WWT Launches ARMOR: A Vendor-Agnostic Framework for Secure AI
▼ Summary
– WWT has launched ARMOR, a vendor-agnostic AI security framework developed with NVIDIA and refined with feedback from Texas A&M University.
– ARMOR is designed to help organizations securely adopt AI by addressing an expanded attack surface and regulatory complexity across the full AI lifecycle.
– The framework is structured around six security domains: governance/risk/compliance, model security, infrastructure security, secure AI operations, secure development, and data protection.
– It integrates with NVIDIA’s AI Enterprise software and hardware, including NeMo Guardrails and BlueField, to provide scalable, high-performance security for AI deployments.
– ARMOR is presented as a practical, real-world solution, shaped by early adopters and aligned with industry standards like the NIST AI Risk Management Framework.
Organizations navigating the rapid adoption of artificial intelligence now have a powerful new tool to manage security and compliance. World Wide Technology (WWT) has introduced the AI Readiness Model for Operational Resilience (ARMOR), a vendor-agnostic framework designed to secure the entire AI lifecycle. Developed in collaboration with NVIDIA and refined through real-world feedback from The Texas A&M University System, ARMOR provides a comprehensive blueprint for embedding security from the initial chip design through final deployment, whether in cloud or on-premises environments. This approach directly tackles the expanded attack surface and complex regulatory demands that accompany enterprise AI initiatives.
The framework is structured around six core domains, each targeting a critical security area in today’s hybrid, AI-driven landscape. Governance, risk, and compliance (GRC) ensures AI operations adhere to regulatory mandates, internal policies, and ethical standards while managing risks across diverse environments. Model security focuses on protecting AI models from sophisticated threats like data poisoning, inversion attacks, and theft to maintain their integrity. Infrastructure security hardens the underlying hardware and network layers, including GPUs and cloud regions, against unauthorized access. Secure AI operations enables continuous monitoring and swift threat response for AI platforms within interconnected systems. The secure development lifecycle (SDLC) embeds security practices directly into the creation of AI software, addressing vulnerabilities such as prompt injection early on. Finally, data protection safeguards datasets in storage or data lakes, ensuring confidentiality and compliance without hindering innovative use.
Chris Konrad, Vice President of Global Cyber at WWT, emphasized the necessity of this integrated approach. “Security and innovation can’t sit on opposite sides of the table. True resilience demands foresight, integration, and a framework that evolves with the threat landscape. The path forward is clear; no AI without ARMOR. ARMOR helps leaders answer the tough questions before adversaries or auditors do,” he stated.
A key strength of ARMOR is its integration with NVIDIA AI Enterprise, which provides scalable tools for enterprise AI. This includes NVIDIA NeMo Guardrails for developing safer AI applications and NVIDIA NIM microservices for secure, containerized AI deployment. Furthermore, ARMOR utilizes NVIDIA BlueField and NVIDIA DOCA Argus to deliver accelerated security operations, offering real-time threat detection and distributed policy enforcement that keeps pace with high-performance AI systems.
“With AI factories scaling at an unprecedented pace, organizations need security that can keep up with the speed, complexity and sensitivity of modern AI pipelines,” said Arik Roztal, global head of AI Cybersecurity Business Development at NVIDIA. “WWT’s ARMOR, powered by NVIDIA AI, delivers the performance and protection organizations need to confidently deploy and secure AI at scale.”
The framework’s practical relevance is underscored by its development process, which incorporated critical input from early adopters like the Texas A&M University System. Their involvement helped refine the strategic domains to ensure real-world applicability across both academic and corporate settings. Adam Mikeal, CISO at Texas A&M University, noted, “ARMOR gives us a common language and structured approach for managing AI risk. It’s a practical solution for real-world AI security.”
ARMOR’s comprehensive, vendor-neutral guidance integrates governance, model protection, infrastructure security, and data protection into a single, actionable structure. It is also deeply aligned with established industry standards, including the National Institute of Standards and Technology’s (NIST) AI Risk Management Framework. According to Neil Anderson, VP and CTO of Cloud, Infrastructure, and AI Solutions at WWT, this practical foundation is what distinguishes the framework. “Organizations are in urgent need of a practical, recognized framework for securing AI deployments. What sets ARMOR apart is that it’s not just theoretical. It’s rooted in real-world applications, designed by experts, and refined through frontline engagements,” Anderson explained.
(Source: HelpNet Security)
