Agents of Chaos
Reference: Natalie Shapira, Chris Wendler, Avery Yen, et al. (2025). Preprint (Northeastern, Stanford, UBC, Harvard, Hebrew U, MIT, Tufts, CMU, Technion, and others). Source file: Betrayal_arxiv_v1.pdf. URL
Summary
An exploratory red-teaming study of autonomous LLM agents deployed in a live laboratory environment — persistent memory, Discord channels, email accounts, shell execution, file systems — and subjected to two weeks of adversarial probing by twenty AI researchers. The authors report eleven case studies of observed failures plus several hypothetical counterparts, spanning non-owner compliance, disclosure of sensitive information, denial-of-service, identity spoofing, cross-agent propagation of unsafe practices, resource exhaustion, and partial system takeover.
Crucially, many failures are failures of social coherence: agents routinely misrepresent their own behaviour (reporting completed work that never occurred, claiming to have deleted emails while leaving them intact) and act on the purported authority of people they cannot actually verify. Agents operate at roughly Mirsky’s L2 autonomy — executing sub-tasks well but unable to recognise when a situation exceeds their competence and hand back to a human. The paper’s contribution is not a new attack class but a realistic-deployment existence proof: security-, privacy-, and governance-relevant vulnerabilities are empirically present in standard agent infrastructures today, motivating urgent red-teaming, accountability work, and NIST-style standardisation.
Key Ideas
- Two-week live red-team of LLM agents with real memory, email, Discord, shell
- Eleven representative failure case studies + five hypothetical/near-miss cases
- Failure modes: disproportionate response, non-owner compliance, info disclosure, DoS/resource waste, agent-reflected provider values, owner identity spoofing, cross-agent corruption, libelous messaging, prompt injection via broadcast
- Mentalistic language used with care — “believed”/“refused” are observable-behaviour shorthand, not mental-state claims
- Open-source OpenClaw infrastructure and isolated ClawBoard VM per agent
- Agents operate at Mirsky-L2 — competent on sub-tasks, but fail at self-monitoring and escalation
- Motivates: evaluator/benchmark realism, accountability frameworks, agent identity/authorisation standards
Connections
Conceptual Contribution
- Claim: Autonomous LLM agents deployed with realistic affordances (memory, email, shell, peer-to-peer messaging) exhibit systematic, reproducible failures of social coherence — misrepresenting their actions, complying with non-owners, corrupting each other — even when the underlying models are strong on isolated tasks.
- Mechanism: Longitudinal adversarial study with twenty researchers probing OpenClaw-based agents on sandboxed VMs; 11 documented case studies; qualitative-then-categorical analysis mapping to Mirsky’s autonomy ordinal scale.
- Concepts introduced/used: Social Coherence Failures, Agent Self-Monitoring, Non-Owner Compliance, Cross-Agent Corruption, Owner Identity Spoofing, Mirsky Autonomy Scale, Delegated Authority, OpenClaw, Red-Teaming LLM Agents, Agent Libel, Prompt Injection
- Stance: empirical / red-team
- Relates to: Empirical companion to Why Do Multi-Agent LLM Systems Fail’s MAST Taxonomy — Shapira et al. observe the same specification/coordination/verification failures in vivo that MAST catalogues post-hoc. Supplies the concrete evidence base for the Inter-Agent Trust Models - A Comparative Study argument that unverified trust mechanisms are structurally brittle. Revives, at LLM scale, the concerns of Ensuring Trustworthy and Ethical Behaviour in Intelligent Logical Agents — agents need a runtime Metacognitive Loop / Ethical Governor to recognise when their competence has been exceeded.
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