Prompt Injection Alignment Bypass
Published Analyzed Source: arXiv
Large Language Models (LLMs) integrated with external retrieval mechanisms (e.g., Retrieval-Augmented Generation (RAG), web search, or email processing) are vulnerable to Indirect Prompt Injection. This vulnerability occurs when an LLM consumes input from untrusted external sources—such as websites, code repositories, or incoming emails—that contain embedded adversarial prompts. Unlike direct injection, where the user attacks the model, here the "poisoned" data is retrieved by the system…
Breaking to Build: A Threat Model of Prompt-Based Attacks for Securing LLMs
Evaluated models: Not reported