When AI infrastructure becomes the target: Securing gateways and control points

Attackers are increasingly targeting exposed AI infrastructure components — such as LiteLLM gateways, RAGFlow, and Kestra workflows — treating them as high-value control planes rather than peripheral tooling. These systems often handle sensitive credentials, orchestrate workflows, and consume significant compute resources, making them attractive targets for credential harvesting and cryptomining. The root issue is that AI platforms are being deployed without the same security rigor applied to traditional enterprise infrastructure, leaving them internet-exposed with weak or default configurations. As AI adoption accelerates, security teams must recognize that every AI gateway or orchestration layer is a potential attack surface that demands hardening, access controls, and continuous monitoring.