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TxPhishScope: Towards Detecting and Understanding Transaction-based Phishing on Ethereum

Bowen He, Yuan Chen, Zhuo Chen, Xiaohui Hu, Yufeng Hu, Lei Wu, Rui Chang, Haoyu Wang, Yajin Zhou

2023Year
38Citations
7Top-tier citations

Abstract

The prosperity of Ethereum attracts many users to send transactions and trade crypto assets. However, this has also given rise to a new form of transaction-based phishing scam, named TxPhish. Specifically, tempted by high profits, users are tricked into visiting fake websites and signing transactions that enable scammers to steal their crypto assets. The past year has witnessed 11 large-scale TxPhish incidents causing a total loss of more than $70 million.

In this paper, we conduct the first empirical study of TxPhish on Ethereum, encompassing the process of a TxPhish campaign and details of phishing transactions. To detect TxPhish websites and extract phishing accounts automatically, we present TxPhishScope, which dynamically visits the suspicious websites, triggers transactions, and simulates results. Between November 25, 2022, and July 31, 2023, we successfully detected and reported 26,333 TxPhish websites and 3,486 phishing accounts. Among all of documented TxPhish websites, 78.9% of them were first reported by us, making TxPhishScope the largest TxPhish website detection system. Moreover, we provided criminal evidence of four phishing accounts and their fund flow totaling $1.5 million to aid in the recovery of funds * Part of the work was finished when the authors were research interns at BlockSec.

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