AI Security Is an Engineering Problem: NVIDIA Outlines Defense Strategies Across the Agent Stack

NVIDIA has published a technical perspective arguing that AI security should be treated as a structured engineering discipline rather than an afterthought, with specific defense strategies mapped to each layer of a modern AI agent stack. The piece covers threat surfaces including prompt injection, model extraction, data poisoning, and output manipulation, and outlines mitigations developers can apply at the model, orchestration, and infrastructure layers. Given the same-day news of the Muse 0-day and Gemini breach confirmations, this framing lands with particular urgency and practical relevance. For developers shipping agentic systems, the layered defense model provides a checklist-style framework for auditing existing pipelines against known attack classes. This is essential reading for any team that has moved beyond prototype and into production AI agent deployments.