proxy contracts, and about 1.5 million contracts exhibit at least one collision issue.

dynamic contract analyzer

storage collision

ethereum blockchain

security analysis

function collision

proxy smart contract

Författare

Cheng Kang Chen

National Taiwan University

Wen Yi Chu

National Taiwan University

Muoi Tran

Chalmers, Data- och informationsteknik, Dator- och nätverkssystem

Göteborgs universitet

Laurent Vanbever

Eidgenössische Technische Hochschule Zürich (ETH)

Hsu Chun Hsiao

National Taiwan University

Proceedings - International Conference on Distributed Computing Systems

10636927 (ISSN) 25758411 (eISSN)

1099-1109
9798331517236 (ISBN)

45th IEEE International Conference on Distributed Computing Systems, ICDCS 2025
Glasgow, United Kingdom,

Ämneskategorier (SSIF 2025)

Datavetenskap (datalogi)

Datorsystem

DOI

10.1109/ICDCS63083.2025.00110

Mer information

Senast uppdaterat

2025-11-03