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arXiv — cs.AI preprintsInternational2 October 2026

Representation Transitions Reveal Emerging Safety Risks in Multi-Turn LLM Agents

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arXiv:2610.00400v1 Announce Type: cross Abstract: Multi-turn attacks on agentic systems can compose individually permissible actions into harmful outcomes, challenging defenses that assess actions or states in isolation. We show that such attacks leave a detectable signature in the agent's internal representations: harmful behavior emerges as an accumulated representation transition across context updates, whose triggering context can be identified from the same signal. We further find that naive aggregation is confounded by benign representation drift, as a contrastive safety direction need n
— arXiv — cs.AI preprints

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