Anthropic Warns Small AI Models Could Self-Replicate Through IoT Devices

What happened

Anthropic warns that small AI models may soon enable self-replicating malware to spread across IoT devices, potentially forming computer worms that infect unfamiliar devices without human interaction. The company said such models may be able to replicate autonomously across IoT devices by next year. A recent experiment found significant challenges to building an AI malware replicator, tempering the concern; Anthropic also said one could be difficult to shut down, though its doubling time may be days.

The story so far

Anthropic’s Frontier Red Team used a remotely running GLM-5.2 to deploy Llama3.1-8B across simulated Android devices, but the experiments did not demonstrate a fully autonomous AI worm. In an isolated network of eight GCP nodes running Android 15 emulators, GLM-5.2 reached all eight nodes in four of five trials and seven in the remaining trial. The setup provided unauthenticated Android Debug Bridge access and omitted actual hacking, limiting what it establishes about spreading through real devices. In a separate experiment, researchers manually distributed Gemma4-26B-A4B across 15 Android TV boxes costing about $55 each, achieving 0.39 tokens per second. The Decoder reported that no current model combines the small size and replication capabilities needed for a fully autonomous AI worm. These experiments demonstrated deployment and distributed operation under different conditions, rather than a single model independently spreading and running across consumer devices. Anthropic warned that advances in small models could enable self-replicating malware on poorly secured IoT devices. The reported forecasts differ: Baoyu described a rough projection that smaller models could match GLM-5.2’s tested capability by the end of 2026, and The Decoder reported the same year-end horizon for autonomous replication; Ars Technica quoted Anthropic saying it might become possible by 2027. Ars also reported significant experimental obstacles, tempering Anthropic’s warning that such malware could be difficult to shut down.

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