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Simulate real-world AI attacks to strengthen your defenses through our comprehensive SDSM.AI framework methodology. Our experts conduct adversarial AI red teaming based on sophisticated threat-informed defense mapping, simulating advanced attacks such as data poisoning, model inversion, prompt injection, and API abuse that conventional security testing misses. We leverage attack graph modeling to identify critical vulnerabilities that could lead to cascading security failures. We implement fixes, harden your AI models through structural risk analysis, and train your team to recognize and prevent future threats using our Impact-Effort Matrix to prioritize defensive measures for maximum security ROI. Our remediation approach integrates seamlessly with your MLOps workflow for continuous security improvement. Think of this as a "fire drill" for your AI security, helping you stay ahead of evolving attack techniques through systematic testing and defense validation that transforms vulnerability discoveries into actionable security improvements. The program includes both immediate fixes and long-term architectural improvements based on our proprietary SDSM.AI framework.