Right Facts, Wrong Rule: Scope-Transfer Poisoning of Retrieval-Augmented Generation
Scope-transfer poisoning exploits RAG systems by causing correctly retrieved rules to be applied outside their valid context — a subtle manipulation that standard factual-accuracy checks will not catch.
Summary written by editorial AI · Source link below
arXiv:2609.35155v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) systems use external documents for facts and rules that guide answers. We study rule-scope misapplication, where a rule valid within its documented scope is applied to a question outside that scope. Correct facts can then support an incorrect answer even when the rule's boundary is visible. This exposes the limits of document-validity checks. We introduce LENS (Local Evidence, Non-local Steering), an LLM-ag
Editorial Analysis
Enterprises relying on RAG for compliance, legal, or operational decision support face manipulation risks that go beyond simple factual poisoning and require scope-aware validation.
Implement scope-boundary validation in RAG pipelines that verifies a retrieved rule's applicability to the specific query context before generating an answer.
RAG-based AI decision support can be subtly manipulated by feeding correct information applied in wrong contexts.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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