ENTERPRISE AI SECURITY

Put AI to work.Govern every action.

WHAT IT IS. WHAT IT DOES.

AI Security is the layer that governs agent identities, tool access, and action approvals together.

For AI builders and security teams

EXAMPLE SCENARIO · THE GOAL

Let an AI agent check the health of a production system.

Operations agent · Platform team
An agent needs to do a job.

The operations agent requests a tool call to read production health metrics.

Monofor/ AI SecurityDemo environment
Requested actionmetrics.readProduction
REQUESTING AGENTrunbook-agentOwner: Platform team
CONTROL POINTMonoforIdentity & policy
TARGET TOOLMCP serverAwaiting decision
Agent identity···
Tool permission···
Human approval···
tool.call.pendingEvaluating policy
Interactive example · No real actions
THE INTENDED OUTCOME

The agent reads only permitted metrics. The access decision is recorded.

Agent identitiesTool-level permissionsHuman approval

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CONNECTED CONTROLS

Choose your goal.
See the control in action.

Identify an agent, control its tools, request approval, investigate risk, or ask about access. Select a capability to follow a working example.

WHAT DOES IT DO?

An agent identity establishes who owns an automation, which credentials it uses, and what it can access.

Explore AI agent identity

EXAMPLE SCENARIO · THE GOAL

Bring a new operations agent online with controlled access.

Identity administrator · New AI agent
Automation becomes a known identity.

Add the agent to the inventory. See which software is behind the credential in use.

Monofor/ AI SecurityDemo environment
AI AGENT · agent-042runbook-agentProduction operations
Configuring
Accountable ownerBeing configured···
CredentialsBeing configured···
Access scopeBeing configured···
Lifecycle controlTry suspending this demo agent’s access.
Interactive example · No real actions
THE INTENDED OUTCOME

An agent with a known owner, governed credentials, and defined access that can be suspended.

HOW IT WORKS

The model reasons. Monofor governs access.

Evaluate the action proposed by the agent at the identity and policy layer. Enforce authorization independently of the model.

Plan it with us
THE WORKFLOW, END TO END

Resolve the agent, its accountable owner, and the user it is acting for.

Check the tool, effective permissions, conditions, and usage budget. Request approval when required.

Keep the caller, tool, decision, and activity visible in the audit trail.

THE OUTCOME YOU ARE WORKING TOWARD

The agent reads only permitted metrics. The access decision is recorded.

CLEAR BOUNDARIES

Know what you control.

Approach AI security through identity, access, and accountability.

How does this work alongside model safety?+

Model safety addresses model output and behavior. Monofor governs the agent’s identity and access, applying identity, permission, and approval checks to tool calls. These controls complement each other.

Does every action need human approval?+

Policy determines which actions need approval. Authorized routine work can proceed; sensitive or destructive tools wait for the responsible person. Rejection, expiry, or timeout blocks the call.

How is an agent acting for a user scoped?+

On-behalf-of access uses the intersection of agent and user permissions. The agent’s own scope does not expand the represented user’s access. Call conditions and budgets are evaluated as well.

Free download

Your AI security rollout starts here.

A four-phase guide to inventory, credentials, tool controls, and response. Includes 27 practical checklist actions.

MONOFOR · AI SECURITY

Make room for AI. Keep control.

Build the right identity and access approach for your agents.

Read the story: give your AI agents identities