{
  "id": "nvidia-gpu-operator-kubernetes-hardening",
  "name": "NVIDIA GPU Operator on Kubernetes Hardening",
  "type": "skill",
  "provider": "nvidia",
  "harnesses": [
    "codex",
    "copilot",
    "claude-code",
    "cursor",
    "gemini",
    "kiro"
  ],
  "summary": "Review NVIDIA GPU Operator on Kubernetes \u2014 device plugin, MIG manager, node feature discovery, time-sliced GPUs, container toolkit, securityContext posture, and namespace tenancy boundaries.",
  "source_type": "original",
  "official_docs": [
    "https://www.nvidia.com/en-us/learn/certification/",
    "https://docs.nvidia.com/ai-enterprise/",
    "https://docs.nvidia.com/datacenter/cloud-native/gpu-operator/latest/",
    "https://docs.nvidia.com/nim/",
    "https://docs.nvidia.com/dcgm/",
    "https://docs.nvidia.com/networking/",
    "https://docs.nvidia.com/nemo-framework/"
  ],
  "security_notes": "Tenant workloads with privileged:true escalate across the GPU Operator boundary. Time-sliced GPUs shared across namespaces without admission gating are a side-channel and noisy-neighbor risk. Tag-pulled GPU Operator images allow silent rollback to compromised versions.",
  "last_verified": "2026-05-10",
  "path": "skills/nvidia/nvidia-gpu-operator-kubernetes-hardening/",
  "category": "platform",
  "certifications": [],
  "author": "github: VincentChuWaiChow",
  "version": "0.1.0"
}