Private AI Sandboxing

Private AI Sandboxing (without the black box)

AI sandboxing is uniquely difficult because AI workloads can have agency (in plain English: it can do things on its own). Therefore, the sandbox must address agency.

What Is a Sandbox?

A sandbox is a highly controlled place to run AI.

In AI, a sandbox limits what the model runtime can see, change, start, and talk to. It gives teams a safer way to evaluate or serve models before sensitive systems and data are exposed.

What It Controls

Files and model weights the runtime can reach.
Network paths and communication channels.
Process behavior, permissions, and runtime boundaries.
Evidence about what was allowed, blocked, or halted.

Why It Matters

Models can arrive with unknown code, dependencies, or configuration risk.
Internal data may require stricter controls than public chatbot use.
Enterprise teams need proof, not just a claim that AI was contained.
Different models need different levels of isolation and oversight.

What Is Blockhouse?

Blockhouse is nFOX's kernel-level sandbox for AI workloads.

Blockhouse places model runtimes inside a controlled operating boundary on hosts you choose. Attempts to step outside approved files, network paths, process scope, or runtime policy are blocked, halted, and recorded.

01 Kernel-Level Misbehavior Prevention

Blockhouse enforces boundaries below the application layer, not just in a wrapper around the model.

02 Controlled Communication

Model traffic moves through monitored paths instead of unmanaged network access.

03 Operating Evidence

Sandbox status, approved access, halts, and runtime decisions are recorded for review.

FAQ

Common AI sandboxing questions.

Q Is a sandbox the same as a container?

No. Containers like Docker are very useful, but they are general-purpose isolation tools with a broad attack surface. We focus on tight AI sandboxing that derives control directly from operating-system primitives.

Q Can sandboxed AI run without Internet access?

Yes. Some internal models do specific domain work and may never need Internet access. The right control posture depends on the model and workload. With nFOX Blockhouse, even Internet-connected AI goes through a single monitored channel called Porthole.

Q What happens when a model misbehaves?

The runtime halts immediately. That halt becomes a clear operational event, recorded with evidence for review.

Q Can we use our own hardware and engine?

Yes. Whether you prefer AWS, Google Cloud, RunPod, Lambda, or your own bare-metal hosts, nFOX is designed for the hardware and inference engines your team chooses.

Q What can't you run on?

macOS and Apple Silicon are not supported today. We want to get there, but Blockhouse sandboxing depends on specific operating-system primitives. gVisor has a similar issue: it sits too far from the host OS primitives Blockhouse needs. Supported Linux CPU/GPU hosts, VMs, Docker, and Kubernetes deployments can work when the required OS controls are available.

Q Can our security team review how it works?

Yes. Corporate-grade security relies on verification, not blind trust. We can set up a technical discussion with your security team.

Next Step

Find the right sandboxing fit.

We can map your models, data sensitivity, host environment, runtime choices, and control needs against the Blockhouse sandbox.

Talk to nFOX