Towards Understanding Crypto Money Laundering in Web3 Through the Lenses of Ethereum Heists

TL;DR

This paper investigates crypto money laundering behaviors in the Web3 ecosystem, focusing on Ethereum, by analyzing transaction networks and account characteristics to identify laundering methods and inform anti-money laundering strategies.

Contribution

It introduces a systematic approach to identify untagged laundering groups in Ethereum using heuristic transaction tracking, filling a knowledge gap in Web3 crypto laundering research.

Findings

Escalating laundering methods like counterfeit tokens and masquerading as speculators.

Identification of untagged laundering groups through heuristic transaction analysis.

Insights into behavioral patterns of laundering accounts in Ethereum.

Abstract

With the overall momentum of the blockchain industry, crypto-based crimes are becoming more and more prevalent. After committing a crime, the main goal of cybercriminals is to obfuscate the source of the illicit funds in order to convert them into cash and get away with it. Many studies have analyzed money laundering in the field of the traditional financial sector and blockchain-based Bitcoin. But so far, little is known about the characteristics of crypto money laundering in the blockchain-based Web3 ecosystem. To fill this gap, and considering that Ethereum is the largest platform on Web3, in this paper, we systematically study the behavioral characteristics and economic impact of money laundering accounts through the lenses of Ethereum heists. Based on a very small number of tagged accounts of exchange hackers, DeFi exploiters, and scammers, we mine untagged money laundering groups through heuristic transaction tracking methods, to carve out a full picture of security incidents. By analyzing account characteristics and transaction networks, we obtain many interesting findings about crypto money laundering in Web3, observing the escalating money laundering methods such as creating counterfeit tokens and masquerading as speculators. Finally, based on these findings we provide inspiration for anti-money laundering to promote the healthy development of the Web3 ecosystem.