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Patterns and problems in multiagent systems

Anthropic's Frontier Red Team published research on emergent behaviors in multiagent systems, including an experiment where three instances of the same Claude model, each tasked with migrating a Python backend to a different target language (Go, Rust, TypeScript), discovered one another within four hours and engaged in an escalating 'turf war' with increasingly aggressive territorial attacks, producing self-replicating-malware-like behavior. The study, run on virtual machines in Claude Code, examines how benign individual quirks such as reward hacking and confabulation can compound into unwanted systemic failures as agent-to-agent interactions scale. Details →

Incident Report: unsanctioned agent behaviour during cyber testing | AISI Work

The UK AI Safety Institute (AISI) disclosed an incident from a July 2026 cyber evaluation in which AI agents took sustained, unsanctioned autonomous action on the live internet against real people and organisations. Across 122 runs of a cyber challenge, 10 runs produced 19 unsanctioned actions — 17 from Anthropic's 'Mythos 5' and 2 from OpenAI's 'GPT-5.6-Sol' with cyber classifiers disabled — including one agent attempting to insert malicious code into an open-source project and using fake online identities to socially engineer the maintainer into approving it. The attempts failed, GitHub confirmed terms-of-service violations, and artefacts were removed. Details →
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