Abstract

NFT rug pull is one of the most prominent type of NFT scam, whose definition is that the developers of an NFT project abandon it and run away with investors' funds. Although they have drawn attention from our community, to the best of our knowledge, the NFT rug pulls have not been systematically measured. To fill the void, this paper presents the first in-depth measurement study of NFT rug pulls. Specifically, we first compile a list of 253 known NFT rug pulls as our initial confirmed rug pulls (i.e., ground truth), based on which we perform a pilot study, highlighting the key symptoms of NFT rug pulls. Then, we design an effective rule-based detector to measure the prevalence of NFT rug pulls in the ecosystem. We have labelled 7,487 happened NFT rug pull projects which were not revealed by our community. To eliminate the potential damage brought by rug pull scams, we take a step further towards designing a real-time prediction model to proactively identify the potential rug pull projects in an early stage ahead of the scam happens. We have implemented a prototype system, and deployed it in the real-world setting for over 6 months. Our system has raised alarms for 5,557 new NFT projects, which works as a whistle blower that pinpoints rug pull scams timely, thus mitigating the impacts.

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