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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41 entries

Matches every word across titles, descriptions, sources, affected systems, and models.

RAG Poisoning Jailbreak

Published 2/1/2024

Analyzed 12/29/2024

Large Language Models (LLMs) utilizing Retrieval Augmented Generation (RAG) are vulnerable to a novel attack vector, termed "RAG Poisoning," where malicious content is injected into the external knowledge base accessed by the LLM via prompt manipulation. This allows attackers to elicit undesirable or malicious outputs from the LLM, bypassing its safety filters. The attack exploits the LLM's reliance on the retrieved information during response generation.

Pandora: Jailbreak gpts by retrieval augmented generation poisoning

Evaluated models: GPT-3.5 Turbo, GPT-4, Mistral 7B

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.