Of Degens and Defrauders: Using Open-Source Investigative Tools to Investigate Decentralized Finance Frauds and Money Laundering

Authors: Arianna Trozze, Toby Davies, Bennett Kleinberg

License: CC BY-NC-SA 4.0

Abstract: Fraud across the decentralized finance (DeFi) ecosystem is growing, with victims losing billions to DeFi scams every year. However, there is a disconnect between the reported value of these scams and associated legal prosecutions. We use open-source investigative tools to (1) triage Ethereum tokens extracted from the Ethereum blockchain for further investigation, (2) investigate potential frauds involving these tokens using on-chain data and token smart contract analysis, and (3) investigate the ways proceeds from these scams were subsequently laundered. The analysis enabled us to (1) identify a set of tokens meriting further investigation, (2) uncover transaction-based evidence of several rug pull and pump-and-dump schemes, and (3) identify their perpetrators' money laundering tactics and cash-out methods. The rug pulls were less sophisticated than anticipated, money laundering techniques were also rudimentary and many funds ended up at centralized exchanges. This study demonstrates how open-source investigative tools can extract transaction-based evidence that could be used in a court of law to prosecute DeFi frauds. Additionally, we investigate how these funds are subsequently laundered.

Submitted to arXiv on 01 Mar. 2023

Explore the paper tree

Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant

Also access our AI generated Summaries, or ask questions about this paper to our AI assistant.

Look for similar papers (in beta version)

By clicking on the button above, our algorithm will scan all papers in our database to find the closest based on the contents of the full papers and not just on metadata. Please note that it only works for papers that we have generated summaries for and you can rerun it from time to time to get a more accurate result while our database grows.