Lineage-Aware Memory Governance: A Derivation-Gated Framework for Privacy-Preserving Column-Level Access Control in Enterprise AI Agents
Factual evidence
What the source reports
Researchers propose a derivation-gated framework for agent memory to prevent sensitive data leakage and inconsistent KPI calculations.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 7 October 2026
- Collected by OneBench
- 8 Oct 2026, 03:01 UK
Stored source excerpt
arXiv:2610.07258v1 Announce Type: cross Abstract: Enterprise AI agents that share a memory store face two unaddressed risks: sensitive data can leak through legitimately computed results…
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OneBench interpretation
Institutional assessment
So what
Shared memory stores in multi-agent deployments create unmonitored data-leakage and logic-inconsistency risks across institutional boundaries.
Do what
Review data-governance protocols with the team responsible for enterprise agent deployment before expanding shared agent memory stores.