Retrieval-augmented generation
Context-Agnostic Attack
Superseded baseline#122 of 1,179 most-superseded
Superseded — cited as a baseline and beaten by newer methods
1 papers critique it · 1 beat it on benchmarks
What papers say
Verbatim critique sentences, each from a paper that cites Context-Agnostic Attack as a baseline.
a fundamental limitation shared by these existing approaches is their reliance on the assumption that an adversary can directly manipulate a user's input query. This premise is often impractical in real-world scenarios, as it confines the attack's impact to the specific, manipulated query initiated by the attacker.
What to use instead
Recent methods in the same sub-problem, not yet superseded in the knowledge base — arXiv benchmark leaders, not vetted production recommendations.
- DiscourseFlipDiscourseFlip: An Oblique Discourse-Level Opinion Manipulation Attack against Black-box Retrieval-Augmented GenerationMay 31, 2026
- SilentRetrievalSilentRetrieval: Hijacking Retrieval-Augmented Generation via Semantically-Preserving Adversarial Data PoisoningMay 27, 2026
- Deceptive Evolutionary Jamming Attack (DEJA)Beyond Explicit Refusals: Soft-Failure Attacks on Retrieval-Augmented GenerationApr 20, 2026
- Apr 3, 2026
- Mar 12, 2026
- Feb 6, 2026
- SD-RAGSD-RAG: A Prompt-Injection-Resilient Framework for Selective Disclosure in Retrieval-Augmented GenerationJan 16, 2026
- RIPRAGRIPRAG: Hack a Black-box Retrieval-Augmented Generation Question-Answering System with Reinforcement LearningOct 11, 2025