{"data":{"id":"17103a44-1adb-4c8b-9389-45b7eae861ee","title":"Accept Changes, Reject Attacks: Robust Memory Management for LLM Agents","summary":"This research paper formalizes robustness for LLM agent memory managers, which must handle both outdated facts and memory poisoning without degrading on other inputs. The authors introduce evidence-conditioned accuracy (ECA), which also checks that selected records contain all needed evidence and are updated and attack-free. They report that existing memory systems and defenses are no more robust than an untuned manager, and that a one-shot fine-tuning recipe improves every category score and more than doubles the untuned manager's overall ECA across three backbones, though robustness remains incomplete.","solution":"N/A -- no mitigation discussed in source.","labels":["research","security"],"sourceUrl":"https://arxiv.org/abs/2610.41056v1","publishedAt":"2026-10-29T22:54:17.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["prompt_injection","rag_poisoning"],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-5-5","classifierPromptVersion":"v4","summaryPromptVersion":"v2","headline":null,"headlinePromptVersion":null,"cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"epssCheckedAt":null,"kevDateAdded":null,"advisoryAliases":null,"affectedPackagesSource":null,"affectedPackagesCheckedAt":null,"patchAvailable":null,"disclosureDate":"2026-10-29T22:54:17.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity"],"aiComponentTargeted":"agent","llmSpecific":true,"classifierConfidence":0.95,"researchCategory":"preprint","atlasIds":["AML.T0051","AML.T0070"]}}