IdentifysecurityvulnerabilitiesinyourAIsystems,largelanguagemodels,andmachinelearningpipelines.
What Is AI Red Teaming?
AI red teaming is adversarial testing specifically designed for AI-powered applications and systems such as large language models, chatbots, and AI-driven applications. Our assessments probe how AI systems respond to malicious prompts, unexpected inputs, and adversarial manipulation techniques. The goal is to identify security vulnerabilities, unsafe behaviors, and potential for harmful outputs before they can be exploited in production environments.
Why Do You Need It?
AI security incidents and risks can be costly — from reputational damage when chatbots produce harmful content to data breaches through prompt injection attacks. Proactive AI red teaming accelerates secure deployment by identifying risks before launch, helps meet EU AI Act compliance requirements, and protects your organization against emerging threats such as prompt injection, training data leakage, and model manipulation.
What We Cover
Our AI red teaming methodology covers the full attack surface area of AI-powered applications, from prompt-level exploits to infrastructure weaknesses.
Our Methodology
AI red teaming combines two very different skills: tricking the AI model itself (prompt injection, jailbreaks, data leakage) and testing everything around it using traditional security testing methods (APIs, cloud infrastructure, plugins). We do both, in one engagement, against the whole AI stack.
security testing
Testing Lifecycle
Every AI red team engagement follows the same end-to-end testing lifecycle — understanding how your AI system is built and used, attacking the model with adversarial prompts, testing the surrounding APIs and infrastructure, and delivering a clear report with concrete fixes your engineering and MLOps teams can ship.