This vulnerability involves a data poisoning attack targeting Retrieval-Augmented Generation (RAG) systems. The attack manipulates the retriever component by injecting a compromised document into the dataset utilized by the embedding model. The injected document is altered to contain inaccurate and misleading information. Upon activation, the system retrieves this poisoned document, leading to the generation of responses that are misleading, biased, and unfaithful to user queries. Mitigation steps: **For AI Developers:** * Implement retrieval refinements, including enhanced ranking algorithms and data consistency checks. * Utilize metadata for effective management of the knowledge base. **For Model Trainers/Fine-tuners:** * [No applicable steps provided for this category]