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Training Camp • Cybersecurity Glossary
Retrieval-Augmented Generation (RAG) grounds LLM answers in retrieved external documents to cut hallucination; it adds risks like data poisoning.
Retrieval-Augmented Generation (RAG) Definition: Retrieval-Augmented Generation (RAG) grounds LLM answers in retrieved external documents to cut hallucination; it adds risks like data poisoning.
Retrieval-Augmented Generation (RAG) is an AI architecture that improves large language model responses by retrieving relevant documents from an external knowledge base and supplying them as context at inference time. This grounds outputs in current, authoritative data, reducing hallucination without retraining the model. Security considerations for RAG include access control on the retrieval corpus, preventing indirect prompt injection from poisoned documents, and protecting sensitive data in vector stores.
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