Ghosts in the GPU: Attacking the Hardware Beneath AI
Download Description:
Modern GPUs now sit at the center of AI and cloud infrastructure, where they process sensitive data, separate workloads, manage memory, and participate in confidential-computing workflows. Recent research has exposed weaknesses across VRAM integrity, GPU page tables, TLBs, schedulers, caches, unified memory, resource partitioning, and attestation. This whitepaper examines how performance-oriented GPU architecture is becoming security-sensitive and why organizations running AI infrastructure need stronger controls around isolation, memory protection, workload placement, telemetry, and trust validation.
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