RISK ASSESSMENT REPORT Moltbook Platform & Moltbot Ecosystem

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Authors: Michael Alexander Riegler, Sushant Gautam
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Abstract

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.

Fields of Study & Subjects

Ethics and Social Impacts of AI Hate Speech and Cyberbullying Detection Spam and Phishing Detection

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
31 January 2026