rag-exploitation

A security team can identify and quantify RAG system vulnerabilities by applying tests across knowledge bases, retrieval pipelines, and prompt handling to prevent unsafe outputs and data leakage. Threat modeling maps attack surfaces including KB poisoning, retrieval manipulation, and context injection.

To test your RAG system for prompt injection vulnerabilities, apply predefined attack scenarios across knowledge bases, vector stores, and prompt handling to validate safeguards and prevent unsafe outputs. The testing harness executes simulated and production-like deployments to identify context injection flaws.

Yes, you can run RAG exploitation tests against a live deployment to confirm prompt safety, access controls, and audit trails. The security test harness applies predefined attack scenarios to validate defenses, safeguards, and monitoring in production-like environments.

Running RAG exploitation tests requires standard Python tooling along with the included scripts, references, and assets to execute tests and generate actionable results. No external dependencies are required beyond the standard Python environment.

The best way to secure a retrieval pipeline against knowledge base poisoning is threat modeling your RAG architecture to map attack surfaces, then applying practical testing with predefined attack scenarios to validate defenses, safeguards, and monitoring. This approach identifies and quantifies vulnerabilities effectively.

Testing retrieval manipulation in simulated environments may not capture all production-like deployment variables affecting access controls and audit trails. The harness covers simulated and production-like states, but complex live integrations require validating prompt safety and monitoring directly.