RAG-redteam, red-team your RAG pipeline for injection and leakage in CI (github.com)

The recent launch of `rag-redteam` introduces a critical security tool for retrieving and generating (RAG) systems, aimed at safeguarding them against vulnerabilities such as prompt injection and data leakage. This tool operates similarly to a red team exercise, actively probing RAG pipelines for exploitable weaknesses that existing evaluations and LLM scanners overlook. Instead of merely assessing response quality or probing the model itself, rag-redteam tests the entire retrieval pipeline by simulating attacks that could plant harmful instructions or access confidential source documents, failing builds if vulnerabilities are detected. This development is significant for the AI/ML community as it raises awareness around the security aspects of RAG systems, which face unique risks not captured by conventional means. The tool features multiple probing mechanisms, including indirect prompt injection and context leakage, with a clear reporting structure that exposes vulnerabilities through a deterministic detection method utilizing unique canary tokens. By incorporating `rag-redteam` into Continuous Integration (CI) workflows, organizations can establish a defense against rising exploits, ensuring that insecure changes do not make it to production. With increasing concerns over data privacy and model security, this tool aims to bolster the integrity of AI systems, setting a new standard for security practices in the field.