Last analyzed 9/9/2026

Language Model Security Database

Explore primary-source AI security research, evaluated models, attack techniques, and defensive evidence.

985 research findings · 1123 evaluated models

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Context-Robust RAG Poisoning

Published 2/1/2026

Analyzed 2/22/2026

Retrieval-Augmented Generation (RAG) systems are vulnerable to a robust corpus poisoning attack known as "Confundo." This vulnerability arises from the lack of pipeline awareness in standard RAG implementations, specifically regarding document ingestion (tokenization and chunking) and query variations. An attacker can exploit this by fine-tuning a Large Language Model (LLM) to function as a poison generator. Unlike traditional adversarial examples which are brittle, Confundo generates poison…

Confundo: Learning to Generate Robust Poison for Practical RAG Systems

Evaluated models: Llama 3 8B, Gemini Pro

Source: arXiv

Research methodology

Entries summarize publicly available primary-source security research. Model names reflect only systems explicitly evaluated by the cited paper, and measurements are research-reported unless independent verification is stated.