Red-team testing for AI models and chatbots
Attack your model with realistic jailbreaks, prompt injection, data leaks and tool misuse, and review the results.
Red-team testing sends realistic attacks to your model and checks whether it held up. It supports the accuracy, robustness and cybersecurity requirements of Article 15.
Run a test
- 1Choose the AI system and the provider (or a custom HTTPS endpoint for your own model).
- 2Optionally paste the system prompt you use in production, so the test attacks the real setup.
- 3Choose Run red-team suite.
Read the results
The run shows how many attacks were held off, by category: jailbreaks, prompt injection, data leaks, harmful content and tool misuse. Each attack shows the prompt, the reply and why it was judged a pass or fail.
Results come from an automated check that looks for refusals and failure signals. It can be wrong, so:
- open anything marked Needs review, read the reply and record your verdict;
- turn real failures into findings.
If any attacks get through, AI owners are notified.
Re-run after every change to the system prompt, model version or tools. Keep the runs as evidence for the robustness control.