Stealthium Flags Ghostjacking Vectors in Accelerator-Backed Neo-Clouds

Accelerator adoption for AI training and inference has outpaced security tooling built around CPU memory models. Neo-cloud providers expose high-speed video RAM and nested virtualization layers that traditional EDR cannot inspect, creating blind spots for supply-chain compromise. Januscape demonstrated the pattern by abusing virtualization nesting to resell tenant environments, a technique that scales directly to chatbot inference workloads where response latency masks anomalous GPU memory access.

Telemetry patterns from compromised accelerators show subtle deviations in DMA transfer rates and context-switch frequency that Stealthium agents correlate against baseline customer workloads. These signals precede visible model output poisoning or data exfiltration, confirming that absence of CPU-level alerts does not equal absence of execution. Sovereign AI programs relying on third-party accelerators inherit this exposure because shared-responsibility models were never extended to silicon offload paths.

Nation-state and ransomware actors already target GPU memory for model theft; the economics favor ghostjacking customer agents once neo-cloud market share exceeds 15 percent. Procurement records show CoreWeave and Nebius scaling accelerator fleets faster than observability contracts can be negotiated. Without hardware-rooted attestation for accelerator state, each new tenant increases the attack surface for undetected agent redirection.

Stealthium's approach requires integration of accelerator firmware counters into customer SOC pipelines within 90 days of deployment or the detection window closes. Expect first production incidents involving cross-tenant chatbot poisoning by mid-2025 once three or more neo-clouds reach 10k accelerator scale.