Cato AI Endpoint puts AI security on the endpoint, where agents and AI apps do their work. A lightweight client covers browser AI, desktop AI apps and add-ins, and the local agents employees run.

Browser AI and AI apps are also inspected inline on the network with the same AI engine, so endpoint and network AI events share one dashboard. Cato AI Endpoint is part of Cato AI Security, which also secures the AI apps and agents customers build.

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Secure browser AI, desktop AI, and coding agents together

Cato secures every type of AI on the endpoint, from web and desktop apps to local agents, with visibility and governance in one dashboard, so teams run fewer tools.

Add AI security without replacing your existing stack

Cato runs alongside the existing security stack and routes only AI application traffic to Cato. All other traffic stays on existing tools, so enterprises can add AI protection in weeks rather than months without replacing the stack.

Catch risky agents and prevent unsafe actions

Cato finds local agents and their MCP servers, tools and skills on the endpoint, before any traffic reaches Cato, and flags risky ones before they act. Shared context ties each AI interaction to the user, endpoint and data behind it, so teams fix the riskiest first.

How it works

AI Endpoint Capabilities

Discover shadow AI and agents

See the agents your organization already runs

Many security teams can’t see the AI agents running on their endpoints. Cato AI Endpoint finds the agents, along with the MCP servers and skills that extend what each agent can do. The dashboard also shows who runs each agent and on which endpoint. Agents with risky settings, such as unrestricted access to the command line, show up first, so the team knows where to start.

See each agent in use, by user and endpoint.

See the MCP servers and skills each agent connects to.

See agents with risky settings first.

Local agentsManaged endpoints

42agents found

96MCP servers and skills

6risky settings

40endpoints

Agents✓ User and endpoint identifiedRisk first

Agent	MCP servers and skills	User / endpoint	Risk
Claude Code14 MCP servers, 9 skills	14 MCP servers, 9 skills	Sam (Engineering)ENG-07	Full command-line access
Cursor11 MCP servers	11 MCP servers	Omar (Design)DESIGN-03	Writes outside the project
Codex6 MCP servers, 3 skills	6 MCP servers, 3 skills	ContractorBUILD-02	Unapproved MCP server
Claude Code8 MCP servers, 4 skills	8 MCP servers, 4 skills	Maya (Finance)FIN-22	None found

See each AI interaction in context

Know who used which AI, and with what data

Cato AI Endpoint ties each prompt, response and agent action to the user, endpoint and data behind it, so teams catch risky agents, MCP servers and skills before they act. Endpoint and network AI activity sit in one dashboard, and the same Cato AI engine inspects both.

See endpoint and network AI activity in one dashboard.

See the riskiest agents first.

AI activityLast 7 days

38users

40endpoints

6risky agents

AI interactions✓ User and endpoint identified

User	Endpoint	AI	Data	Result
Sam (Engineering)	ENG-07	Local agent	Build files to unapproved tool	Blocked
Maya (Finance)	FIN-22	Desktop AI app	Customer list	Blocked
Contractor	BUILD-02	Local agent	Source code	Monitored
Lee (Marketing)	MKT-45	Browser AI	Customer names	Anonymized

Protect agents before they act

Stop a risky tool before it runs

An engineer asks a local agent to tidy up a build, and the agent pulls in a tool the security team never approved. Cato AI Endpoint blocks that tool call on the endpoint before it runs, and the rest of the agent’s work carries on. The security team sees the user, the agent and the reason in the dashboard.

Blocks unsafe tool calls in supported local agents.

Runs on the endpoint, with no network change.

Local agentCato

> tidy up the build and fix the failing step

Reading 14 files in the build folder ...

Agent wants to run a new tool: unapproved-uploader

Tool call blockedNot on the approved list. The user, the agent and the reason are in the dashboard.

Agent carries on with the rest of the build.

Desktop AI app

Maya (Finance) · signed in to Cato

Sort this list by account size.

Pasted: customer list, 240 rows

Prompt blocked by company policyChecked when sent, and blocked before it reached the AI service.

Protect prompts and responses inline

Keep sensitive data out of AI apps

An employee pastes a customer list into a desktop AI app because the app is quicker than the browser. AI desktop apps can lock their connection to their own certificate, which stops network tools from reading the traffic. Cato AI Endpoint doesn’t act while the employee types or pastes. When the employee sends the prompt, Cato AI Endpoint checks the prompt and stops the customer list from reaching the AI service. The employee sees a pop-up saying company policy blocked the prompt. In the browser, the same rules can monitor a prompt, anonymize the sensitive data in the prompt, or block the prompt.

Controls sensitive data in prompts from desktop AI apps.

Controls sensitive data in prompts from AI add-ins in Office apps.

Controls sensitive data in prompts from browser AI.

Add AI security without rip and replace

Keep the stack you already run

Cato AI Endpoint is pushed out with the endpoint management tools IT already uses, and runs beside the existing EDR. For inline protection, only AI application traffic goes to Cato. Existing SSE, VPN and EDR keep doing their jobs, so AI protection goes live in weeks. And there’s no need to buy SASE first.

Finding local agents needs no network change.

Runs beside the EDR and keeps the EDR in place.