Auditing Privacy in Multi-Tenant RAG under Account Collusion

TL;DR

This paper reveals privacy vulnerabilities in multi-tenant RAG systems under account collusion, proposes an auditable protocol to detect leakage, and empirically validates its effectiveness.

Contribution

It introduces the first audit protocol for unmodified RAG deployments that quantifies privacy leakage under collusion scenarios.

Findings

Joint leakage degrades at rate Θ(√k) under collusion.

The proposed audit protocol effectively detects privacy breaches.

Empirical tests confirm the attack's realization and the protocol's accuracy.

Abstract

Multi-tenant retrieval-augmented generation (RAG) services advertise per-account differential privacy as the operative leakage boundary: each account's queries are guaranteed to satisfy $(\varepsilon_{\text{acc}}, \delta_{\text{acc}})$-DP with respect to the index. We identify same-index multi-account collusion as a privacy-boundary failure: for $k$ same-tenant accounts coordinating against the tenant's index -- the operative regime -- known DP composition theory implies joint leakage degrades unconditionally at rate $\Theta(\sqrt{k} \cdot \varepsilon_{\text{acc}})$ for Gaussian-noised retrieval. Cross-tenant and external collusion match the rate only under explicit access-control failure (M4); without M4 these regimes have zero leakage by design and reduce to an architectural audit, not a DP audit. We exhibit an attack realizing the rate and derive a RAG-specific MIA prediction we test empirically. To make this per-account/joint gap auditable, we design the first audit protocol that operates against unmodified RAG deployments and issues a quantitative $(\textsf{PASS}, \varepsilon_{\text{audit}})$ verdict for the retrieval-score channel -- the noise-then-select step the per-account DP guarantee actually covers -- without index disclosure, pipeline redesign, or model-weight exposure. Generation-channel privacy (LLM output conditioned on selected documents) is a separate audit predicate that should compose with ours; we explicitly scope it out. The protocol composes generic cryptographic primitives (Merkle ledgers, ZK function-application proofs, Gaussian noise attestations) with six RAG-specific primitives (embedder commitment, index-content vector commitment, per-account query ledger, noise-then-select attestation, cross-tenant containment proof, coalition-size estimator) and supports both closed-form audit bounds and R\'enyi-DP moments-accountant tracking.