LLM Graph Memory Selection Integrity

Arxiv pdf 2025-12-10T00:00:00
arXiv Paper — PDF not available. Only the Executive Summary is available here. To read or download the full paper, visit the arXiv abstract page.

Abstract

Agent memory is moving to graphs, and the provenance defenses now being built for it all check one thing: the provenance of the records an agent retrieves. We show that this entire class of defense is blind by construction. A longterm graph memory runs a global selection step over writable graph structure, so structure that an untrusted principal writes changes which authenticated facts are selected while the cited evidence stays fully authenticated; faithful information-flow control (IFC), checking the provenance of what the reader uses (all of it authenticated), makes the byte-identical decision to no defense at all, across document-QA substrates and real multisession agent memory. In the most consequential instance, a no-source structural write silently misdirects 28 irreversible ledger transfers over 499 live actions: faithful IFC permits every one, and AUTHSELECT prevents every one. We then characterize exactly which memories are exposed: a selector admits the channel when its structural term can reallocate an (1) share of top- k membership past a selected facts margin. Personalized PageRank can, since a sourceless write reroutes conserved random-walk mass; a content-fixed reranker cannot, and Graphitis node-distance, which leans on structure more than PageRank does, stays immune. Reallocatability, not reliance, is the predictor. We prove the immune case in general and the open case under a chokepoint condition we verify. Closing the channel forces any provenance defense to recompute selection on the authenticated subgraph, which is what AUTHSELECT does, at zero over-block and 23% latency.

Loading executive summary...

LINK COPIED TO CLIPBOARD