Adversarial AI Defense and Red Teaming

Your AI models are systematically hardened against known attack vectors like data poisoning, evasion, and prompt injection. We deliver a security-certified model artifact with a detailed threat matrix, enabling deployment with confidence in contested environments.

Receive a comprehensive, actionable report detailing your AI system's vulnerabilities, prioritized by exploitability and potential mission impact. This includes specific remediation steps and code-level fixes, not just high-level findings.

Move beyond a point-in-time audit. We establish a continuous adversarial testing program, simulating novel attack techniques and monitoring for model drift or new vulnerabilities, ensuring your defenses evolve with the threat landscape.

We design and implement a resilient MLOps pipeline with built-in adversarial detection layers, secure model serving, and automated rollback capabilities. This ensures operational integrity even under active attack conditions.

Your engineering and security teams gain hands-on experience through tailored adversarial AI war-gaming exercises. We transfer knowledge on attack methodologies and defensive countermeasures, building internal expertise.

Our service delivers the evidence and documentation required for compliance with frameworks like NIST AI RMF, ISO/IEC 42001, and upcoming EU AI Act mandates for high-risk systems. Achieve audit readiness for national security contracts.

We conduct systematic security assessments using the MITRE ATLAS framework to identify vulnerabilities in your AI systems, including data poisoning, model evasion, and prompt injection attacks specific to defense applications.

We implement defensive techniques like adversarial training, input sanitization, and ensemble methods to fortify your mission-critical models against manipulation, ensuring reliable performance under attack.

Move beyond one-time audits with our ongoing red teaming program. We simulate advanced persistent threats (APTs) to continuously probe your AI deployment, providing real-time alerts and mitigation strategies.

We integrate security-first practices into your entire MLOps pipeline—from secure data curation and model training to hardened deployment and monitoring—ensuring governance and compliance from inception.

We specialize in securing complex AI agent networks and multi-agent systems against novel threats like goal hijacking and inter-agent manipulation, which are critical for autonomous planning and logistics. Learn more about our Multiagent Systems (MAS) Architecture.

Protect sensitive model weights and inference data with hardware-based Trusted Execution Environments (TEEs). We deploy AI within encrypted memory enclaves, securing data in use for the most classified workloads. Explore our Confidential Computing for AI Workloads service.