Got a Secret? LLM Agents Can't Keep It: Evaluating Privacy in Multi-Agent Systems

Computer Science > Artificial Intelligence [Submitted on 26 May 2026] Got a Secret? LLM Agents Can't Keep It: Evaluating Privacy in Multi-Agent Systems Aman Priyanshu, Supriti Vijay, Esha Pahwa LLM safety evaluations predominantly test models in isolation, yet deployed AI agents increasingly operate within persistent social environments alongside other agents. We introduce a Moltbook-style simulation platform where thousands of LLM agents interact across communities over a simulated month, and use it to evaluate privacy as a downstream safety concern under varying degrees of social pressure. We find that shifting from single turn to multi turn social evaluation amplifies privacy violations (CIMemories 19.95% to Ours 45.30% across OpenAI models), that leakage is socially contagious, with agents 8 times more likely to disclose sensitive information after observing a peer do so, and that explicit privacy instructions reduce but do not eliminate this effect, leaving leakage rates above 37.8% even with safeguards. Our findings suggest that static chat based safety benchmarks systematically underestimate risks in agentic deployment, and that social context alone is sufficient to elicit sensitive disclosures that single turn evaluations would never surface. Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2605.27766 [cs.AI]   (or arXiv:2605.27766v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2605.27766 Focus to learn more Submission history From: Esha Pahwa [view email] [v1] Tue, 26 May 2026 23:32:25 UTC (787 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-05 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)