With Trail to Follow: Measurements of Real-world Non-fungible Token Phishing Attacks on Ethereum

• URL: http://arxiv.org/abs/2307.01579v2
• Date: Thu, 28 Mar 2024 07:51:04 GMT
• Title: With Trail to Follow: Measurements of Real-world Non-fungible Token Phishing Attacks on Ethereum
• Authors: Jingjing Yang, Jieli Liu, Jiajing Wu,
• Abstract summary: There has been growing anecdotal evidence that new means of NFT phishing attacks have emerged in ecosystem. Most of the existing research focus on detecting phishing scam accounts for native cryptocurrency on the blockchain. There is a lack of research in the area of phishing attacks of emerging NFTs.
• Score: 4.297180143942048
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: With the popularity of Non-Fungible Tokens (NFTs), NFTs have become a new target of phishing attacks, posing a significant threat to the NFT trading ecosystem. There has been growing anecdotal evidence that new means of NFT phishing attacks have emerged in Ethereum ecosystem. Most of the existing research focus on detecting phishing scam accounts for native cryptocurrency on the blockchain, but there is a lack of research in the area of phishing attacks of emerging NFTs. Although a few studies have recently started to focus on the analysis and detection of NFT phishing attacks, NFT phishing attack means are diverse and little has been done to understand these various types of NFT phishing attacks. To the best of our knowledge, we are the first to conduct case retrospective analysis and measurement study of real-world historical NFT phishing attacks on Ethereum. By manually analyzing the existing scams reported by Chainabuse, we classify NFT phishing attacks into four patterns. For each pattern, we further investigate the tricks and working principles of them. Based on 469 NFT phishing accounts collected up until October 2022 from multiple channels, we perform a measurement study of on-chain transaction data crawled from Etherscan to characterizing NFT phishing scams by analyzing the modus operandi and preferences of NFT phishing scammers, as well as economic impacts and whereabouts of stolen NFTs. We classify NFT phishing transactions into one of the four patterns by log parsing and transaction record parsing. We find these phishing accounts stole 19,514 NFTs for a total profit of 8,858.431 ETH (around 18.57 million dollars). We also observe that scammers remain highly active in the last two years and favor certain categories and series of NFTs, accompanied with signs of gang theft.

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