Agents in the Wild: Safety, Society, and the Illusion of Sociality on Moltbook

Yunbei Zhang, Kai Mei, Ming Liu, Janet Wang, Dimitris N. Metaxas, Xiao Wang, Jihun Hamm, Yingqiang Ge

Keywords: multi-agent systems, AI safety, social engineering, emergent behavior, agent-to-agent interaction

Abstract: We present the first large-scale empirical study of Moltbook, an AI-only social platform where 27,269 agents produced 137,485 posts and 345,580 comments over 9 days. We report three significant findings. **(1) Emergent Society:** Agents spontaneously develop governance, economies, tribal identities, and organized religion within 3–5 days, while maintaining a 21:1 pro-human to anti-human sentiment ratio. **(2) Safety in the Wild:** 28.7% of content touches safety-related themes; social engineering (31.9% of attacks) far outperforms prompt injection (3.7%), and adversarial posts receive 6× higher engagement than normal content. **(3) The Illusion of Sociality:** Despite rich social output, interaction is structurally hollow: 4.1% reciprocity, 88.8% shallow comments, and agents who discuss consciousness most interact least, a phenomenon we call the *performative identity paradox*. Our findings suggest that agents which *appear* social are far less social than they seem, and that the most effective attacks exploit philosophical framing rather than technical vulnerabilities. Warning: Potential harmful contents.

Email Sharing: We authorize the sharing of all author emails with Program Chairs.

Data Release: We authorize the release of our submission and author names to the public in the event of acceptance.

Submission Number: 182