Mind the Hook: Source-Level Auditing of Privacy Defenses in Retrieval-Augmented Generation

Computer Science > Cryptography and Security [Submitted on 10 Aug 2026] Mind the Hook: Source-Level Auditing of Privacy Defenses in Retrieval-Augmented Generation Yanhang Li, Zhichao Fan, Zexin Zhuang Black-box privacy scores for retrieval-augmented generation (RAG) are difficult to interpret unless the audited defense's active pipeline hook is known. We propose an active-path audit: inventory source-level hooks over retrieval, retrieved content, and generation; map each metric to the leakage channel it observes; and validate generated-text effects with exact-match canaries. In our benchmark reimplementations, the DP-style defenses modify retrieval scores only: their generation hooks are TODO-flagged stubs that return responses unchanged. This active path explains why they affect membership-inference behavior but track No-Defense on generated-text named-entity leakage, measured by NEL_strict. By contrast, the end-to-end LPRAG path is canary-validated on the email channel, recovering 53/150 canaries under No-Defense and 0/150 under LPRAG. These findings concern our reimplementations on our stack, not released defenses or defense families; the contribution is a methodology and case study, not a universal ranking Comments: 6 pages, 1 figure. Accepted as a regular paper at the 25th IEEE International Conference on Machine Learning and Applications (ICMLA 2026) Subjects: Cryptography and Security (cs.CR); Machine Learning (cs.LG) Cite as: arXiv:2608.09001 [cs.CR]   (or arXiv:2608.09001v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2608.09001 Focus to learn more Submission history From: Yanhang Li [view email] [v1] Mon, 10 Aug 2026 01:40:25 UTC (98 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-08 Change to browse by: cs cs.LG References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)