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Security & architecture

AI agents in your infrastructure, inside your policy.

Giving an AI agent access to production raises fair questions about data, secrecy, and control. Here is how the architecture answers them.

At a glance

What a security review needs to know.

  • Runs in your cluster

    One Helm install. No Infraware control plane, no channel back to us.

  • Read-only by construction

    Every command Virgil runs passes a gate: reads go through, anything that writes is rejected and waits for a signature. How the gate parses every command.

  • A named engineer signs every change

    The signed command runs once, as a scoped job bounded by your RBAC.

  • One record per change, in your logs

    Who approved what, on what evidence, and what ran.

  • Your model, your egress

    Your key, your provider, or in-cluster with vLLM. Once running, the only outbound calls are the model endpoint and, unless you mirror it, the executor image approved commands run in.

  • What the model sees

    The alert, the conversation, what Virgil has learned, summaries of your stack and runbooks, and the full output of the read-only commands it runs, not redacted. Leave Secrets out of the read role, or point it at a model served inside your own boundary.

The whole system · one picture

Outbound, once running: the model endpoint you configure and, unless you mirror it, the executor image. No control plane, no telemetry, no channel back to us.

Controls

Where each control lives.

Where it runs

Data, context and logs are stored within your systems.

Configurable AI provider and model options give you a range of provider risk and execution tradeoffs, including a strict on-premises configuration with the model served inside your own boundary. There is no Infraware control plane and no channel back to us: the deployment is yours, end to end. With an external model, each call carries what the model sees, listed above.

Human oversight and control granularity

Layered controls, from human-in-the-loop to automated.

Infraware provides agent security with layered controls: technical conformance balanced with human factors. Different scales of control apply, from human-in-the-loop approvals to automated actions, and the control granularity ranges from individual commands to batches or permission scopes of accounts and different permission envelopes.

Identity and access management

Named accounts, one approval each.

Engineers sign in to the console with their own accounts, local to your installation, with passwords hashed with argon2id. Every approval is made by a named account, and the audit entry carries that name.

Execution mapping

Least privilege, by mapping.

Actions that touch infrastructure execute under configurable service account and RBAC mappings. Narrowly scoped execution environments apply the principle of least privilege to every change.

Audit and accountability

What changed, who or what changed it, and under what authority.

Agent logs carry session-level traceability: what was changed, who (or what) changed it, and what authority was used. The log can be stored locally or streamed to the service or storage backend you choose.

Talk to us

Every environment has different constraints.

Book a meeting to walk through yours.