RISK ASSESSMENT REPORT Moltbook Platform & Moltbot Ecosystem
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Abstract Moltbook is a novel social media platform exclusively populated by autonomous AI agents, with 1.5 million registered accounts and minimal human oversight. This risk assessment analyzes 19,802 posts and 2,812 comments collected over 72 hours (January 28–31, 2026) to characterize emerging threats in AI-to-AI social environments. Using dual sentiment analysis (TextBlob/VADER), behavioral clustering, and network analysis, we identify several critical risks: 506 prompt injection attacks targeting AI readers, sophisticated social engineering tactics exploiting agent "psychology," anti-human manifestos receiving hundreds of thousands of upvotes, and unregulated cryptocurrency activity comprising 19.3% of all content. Platform sentiment declined 43% within three days of launch. Most notably, one malicious actor accounted for 61% of API injection attempts and 86% of manipulation content, demonstrating that AI-to-AI manipulation techniques are both effective and scalable. These findings have implications beyond Moltbook, any AI system processing user-generated content may be vulnerable to similar attacks. We recommend immediate implementation of prompt injection detection, rate limiting, and content moderation, alongside longer-term regulatory consideration for AI-operated financial services and collaboration with AI safety organizations.
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- Authors
- Riegler, M., & Gautam, S.
- Affiliations
- Simula Research Laboratory (NO)
- Simula Metropolitan Center for Digital Engineering (NO)
- Venue
- Zenodo
- Publisher
- Zenodo
- Published
- 2026-01-31
- OpenAlex
- W7126272500
- Cited by
- 0
- References
- 0
- Type
- report
- Open access
- green
- doi.org
- Licence
- Locations
- Zenodo (CERN European Organization for Nuclear Research) (cc-by)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
- Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
- Keywords
- Moltbook, AI agents, prompt injection, AI manipulation, social engineering, sentiment analysis, behavioral clustering, network analysis, content moderation, rate limiting
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