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A recent Bloomberg study reveals potential security vulnerabilities arising from the use of Retrieval-Augmented Generation (RAG) in Large Language Models (LLMs). While RAG aims to improve LLM accuracy and trustworthiness, the research indicates that its implementation can inadvertently introduce new security risks, potentially compromising enterprise AI systems. The findings suggest that deploying RAG may not always enhance the safety of LLMs as intended, and further investigation is warranted to mitigate these emerging threats. More comprehensive information is available in the full Bloomberg report.