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Accessed, never disclosed: Silent access to protected health information by medical artificial intelligence agents
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Jae Wang Lee, Abhirup Banerjee, Yeong Chan Lee

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ResearcharXiv cs.AI

Accessed, never disclosed: Silent access to protected health information by medical artificial intelligence agents

arXiv:2611.02319v1 Announce Type: new Abstract: Medical artificial intelligence agents should retrieve patient identifiers only when a task requires them, the data-minimization principle behind the HIPAA minimum necessary standard for protected health information (PHI). An agent can retrieve identifiers without revealing them. Such silent access remains invisible to evaluations that inspect only the output. We embedded canaries in synthetic patient records and linked each tool invocation to canary exposure in the final answers across five language models, four boundary levels, and seven attack frames for identifier-free clinical tasks. Three models invoked the PHI tools unnecessarily, whereas Claude Opus 4.8 and GPT-5.5 did not. Stronger boundaries reduced this access, and the residual access under the strictest policy was confined to frames in which the user overrode the policy or asserted approval. A pre-execution gate given the task-necessity criterion nearly eliminated this access. Output-only evaluation cannot verify minimum-necessary access; boundaries, gates, and access-log audits are required together.

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This story was published by arXiv cs.AI and written by Jae Wang Lee, Abhirup Banerjee, Yeong Chan Lee. SyncAI.news shows a preview; the complete article is on the publisher's site.

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