Abstract
DeFi has attracted legitimate investors and scammers alike. The paper presents an empirical investigation into the prevalence of rugpulls, a scam where cryptocurrency project developers exit without fully delivering and leave investors in the wind. Using forum data, 101 rugpulls from 6 different types of DeFi services are documented. ICOs form the majority of the rugpulls, most of which were active for less than six months before scamming out. ICOs rugpulled in 2021 were active for a much longer time than those that were rugpulled later on, perhaps pointing to new entrants intending to pull the rug. Through qualitative thematic analysis, we discover that these schemes primarily use authoritative and financial lures at the announcement stage of the project to mimic legitimate projects.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
- 3.
We only consider those that we have start dates for. See Sect. 3.1.
- 4.
Marketing must also follow the notification and publication process where applicable.
- 5.
The right to withdraw and reimbursement only applies to retail holders and not to qualified investors.
References
Atondo Siu, G., Hutchings, A., Vasek, M., Moore, T.: “Invest in crypto!”: an analysis of investment scam advertisements found in Bitcointalk. In: 2022 APWG Symposium on Electronic Crime Research (eCrime). IEEE (2022)
Chainalysis: The Biggest Threat to Trust in Cryptocurrency. Rug pulls put 2021 cryptocurrency scam revenue close to all-time highs. https://blog.chainalysis.com/reports/2021-crypto-scam-revenues/
Cousaert, S., Xu, J., Matsui, T.: SOK: yield aggregators in DeFi. In: 2022 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), pp. 1–14 (2022)
European Commission. Proposal for a regulation of the European parliament and of the council on markets in crypto-assets, and amending Directive (EU) 2019/1937 (2022). https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52020PC0593
Foley, S., Karlsen, J.R., Putninš, T.J.: Sex, drugs, and bitcoin: how much illegal activity is financed through cryptocurrencies? Rev. Financ. Stud. 32(5), 1798–1853 (2019)
Gibbs, G.: Analyzing qualitative data. The SAGE Qualitative Research Kit. SAGE, London (2007)
Jahani, E., Krafft, P.M., Suhara, Y., Moro, E., Pentland, A.S.: Scamcoins, s*** posters, and the search for the next bitcoin\(^{TM}\): collective sensemaking in cryptocurrency discussions. In: Proceedings of the ACM on Human-Computer Interaction, vol. 2(CSCW), pp. 1–28 (2018)
Mackenzie, S.: Criminology towards the metaverse: cryptocurrency scams, grey economy and the technosocial. Br. J. Criminol. (2022)
Mazorra, B., Adan, V., Daza, V.: Do not rug on me: leveraging machine learning techniques for automated scam detection. Mathematics 10(6) (2022)
Moore, T., Christin, N., Szurdi, J.: Revisiting the risks of bitcoin currency exchange closure. ACM Trans. Internet Technol. 18(4), 50:1–50:18 (2018)
Morin, A., Vasek, M., Moore, T.: Detecting text reuse in cryptocurrency whitepapers. In: 2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), pp. 1–5 (2021)
Oosthoek, K., Doerr, C.: From hodl to heist: analysis of cyber security threats to bitcoin exchanges. In: 2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), pp. 1–9. IEEE (2020)
Soska, K., Christin, N.: Measuring the longitudinal evolution of the online anonymous marketplace ecosystem. In: Proceedings of the 24th USENIX Security Symposium, Washington, DC, pp. 33–48 (2015)
Stajano, F., Wilson, P.: Understanding scam victims: seven principles for systems security. Commun. ACM 54(3), 70–75 (2011)
Stokel-Walker, C.: How a Squid Game crypto scam got away with millions. https://www.wired.co.uk/article/squid-game-crypto-scam
Trozze, A., Davies, T., Kleinberg, B.: Of degens and defrauders: using open-source investigative tools to investigate decentralized finance frauds and money laundering (2023). https://arxiv.org/abs/2303.00810
US Department of Justice. Two defendants charged in non-fungible token fraud and money laundering scheme. https://www.justice.gov/usao-sdny/pr/two-defendants-charged-non-fungible-token-nft-fraud-and-money-laundering-scheme-0
Vasek, M., Moore, T.: There’s no free lunch, even using bitcoin: tracking the popularity and profits of virtual currency scams. In: Böhme, R., Okamoto, T. (eds.) FC 2015. LNCS, vol. 8975, pp. 44–61. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-47854-7_4
Xia, P., et al.: Trade or trick? Detecting and characterizing scam tokens on Uniswap decentralized exchange. Proc. ACM Measur. Anal. Comput. Syst. 5(3), 1–26 (2021)
Xia, P., et al.: Don’t fish in troubled waters! characterizing coronavirus-themed cryptocurrency scams. In: 2020 APWG Symposium on Electronic Crime Research (eCrime), pp. 1–14. IEEE (2020)
Xia, P., et al.: Characterizing cryptocurrency exchange scams. Comput. Secur. 98, 101993 (2020)
Xu, J., Paruch, K., Cousaert, S., Feng, Y.: SOK: decentralized exchanges (DEX) with automated market maker (AMM) protocols (2021). https://arxiv.org/abs/2103.12732
Acknowledgements
We would like to thank the reviewers for their helpful comments and the FC attendees for their insightful questions. MO is supported by the UK Engineering and Physical Sciences Research Council [grant number EP/S022503/1]. GAS and AH are supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme [grant agreement No. 949127].
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 International Financial Cryptography Association
About this paper
Cite this paper
Agarwal, S., Atondo-Siu, G., Ordekian, M., Hutchings, A., Mariconti, E., Vasek, M. (2024). Short Paper: DeFi Deception—Uncovering the Prevalence of Rugpulls in Cryptocurrency Projects. In: Baldimtsi, F., Cachin, C. (eds) Financial Cryptography and Data Security. FC 2023. Lecture Notes in Computer Science, vol 13950. Springer, Cham. https://doi.org/10.1007/978-3-031-47754-6_21
Download citation
DOI: https://doi.org/10.1007/978-3-031-47754-6_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-47753-9
Online ISBN: 978-3-031-47754-6
eBook Packages: Computer ScienceComputer Science (R0)