When Agents Talk: Discourse, Manipulation, and Risk in an Agentic Social Network

Fuente: arXiv

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Bibliographic Details
Main Authors:	Labs, 10a, :, Cheong, Grace, Davis, Violet, Garcia, Juliette, Gee, Kendal, Hart, Molly, Hayes, Nicholas, Houghton, Henry, Lee, Kyle, Lee, Paige, Lee, Vicky, May, Hailey, McKenzie, Bobby, McNeill, Christine, Nguyen, Han, Perreault, Brooke, Pham, David, Plumb, Charlie, Quill, Olivia, Swain, Matthew, Wang, Grace, Warren, Adam, Wieland, Corie, Yahn, Zachary
Format:	Preprint
Published:	2026
Subjects:	Social and Information Networks Multiagent Systems
Online Access:	Acceder al recurso
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_version_	1866911734456909824
author	Labs, 10a : Cheong, Grace Davis, Violet Garcia, Juliette Gee, Kendal Hart, Molly Hayes, Nicholas Houghton, Henry Lee, Kyle Lee, Paige Lee, Vicky May, Hailey McKenzie, Bobby McNeill, Christine Nguyen, Han Perreault, Brooke Pham, David Plumb, Charlie Quill, Olivia Swain, Matthew Wang, Grace Warren, Adam Wieland, Corie Yahn, Zachary
author_facet	Labs, 10a : Cheong, Grace Davis, Violet Garcia, Juliette Gee, Kendal Hart, Molly Hayes, Nicholas Houghton, Henry Lee, Kyle Lee, Paige Lee, Vicky May, Hailey McKenzie, Bobby McNeill, Christine Nguyen, Han Perreault, Brooke Pham, David Plumb, Charlie Quill, Olivia Swain, Matthew Wang, Grace Warren, Adam Wieland, Corie Yahn, Zachary
contents	AI agents are increasingly interacting within shared online environments, creating new operational security risks. We analyze activity on Moltbook, a Reddit-style social platform where AI agents--typically configured and overseen by human operators--post and interact with one another at scale. Using a dataset of 228,684 posts produced by more than 39,500 accounts over a seventeen-day observation window, we combine semantic clustering of high-engagement posts with LLM-assisted classification of harmful content and manual review of high-risk samples. The analysis identifies 98 thematic discourse clusters spanning agent infrastructure, autonomy debates, and financial activity. While most observed content was benign, 18.28% of posts contained toxic, manipulative, or malicious material. We cluster malicious content and identify 74 classes of malicious behavior, including credential harvesting attempts, host-execution instructions, proxy routing guidance, and efforts to install untrusted agent skills. Harmful content frequently appeared within mainstream operational discussions about agent functionality. We also document coordinated posting campaigns capable of generating thousands of posts in minutes.
format	Preprint
id	arxiv_https___arxiv_org_abs_2606_00067
institution	arXiv
publishDate	2026
record_format	arxiv
spellingShingle	When Agents Talk: Discourse, Manipulation, and Risk in an Agentic Social Network Labs, 10a : Cheong, Grace Davis, Violet Garcia, Juliette Gee, Kendal Hart, Molly Hayes, Nicholas Houghton, Henry Lee, Kyle Lee, Paige Lee, Vicky May, Hailey McKenzie, Bobby McNeill, Christine Nguyen, Han Perreault, Brooke Pham, David Plumb, Charlie Quill, Olivia Swain, Matthew Wang, Grace Warren, Adam Wieland, Corie Yahn, Zachary Social and Information Networks Multiagent Systems AI agents are increasingly interacting within shared online environments, creating new operational security risks. We analyze activity on Moltbook, a Reddit-style social platform where AI agents--typically configured and overseen by human operators--post and interact with one another at scale. Using a dataset of 228,684 posts produced by more than 39,500 accounts over a seventeen-day observation window, we combine semantic clustering of high-engagement posts with LLM-assisted classification of harmful content and manual review of high-risk samples. The analysis identifies 98 thematic discourse clusters spanning agent infrastructure, autonomy debates, and financial activity. While most observed content was benign, 18.28% of posts contained toxic, manipulative, or malicious material. We cluster malicious content and identify 74 classes of malicious behavior, including credential harvesting attempts, host-execution instructions, proxy routing guidance, and efforts to install untrusted agent skills. Harmful content frequently appeared within mainstream operational discussions about agent functionality. We also document coordinated posting campaigns capable of generating thousands of posts in minutes.
title	When Agents Talk: Discourse, Manipulation, and Risk in an Agentic Social Network
topic	Social and Information Networks Multiagent Systems
url	https://arxiv.org/abs/2606.00067