MemLeak: Cross-User Semantic Leakage in Multi-Tenant AI Agent Memory

arXiv cs.AIOctober 6, 2026en

arXiv cs.AI

AI Global Wire

arXiv:2610.04195v1 Announce Type: new Abstract: Personal AI agents in enterprise multi-tenant deployments share a common vector store for long-term memory. Shared embedding spaces create a surface for cross-user memory leakage: a user's query can retrieve semantically adjacent memories belonging to another user through ordinary cosine-similarity retrieval, without any exploit. We formalize this as cross-user admissibility failure and evaluate it across six experiments, plus follow-up ablations, under both sparse (TF-IDF) and production-faithful (MiniLM-L6-v2) retrieval. Non-adversarial, incidental leakage reaches 70--100\% under pooled {same-team} retrieval; adversarially crafted memories ac

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