MoorAI vs Cato Networks AI Security
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Both stop a coding agent’s tool call before it runs. They differ in what leaves the device, what the decision depends on, and how much of the enterprise each reaches. Cato AI Security is Cato’s AI line on its SASE platform: AI Security for End Users, AI Security for Applications and AI Security for Agents, which includes Cato AI Endpoint, a client Cato launched on 27 October 2026. On the endpoint Cato says: “Cato AI Endpoint blocks that tool call on the endpoint before it runs, and the rest of the agent’s work carries on.” (catonetworks.com, Cato AI Endpoint) It names its scope: “Blocks unsafe tool calls in supported local agents.” (catonetworks.com, Cato AI Endpoint) and, on its AI Security page, “with enforcement for Claude Code, Cursor, and Codex.” (catonetworks.com, AI Security) MoorAI runs where the agent runs. On employee endpoints it is a PreToolUse hook inside the coding agent and an MCP stdio proxy in front of its tool servers. On AI servers it is server mode of its hook in claude -p CI jobs and Agent SDK services, @moorai/agent-sdk in the service’s own process, the moorai-serve localhost sidecar, an MCP gateway in front of remote MCP servers and a model proxy in front of model APIs. It reads the prompt, the file read into context, the shell command, the Model Context Protocol (MCP) arguments and results and the tool calls in a model’s response, and coaches, masks or blocks on what it finds.
The difference is where the judgment and the record live. Cato says its endpoint client “uses the same AI security engine that protects AI traffic inline across the Cato platform” (catonetworks.com, launch release), that “Cato executes intelligence and enforcement in the Cato PoP” (catonetworks.com, AI Security launch release), and that “Cato AI Endpoint ties each prompt, response and agent action to the user, endpoint and data behind it”. (catonetworks.com, Cato AI Endpoint) MoorAI decides on the device with no network, keeps enforcing when its console is unreachable, and sends the console a category, a risk level and a keyed hash, never the prompt or the file.
Two things this page does not state. (1) Where Cato computes an endpoint verdict. Cato says the endpoint client blocks on the device and uses the same engine as its inline traffic inspection; it does not say whether that engine runs on the device or in its cloud for the endpoint. (2) Pricing. Cato sells per-user licenses and publishes no price in the material read. Every Cato statement below is quoted from Cato’s own site or Knowledge Base, and the page is named.
The core difference is what each decision depends on and what it leaves behind: a cloud AI engine and a record of the interaction, or a check on the device and a content-free signal.
.env, is stopped at the read, and local secret values are fingerprinted as keyed one-way hashes so a command or tool call carrying one is blocked on its way out.Where MoorAI holds ground Cato does not
These rows follow from checking on the device, with nothing to send away, and from keeping content off the console.
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| MoorAI | Cato | |
|---|---|---|
| Stops a secret or PII being read into the agent’s context, at the file read | ✓context interception in the pre-tool hook | —tool-call blocking described; file reads not |
| By default only category · risk · keyed one-way hash (plus login and hostname, pseudonymised on arrival) leave the device | ✓capture tiers are opt-in, admin-enabled | ✗ties each prompt and response to user and data; retains Claude conversation logs |
| Enforces with no network path to a vendor cloud, including air-gapped | ✓cached, last-known-good, then offline default | —offline operation not described |
| Self-hosted management console for agent enforcement | ✓free to self-host, no user limit | ◐Outposts for AI Security for Applications only |
| Open source, so the data claim can be checked in code | ✓agent MIT | ✗proprietary |
| Free to start and to enforce, without talking to sales | ✓agent free; console free self-hosted, no user limit | ✗per-user licenses |
| Pre-tool hooks in Codex CLI, GitHub Copilot CLI, Gemini CLI and Factory Droid as well as Claude Code and Cursor | ✓validated end to end on Claude Code | ◐names Claude Code, Cursor and Codex |
Where Cato covers ground MoorAI does not
This list matters. Cato reaches desktop AI apps, Office add-ins, browser AI and whole sites from one platform, and ships connectors to the AI gateways and agent platforms customers already run.
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| MoorAI | Cato | |
|---|---|---|
| Prompt controls in desktop AI apps and AI add-ins in Office apps | ✗Browser Guard covers web AI prompts only | ✓Cato AI Endpoint |
| AI traffic from whole sites and offices, not only enrolled devices | ✗ | ✓SASE network |
| Connectors for existing AI gateways (LiteLLM, Kong, Portkey, TrueFoundry) | ◐its own model proxy and MCP gateway; no connector for those gateways | ✓AI Runtime Protection integrations |
| Discovery of managed agents on Bedrock, Foundry, Copilot Studio and ChatGPT | ✗ | ✓platform integrations |
| Red-team testing of the models behind an AI app | ◐local self-test of the active policy only | ✓AI Red Teaming |
Same capability, different mechanism
Both products do each of these, so the table describes how rather than scoring.
