This research reveals critical security vulnerabilities in Retrieval-Augmented Generation (RAG) systems through a novel poisoning attack method called 'CorruptRAG'.

• RAG systems designed to enhance LLM outputs remain highly vulnerable to strategic poisoning of their knowledge databases
• Attackers can successfully manipulate RAG outputs with minimal access and resources
• The paper demonstrates practical attack scenarios with concerning success rates
• Results highlight urgent need for robust defense mechanisms in production RAG systems

As organizations increasingly deploy RAG to improve LLM reliability, these findings underscore the critical importance of security auditing before implementation in sensitive business applications.

Practical Poisoning Attacks against Retrieval-Augmented Generation