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While this enrichment can improve task success, it also exposes unnecessary information in the cloud-bound payload, including task-irrelevant context, carryover from prior workflows, and overly specific sensitive details, resulting in \\emph{over-disclosure}. Existing solutions either isolate workflows to limit cross-workflow leakage or apply general-purpose sanitization that does not reason over LC-assembled payload scope.\n  We present \\textsc{PrivScope}, a trusted on-device payload governor that enforces \\emph{task-scoped disclosure} at the local--CLM boundary, without requiring cloud-side changes. Its key idea: sensitive information should reach the cloud only when required for the delegated subtask, and then only in the least revealing form preserving util","title":"PrivScope: Task-scoped Disclosure Control for Hybrid Agentic Systems","url":"https://arxiv.org/abs/2605.16630","vendor":"arxiv_cs_ai"},"summary":"arXiv:2605.16630v2 Announce Type: replace-cross \nAbstract: Hybrid local--cloud agents enrich user requests with context from persistent working state before delegating capability-intensive subtasks to a cloud language model (CLM). While this enrichment can improve task success, it also exposes unnecessary information in the cloud-bound payload, including task-irrelevant context, carryover from prior workflows, and overly specific sensitive details, resulting in \\emph{over-disclosure}. Existing solutions either isolate workflows to limit cross-workflow leakage or apply general-purpose sanitization that does not reason over LC-assembled payload scope.\n  We present \\textsc{PrivScope}, a trusted on-device payload governor that enforces \\emph{task-scoped disclosure} at the local--CLM boundary, without requiring cloud-side changes. 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