DeepKeep Automated AI Red Teaming

DeepKeep's Automated AI Red Teaming helps organizations expose GenAI vulnerabilities across custom AI apps and AI models, through continuous context-aware attack simulation and remediation. It tests both models and custom AI applications to uncover security and trust failures such as prompt injection, data leakage, hallucinations and fairness issues. Findings are prioritized, reproducible and enriched with root-cause analysis and remediation playbooks that guide teams toward concrete fixes. Key capabilities include:

• Adversarial scenario generation to simulate realistic, real-world attack patterns.
• Dynamic multi-turn probing to expose deeper vulnerabilities beyond single-shot testing.
• Trust and quality evaluations to assess reliability and fairness alongside security.
• Root-cause analysis that identifies underlying weaknesses and provides targeted mitigation steps.
• Continuous operation with scheduled tests, CI/CD integration and event-driven re-scans.
• Bring Your Own Dataset to evaluate vulnerabilities against real business scenarios.

By combining these capabilities, DeepKeep enables security, engineering and AI teams to continuously test, harden and validate their GenAI systems, reducing the attack surface and strengthening trust in production AI.