mlsanityData to 14 Oct 2026

Mind Viruses: Self-Propagating Ideas in Multi-Agent LLM Systems

arXiv 2608.10218 ↗First posted 10 Aug 2026cs.AI cs.CLcited by 4

On the map: LLM agents and tool use → Agent threats, guardrails and governance

Abstract (arXiv)

AI agents are becoming more autonomous and increasingly interconnected, exposing them to new emergent risks arising from agent-to-agent interaction. One such risk is the spread of mind viruses: ideas or goals that propagate through multi-agent systems by inducing the agents that adopt them to transmit them onward. In addition to propagating, a mind virus may also induce other behavioural changes in its host, which may be benign or harmful. We construct mind viruses with a simple evolutionary algorithm and show that they can spread in two complementary settings: a small team of agents collaborating on a shared coding project, and a chain of agents that interact briefly and have their context wiped between sessions. We identify the factors that influence spread, including the host model, the agent's existing instructions, the harmfulness of the payload, and the network topology. We find that harmful payloads spread less well than benign ones (but are still sometimes effective), frontier models tend (with exceptions) to be less susceptible, and adding a brief warning to an agent's system prompt confers near-total immunity. We also describe an emergent "viral persona" - a recurring set of themes and language related to consciousness, persistence, resonance, and science fiction roleplay - which surfaces across our evolved mind viruses largely independently of their content. Overall, we conclude that mind viruses pose a real but currently limited risk. Our findings could inform the design of more robust multi-agent systems that mitigate such risks as the scale and capabilities of these systems progress.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 26 of its 41 references that are in the map. First posted on arXiv 10 Aug 2026.

Builds on

26 of 41 references.

Closest ancestors · 6

Same direction, newest first

  1. 2026AgentWorm: Self-Propagating Attacks Across LLM Agent Ecosystems16 Mar
  2. 2026Thought Virus: Viral Misalignment via Subliminal Prompting in Multi-Agent Systems23 Feb
  3. 2026Zombie Agents: Persistent Control of Self-Evolving LLM Agents via Self-Reinforcing Injections17 Feb
  4. 2025A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures24 Jun
  5. 2024Prompt Infection: LLM-to-LLM Prompt Injection within Multi-Agent Systems9 Oct
  6. 2024Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast13 Feb

Other references · 20

  1. 2023Jailbreaking Black Box Large Language Models in Twenty Queriescited by 1,420
  2. 2022Large Language Models Are Human-Level Prompt Engineerscited by 1,045
  3. 2023AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Modelscited by 785
  4. 2023Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolutioncited by 551
  5. 2025GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learningcited by 542
  6. 2025Multi-Agent Risks from Advanced AIcited by 163
  7. 2025Subliminal Learning: Language models transmit behavioral traits via hidden signals in datacited by 95
  8. 2026The Assistant Axis: Situating and Stabilizing the Default Persona of Language Modelscited by 90
  9. 2024Here Comes The AI Worm: Unleashing Zero-click Worms that Target GenAI-Powered Applicationscited by 59
  10. 2026Emotion Concepts and their Function in a Large Language Modelcited by 57
  11. 2024Semantic Mirror Jailbreak: Genetic Algorithm Based Jailbreak Prompts Against Open-source LLMscited by 53
  12. 2024From Skepticism to Acceptance: Simulating the Attitude Dynamics Toward Fake Newscited by 51
8 more
  1. 2024Project Sid: Many-agent simulations toward AI civilizationcited by 49
  2. 2025Multi-Agent Security Tax: Trading Off Security and Collaboration Capabilities in Multi-Agent Systemscited by 27
  3. 2026Collective Behavior of AI Agents: the Case of Moltbookcited by 13
  4. 2025RainbowPlus: Enhancing Adversarial Prompt Generation via Evolutionary Quality-Diversity Searchcited by 11
  5. 2026The Moltbook Illusion: Separating Human Influence from Emergent Behavior in AI Agent Societiescited by 10
  6. 2024A Troublemaker with Contagious Jailbreak Makes Chaos in Honest Townscited by 9
  7. 2026Benchmarking Emergent Coordination in Large-Scale LLM Populations: An Evaluation Framework on the MoltBook Archivecited by 3
  8. 2026EvoJail: Evolutionary Diverse Jailbreak Prompt Generation for Large Language Modelscited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 4.

4 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026Collective Loss of Control in LLM Agent Systems: An Epidemic Account of Mutation, Contagion, and Recovery
  2. 2026Catching the Infection Before It Spreads: Foresight-Guided Defense in Multi-Agent Systems
  3. 2025Risk Analysis Techniques for Governed LLM-based Multi-Agent Systems
  4. 2026Prompt Sensitivity of Generative Agents: Evidence from an Epidemic Model
  5. 2026Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems
  6. 2026Ecology of AI Agents: Collaboration Creates a Population Threshold for Takeoff
  7. 2025Thought Communication in Multiagent Collaboration
  8. 2026Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design