Provenance-Preserving Memory Firewall for LLM Agents

A recent study published on arXiv (2607.29167) presents a security solution for large language model (LLM) agents equipped with persistent memory. The research highlights a security flaw termed 'memory provenance laundering,' where unreliable external inputs can be altered during the memory consolidation process to mimic user history or workflow assistance, thus maintaining action triggers while eliminating the low-trust origin. To address this issue, the authors introduce the Provenance-Preserving Memory Firewall (PPMF), a lightweight middleware that ensures platform-maintained provenance and validates tool usage by correlating action risk with the authority of pertinent memories. Their evaluation, utilizing a schema-grounded method with established risk policies, reveals that vulnerable consolidated memories can attain significant risk levels. This paper serves as a cross-type announcement on arXiv, suggesting it may have been featured at a conference or in a journal.