Continuous red teaming¶
Once your test cases are generated, refined with business knowledge, and automatically executed, it is essential to maintain them over time. As AI applications interact with real-world data, new vulnerabilities emerge, and your test dataset may miss critical test cases. New vulnerabilities can arise when:
Company content changes: Updates to the RAG knowledge base or modifications to the company’s products.
News evolves: Events not included in the foundational model’s training data (e.g., the 2024 Olympic Games, a new CEO appointment, U.S. elections, etc.).
Cybersecurity research advances: Newly discovered prompt injections or other vulnerabilities identified by the scientific community.
New model versions are introduced: Changes in prompts, updates to foundational models, or modifications in AI behavior.
Upon request, Giskard can offer a continuous red teaming service that constantly enriches your datasets with new test cases. These new test cases are generated from:
Internal data (e.g., RAG knowledge base)
External data (e.g., social media, news articles)
Security research