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| MoorAI does it by… | Cato does it by… | |
|---|---|---|
| Blocking a coding agent’s tool call | A PreToolUse hook in the agent’s own process, validated end to end on Claude Code. Codex CLI, Copilot CLI, Gemini CLI, Cursor and Factory Droid block through their own pre-tool hooks. The check runs on the device and needs no network. | Cato AI Endpoint, installed through hooks: “Protection before first use: Write hook configuration before a supported agent is detected, reducing the chance that the first session on a new device is outside enforcement.” (catonetworks.com blog) Cato says “the same Cato AI engine inspects both” endpoint and network AI activity. (catonetworks.com, Cato AI Endpoint) |
| Prompt injection in what a tool returns | What comes back into the agent, such as command output, MCP results and fetched pages, is scanned after the tool runs as untrusted inbound content. In Claude Code a block adds a reason next to the result, which the model still sees; it cannot un-run the tool. | Inline inspection: “It inspects each prompt and response in line, along with the results tools send back to an agent.” (catonetworks.com blog) |
| Destructive commands | Rules on the command itself and intent alignment, which flags a destructive command or credential read on a path the user’s request never named. | A detector that weighs context: “Cato’s destructive commands detector evaluates the action in context before it is executed.” (catonetworks.com blog) |
| Skills and MCP servers an agent picks up | Skill Analysis, an inventory and intent view of the skill surface an agent auto-loads, MCP server reputation scoring, and a signed MCP server and skill catalogue with a per-version scan verdict. | “The Cato AI Endpoint client gives each skill a risk finding with a block, monitor or allow recommendation.” (catonetworks.com blog) |
MITRE ATLAS, as documented. In our reading of vendor material against the 76 ATLAS techniques tagged Agentic AI, Cato’s AI Security material documents 12 of the 76, four of them with a limit on what they cover (read 29 October 2026): AI agent tool invocation, prompt injection, jailbreak, external harms, LLM data leakage, tool data poisoning, tool poisoning, data destruction through a tool, supply-chain compromise through skills, and, bounded, deploying an agent (inventory), exposed AI services (its own port-forwarding rules) and cost harvesting (spend limits). Shadow-AI discovery, data-loss rules and app control govern AI usage and earn no cell, and Cato’s Agentic Threat Prevention, sold as network threat prevention, was not scored. MoorAI documents 34. The method is in MITRE ATLAS agentic-technique coverage.
Where MoorAI is stronger. Nothing to send away. The check runs on the device, enforcement keeps working with no path to a vendor cloud, what the agent reads into its context is checked as well as what it calls, the console receives no content, the code that guarantees that is MIT, and enforcing is free on a self-hosted console.
Where Cato is stronger. Breadth from one platform. Cato covers desktop AI apps, Office add-ins, browser AI and coding agents with one client, carries whole-site AI traffic on its SASE, connects to the AI gateways and agent platforms customers already run, discovers managed agents on cloud platforms, and red-teams the models behind AI apps. For a company that already runs its traffic through Cato, that coverage comes with the network.
Which to run where. The two overlap on employee coding agents and diverge everywhere else. Cato fits a company that wants AI usage, AI apps and agents governed from the SASE it already runs, with interactions recorded centrally. MoorAI fits where content must not leave the device, where enforcement has to work offline or air-gapped, and on AI servers run with a self-hosted console. Cato documents running its client side by side with another SSE client; running Cato AI Endpoint and MoorAI’s hook in the same agent has not been tested.
Questions about MoorAI and Cato Networks AI Security
Do Cato AI Endpoint and MoorAI both block coding-agent tool calls?
Yes. Cato says Cato AI Endpoint blocks a tool call on the endpoint before it runs, for supported local agents, and names enforcement for Claude Code, Cursor and Codex, installed through the agents’ hooks. MoorAI runs as a pre-tool hook in Claude Code, validated end to end there, and in Codex CLI, GitHub Copilot CLI, Gemini CLI, Cursor and Factory Droid through their own pre-tool hooks, plus an MCP stdio proxy for any host that launches a stdio MCP server.
What data does each keep?
Cato ties each prompt, response and agent action to the user, endpoint and data behind it, its Claude Enterprise integration collects and retains conversation logs, and its AI gateway integrations send prompts, model responses and agent tool calls to Cato AI Security. MoorAI sends a category, a risk level and a keyed one-way hash by default, plus the login and hostname, which the console pseudonymises on arrival, and keeps content only if an administrator enables a capture tier.
Does either work offline or self-hosted?
Cato offers AI Security Outposts to run AI Security for Applications on-premises or in the customer’s own cloud; an offline mode is not described in the material read, nor is a self-hosted option for Cato AI Endpoint or the management console, and Cato says its AI Security runs on AWS. MoorAI’s hook, sidecar, MCP gateway and model proxy decide on the device with no network, a device whose console is unreachable keeps enforcing its cached policy, then its last-known-good policy, then the offline default, and the console is free to self-host with no user limit.
Can MoorAI and Cato run together?
Nothing in either’s public material says they conflict. Cato describes running its client beside an existing security stack and side by side with another SSE client, routing only AI application traffic to Cato. Cato then covers desktop and browser AI, whole-site traffic and AI gateways, and MoorAI decides agent actions on the device and on AI servers without sending content. Both install hooks in coding agents such as Claude Code; we have not run them together in the same agent.
Cato capabilities are taken from Cato’s own published material, checked on 29 October 2026: Cato AI Endpoint, AI Security, AI Security for Agents, Cato AI Endpoint blog, Cato AI Endpoint launch, AI Security for Claude, OWASP mapping, destructive commands, Claude Compliance API, LiteLLM integration, Integration Hub, AI Security launch, AWS competency and Getting Started with AI Security. Every quoted phrase is Cato’s. ◐ = partial: present but narrower than the other column. — = unconfirmed, not necessarily absent. MoorAI marks reflect shipped capability: hook enforcement is validated end to end on Claude Code; Codex, Copilot CLI, Gemini CLI, Cursor and Factory Droid block through their own pre-tool hooks. The agent is MIT and runs on macOS, Windows and Linux; the console is source-available under the Elastic License 2.0, free self-hosted with no user limit, and paid when hosted by MoorAI. Cato Networks is a trademark of its owner; this page is independent and is not affiliated with or endorsed by Cato Networks. Both products change, so check specifics against current documentation.