Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation
The most capable AI deployments are not single models but ensembles of specialized agents that delegate and act in coordination. This architecture unlocks powerful new capabilities, and it also introduces risks that existing frameworks for monitoring, detection, and mitigation were not designed to address. Most state-of-the-art AI abuse detection literature focuses on single-turn or multi-turn (single-session) threat models. This leaves a critical gap: an attacker can decompose a harmful goal in
Record details
Published: 3 August 2026
Source: arXiv cs.AI
Category: Research
Topics: Agents & autonomy
Retrieved: 4 August 2026
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ethics.ai (3 August 2026), “Magnet: Detecting Cross-Session AI Misuse Through Capability Accumulation,” evidence record 16088, https://ethics.ai/record/16088 (originally published by arXiv cs.AI).
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