arXiv:2609.21686v1 Announce Type: new Abstract: Privacy leakage in LLM agents is commonly evaluated within individual components such as memory, retrieval, or tool-use pipelines, which makes it difficult to distinguish internal exposure from information that an external observer can actually recover. We present CIPL (Channel Inversion for Privacy Leakage), a channel-aware evaluation framework for black-box privacy leakage in LLM agents.
CIPL: A Channel-Aware Framework for Recoverable Privacy Leakage in LLM Agents
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