gpu-infrastructure-security

What problem does it solve?

GPU infrastructures often run multiple workloads on shared GPUs, leading to VRAM residues, non-isolated CUDA contexts, and potential credential exposure. This Skill provides guidance to identify, mitigate, and validate isolation gaps to reduce cross-tenant data leakage and privilege escalation in GPU compute environments.

Core Features & Use Cases

• VRAM isolation checks: verify memory is cleared before releasing GPU allocations and workloads initialize VRAM explicitly.
• Credential isolation and IMDS hardening: ensure credentials aren’t leaked via instance metadata and limit cloud credentials exposure.
• Deployment governance: enforce tenancy policies, auditing, and patching cadences for GPU drivers and firmware.
• Use Case: In a multi-tenant cloud cluster, apply these controls to prevent a following workload from reading remnants of a previous job’s activations or weights.

Quick Start

Audit GPU tenancy to ensure VRAM isolation and IMDS hardening on all GPU nodes.