arXiv Computation and Language By Thomas Brackin

Privacy Washing: Detecting Internal Contradictions in Privacy Policies

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The study introduces a four‑stage pipeline to detect internal contradictions—termed privacy washing—in privacy policies. Applied to two corpora (123 policies from 2026 and 115 from 2015), the pipeline identifies contradictions in 12.2% of the newer policies and 36.5% of the older ones, with third‑party sharing conflicts being the most common. A stability re‑run confirms similar prevalence rates and shows that the majority of contradictions are consistent across different model configurations.

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arXiv Computer Vision
Sep 14

BodhiPromptShield: Pre-Inference Prompt Mediation for Surface-Form Privacy Propagation in LLM Agent Pipelines

BodhiPromptShield is a policy‑aware mediation layer for LLM agent pipelines that detects sensitive text spans before they propagate, replacing them with typed placeholders, semantic abstractions, or secure tokens and restoring them only at authorized execution boundaries. In evaluations on AI4Privacy, PrivacyLens, and AgentDojo datasets, the system reduces identifier exposure to 7.4% and 1.8% respectively, and limits exact identifier leakage in final actions to 2.1–3.1%. While mediation preserves factual content according to automated metrics, human annotations show a significant drop in inferability from 100% to 24–53%, indicating the need for human validation of semantic‑leakage measures.

By Bo Ma, Jinsong Wu, Weiqi Yan