  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.
