AI infrastructure attacks are rising, but the focus of most security teams remains on prompt manipulation rather than the underlying cloud infrastructure. Real-world risk patterns show breaches originating from misconfigurations, excessive privileges, exposed endpoints, and supply chain vulnerabilities — not prompt injection. A practical four-part control framework is outlined: AI asset discovery across SaaS/PaaS/IaaS, continuous posture management, shift-left security in pipelines, and runtime protection inside containers and cloud services. The post argues that AI workloads deserve their own security category because they concentrate data, compute, and privileges at scale, and maps OWASP Top 10 LLM risks to cloud-native protection capabilities.
