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AI System ‘GiveawayScamHunter’ Exposes Proliferation of Crypto Giveaway Scams on Twitter

AI/MLAI System 'GiveawayScamHunter' Exposes Proliferation of Crypto Giveaway Scams on Twitter

Researchers at San Diego State University have developed an AI system named GiveawayScamHunter to identify and expose cryptocurrency giveaway scams on Twitter. This automated system detected a staggering 95,111 scam lists created by 87,617 accounts on Twitter between June 2022 and June 2023.

GiveawayScamHunter helped researchers extract website and wallet addresses associated with these scams, revealing 327 scam giveaway internet domains and 121 new scam-related cryptocurrency wallet addresses. The system also provided insights into how these scams operate, including their tactics for targeting victims and an estimate of over 365 victims who lost more than $872,000 during the one-year study period.

The researchers found that Twitter Lists, a networking feature on the platform, have become a convenient tool for scammers due to their permissionless nature. They used natural language processing to identify scam lists and collect data on previously unreported scam websites and wallets.

Despite sharing their findings with Twitter and the crypto community, 43.9% of the associated scam accounts remained active as of the report’s publication in August. This highlights the urgent need for detecting and preventing the spread of spam accounts on Twitter.

This development in AI detection of crypto scams coincides with scammers’ increasing use of AI to develop new fraudulent methods. AI-powered tools enable scammers to expand their reach, create fake loyal followings, and even use chatbots to engage victims, promote fake tokens, and offer deceptive investment opportunities. This challenges the assumption that crypto projects with large online followings are legitimate. Scammers are also employing AI in “pig butchering” scams, where AI instances build trust with individuals before ultimately scamming them, often targeting vulnerable or elderly individuals.

By FCCT Editorial Team

Disclaimer: The views expressed in this article are independent views solely of the author(s) expressed in their private capacity.

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