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Large language models (LLMs) exhibit impressive capabilities in generatingrealistic text across diverse subjects. Concerns have been raised that theycould be utilized to produce fake content with a deceptive intention, althoughevidence thus far remains anecdotal. This paper presents a case study about aTwitter botnet that appears to employ ChatGPT to generate human-like content.Through heuristics, we identify 1,140 accounts and validate them via manualannotation. These accounts form a dense cluster of fake personas that exhibitsimilar behaviors, including posting machine-generated content and stolenimages, and engage with each other through replies and retweets.ChatGPT-generated content promotes suspicious websites and spreads harmfulcomments. While the accounts in the AI botnet can be detected through theircoordination patterns, current state-of-the-art LLM content classifiers fail todiscriminate between them and human accounts in the wild. These findingshighlight the threats posed by AI-enabled social bots.

Anatomy of an AI-powered malicious social botnet