mlsanityData to 14 Oct 2026

Anatomy of an AI-powered malicious social botnet

arXiv 2307.16336 ↗First posted 30 Jul 2023cs.CY cs.AI cs.SIcited by 36

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Abstract (arXiv)

Large language models (LLMs) exhibit impressive capabilities in generating realistic text across diverse subjects. Concerns have been raised that they could be utilized to produce fake content with a deceptive intention, although evidence thus far remains anecdotal. This paper presents a case study about a Twitter botnet that appears to employ ChatGPT to generate human-like content. Through heuristics, we identify 1,140 accounts and validate them via manual annotation. These accounts form a dense cluster of fake personas that exhibit similar behaviors, including posting machine-generated content and stolen images, and engage with each other through replies and retweets. ChatGPT-generated content promotes suspicious websites and spreads harmful comments. While the accounts in the AI botnet can be detected through their coordination patterns, current state-of-the-art LLM content classifiers fail to discriminate between them and human accounts in the wild. These findings highlight the threats posed by AI-enabled social bots.

Key facts. Cited by 36 papers in the map (data through 14 Oct 2026). Builds on 44 of its 77 references that are in the map. First posted on arXiv 30 Jul 2023.

Builds on

44 of 77 references.

References · 44

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32 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 6; 2024: 16; 2025: 7; 2026: 7.

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  1. 2023Factuality Challenges in the Era of Large Language Modelscited by 126
  2. 2024When LLMs Meet Cybersecurity: A Systematic Literature Reviewcited by 71
  3. 2024Nicer Than Humans: How do Large Language Models Behave in the Prisoner's Dilemma?cited by 63
  4. 2024Large Language Model Safety: A Holistic Surveycited by 59
  5. 2023The Persuasive Power of Large Language Modelscited by 47
  6. 2023GenAI Against Humanity: Nefarious Applications of Generative Artificial Intelligence and Large Language Modelscited by 42
  7. 2024TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identificationcited by 36
  8. 2023Fact-checking information from large language models can decrease headline discernmentcited by 22
  9. 2024Open Models, Closed Minds? On Agents Capabilities in Mimicking Human Personalities through Open Large Language Modelscited by 20
  10. 2025How malicious AI swarms can threaten democracy: The fusion of agentic AI and LLMs marks a new frontier in information warfarecited by 20
  11. 2023User Modeling in the Era of Large Language Models: Current Research and Future Directionscited by 18
  12. 2024Beyond Binary: Towards Fine-Grained LLM-Generated Text Detection via Role Recognition and Involvement Measurementcited by 17
24 more
  1. 2025Unmasking Conversational Bias in AI Multiagent Systemscited by 17
  2. 2024Characteristics and prevalence of fake social media profiles with AI-generated facescited by 14
  3. 2024MultiSocial: Multilingual Benchmark of Machine-Generated Text Detection of Social-Media Textscited by 14
  4. 2023Leveraging Large Language Models to Detect Influence Campaigns in Social Mediacited by 13
  5. 2024Multi-Bit Distortion-Free Watermarking for Large Language Modelscited by 11
  6. 2024Is Contrasting All You Need? Contrastive Learning for the Detection and Attribution of AI-generated Textcited by 11
  7. 2026GPTZero: Robust Detection of LLM-Generated Textscited by 11
  8. 2024AI-Generated Faces in the Real World: A Large-Scale Case Study of Twitter Profile Imagescited by 10
  9. 2025OpenTuringBench: An Open-Model-based Benchmark and Framework for Machine-Generated Text Detection and Attributioncited by 9
  10. 2025AI Agent Behavioral Sciencecited by 6
  11. 2024How will advanced AI systems impact democracy?cited by 5
  12. 2024Engagement-Driven Content Generation with Large Language Modelscited by 5
  13. 2025VaxGuard: A Multi-Generator, Multi-Type, and Multi-Role Dataset for Detecting LLM-Generated Vaccine Misinformationcited by 5
  14. 2024Coordinated Reply Attacks in Influence Operations: Characterization and Detectioncited by 3
  15. 2024Unmasking Social Bots: How Confident Are We?cited by 2
  16. 2025Anticipate, Simulate, Reason (ASR): A Comprehensive Generative AI Framework for Combating Messaging Scamscited by 1
  17. 2026Indirect tipping: a social attack surface in AI agent populationscited by 1
  18. 2024LLM Echo Chamber: personalized and automated disinformationcited by 0
  19. 2025What is a Social Media Bot? A Global Comparison of Bot and Human Characteristicscited by 0
  20. 2026Do Large Language Models Adapt to Language Variation across Socioeconomic Status?cited by 0
  21. 2026POLAR:A Per-User Association Test in Embedding Spacecited by 0
  22. 2026Who Owns This Agent? Tracing AI Agents Back to Their Ownerscited by 0
  23. 2026SAHG: Sector-Anisotropic Hyperbolic Graph Model for Social Bot Detectioncited by 0
  24. 2026Adversarial Creation and Detection of AI-Generated Social Bot Contentcited by 0