{"data":{"id":"9ef80d8e-aa2f-40a2-84c6-bd114c13b5a3","title":"Factual Yet One-Sided: Stance Poisoning and Evidence Balancing in Retrieval-Augmented Generation","summary":"This research shows that RAG systems take on the stance of retrieved documents: at a mean poisoning share of 18.9% in ProCon documents, four generation models from different vendors shifted toward the poisoning direction, and the shift grew monotonically across four concentration levels. The authors propose a Stance-Balancing Middleware between retriever and generator, combining stance detection, fixed balancing (2 supporting, 2 opposing, 1 neutral) and a debiasing prompt, with no extra LLM calls. The method reduced stance deviation by an estimated 0.106 to 0.350 across eight settings, with residual pro-poisoning estimates of +0.045 to +0.063 in some cross-model results.","solution":"The source proposes a Stance-Balancing Middleware positioned between the retriever and the generator, consisting of stance detection, fixed balancing (2 supporting + 2 opposing + 1 neutral), and a debiasing prompt, without additional large language model calls.","labels":["security","research"],"sourceUrl":"https://arxiv.org/abs/2610.34294v1","publishedAt":"2026-10-25T13:50:10.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["other"],"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":"2026-10-25T13:50:10.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["integrity"],"aiComponentTargeted":"rag","llmSpecific":true,"classifierConfidence":0.93,"researchCategory":"preprint","atlasIds":null}}