// USE CASE
Protecting Proprietary Weights
Stop proprietary model weights — foundation weights, trading models, customer PII — from leaving the GPU at the ioctl boundary.
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// PROPRIETARY WEIGHTS · AI LABS · FINTECH · ILLUSTRATIVE SCENARIOProtecting Proprietary Weights
Stop proprietary model weights — foundation weights, trading models, customer PII — from leaving the GPU at the ioctl boundary.
SOC 2 · TYPE IIPCI-DSSFFIECNYDFS · Part 500
Imagine an AI lab or quant desk training proprietary models on H100s — the weights are the entire business. The risk: a contractor's notebook fires a large ioctl that pulls weights off the device. The hot-path heuristic flags transfers above the configured byte threshold; a sample is forwarded to the on-host SLM, which scores risk 0–100 and returns a reason. Above threshold, the daemon writes a structured alert and (if mode = kill) SIGKILLs the offending PID before the next ioctl batch lands. No data leaves the host at any point.
// AT FLEET SCALE · ARCA NEXUS
Nexus aggregates exfil-risk scoring across every research and training host into a single fleet view. SAN-bound per-line identity means a compromised contractor box can't impersonate a peer.
Action
alert · or SIGKILL (opt-in)
Privacy
no host egress
Numbers above
design target · not measured