The Action Firewall for AI agents

Govern every AI-agent action. Prove every outcome.

AgenticDome sits between your AI agents and your business systems, checking each connected action against policy and blocking it before it happens when policy says no.

No account or API key. The simulation runs without network access after installation.

Local SDK demo output: the refund hijack would execute without a policy decision; AgenticDome returns BLOCKED and the simulated tool would not execute.
Actual output excerpt from the local SDK simulation. No live payment or framework execution. Run this example →
The action-authority gap

Valid access. Wrong action.

An agent can have the right credentials and still send money to the wrong account, export the wrong records, or follow instructions hidden in a document. Access alone cannot answer whether this exact action should happen now.

01 · IDENTITY

Who can connect?

Your identity and access controls authenticate users and workloads, grant permissions, and limit which systems they can reach. Those controls remain in place.

02 · CONTEXT

What are they trying to do?

Agents interpret prompts, retrieved documents and other agents’ requests. The selected tool, its arguments and its destination can drift from the original task.

03 · ACTION

Should it happen now?

The Action Firewall evaluates the actor, purpose and final request while the application can still stop it. A valid token does not settle that decision.

Read the case for action security →

How it works

One decision before business impact.

01

Connect the boundary

Attach an SDK, plugin or gateway where your agent calls a tool or business system. AgenticDome Copilot guides onboarding and helps you work through setup and verification.

02

Evaluate

Check the final action against your organisation’s policy, using identity, purpose, tool arguments, destination and delegation context supplied by the integration.

03

Enforce and evidence

Apply the decision before the operation runs. Retain the decision and the available outcome evidence so security and operations teams can review what happened.

Explore the platform and deployment options →

Where it plugs in

Your agents. Your stack. One action policy.

Explore 17 framework, SDK and runtime integration paths. Each guide explains where to attach the decision and what to test before production.

python -m pip install agenticdome-python-sdk
agenticdome-demo --framework crewai --scenario refund_hijack

The demo uses local simulated actions. Installation needs network access; running the simulation does not. Live enforcement requires a tenant connection and a tested application boundary.

Browse all integrations →

Why action security matters now.

230K+

Organisations had used Copilot Studio by April 2025. Microsoft earnings report

97M+

Monthly MCP SDK downloads reported in December 2025. MCP project report

OWASP Top 10

A dedicated 2026 risk framework for agentic applications. Read the OWASP publication

Independent industry context. These organisations are not presented as AgenticDome customers or endorsers.

Who it’s for

Bring agents into production with a clear decision point.

Security leaders

Put business policy before tool execution and establish a clear boundary your team can test and review.

Action security →

Developers

Keep your framework. Start locally, attach a decision to one tool, and verify allowed and blocked paths.

Developer workflows →

Platform teams

Apply consistent action decisions across MCP tools, Microsoft agents and delegated workflows.

Platform governance →

Risk and governance

Connect the requested action, policy decision and outcome evidence to the workflow under review.

Evidence and oversight →

See the decision before the action.

Try a local scenario, then bring your workflow to a deployment review. Start with one agent and one tool, and see exactly where the action can be stopped.