Medium Risk

create_frontend_deployment

Create a frontend deployment and get an upload URL. Upload your built frontend as a zip file to the returned URL, then use manage_frontend (action: "start_deployment") to trigger the deploy. Steps: 1. Call this tool to get an upload URL 2. Upload your zip file to the URL (e.g. curl -X PUT "{uploa...

Risk signalsBulk/mass operation — affects multiple targets

Part of the Mcp server.

create_frontend_deployment can modify Mcp data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use create_frontend_deployment to create or modify resources in Mcp. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call create_frontend_deployment repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Mcp.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "create_frontend_deployment": {
      "limits": [
        {
          "counter": "create_frontend_deployment_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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These attack patterns abuse exactly the kind of access create_frontend_deployment gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so create_frontend_deployment only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the create_frontend_deployment tool do? +

Create a frontend deployment and get an upload URL. Upload your built frontend as a zip file to the returned URL, then use manage_frontend (action: "start_deployment") to trigger the deploy. Steps: 1. Call this tool to get an upload URL 2. Upload your zip file to the URL (e.g. curl -X PUT "{uploadUrl}" -H "Content-Type: application/zip" --data-binary @frontend.zip) 3. Call manage_frontend (action: "start_deployment") with the returned deployment_id Example: Input: { app_id: "app_abc123", framework: "react-vite" } Output: { deployment_id: "uuid-1234", uploadUrl: "https://...", expiresIn: 900, maxSizeBytes: 104857600 } Prerequisites: - App must exist (use init_app to create) Free plan: 1 deployment per app. Deploying again automatically replaces the previous deployment (no need to delete first). Starter+: unlimited deployments. Framework options: - react-vite: React app built with Vite (zip the dist/ folder) - nextjs-static: Next.js static export (zip the out/ folder) - static: Plain HTML/CSS/JS - other: Any framework that produces static output SPA routing: For SPA frameworks (react-vite, nextjs-static, other), a _redirects file is auto-injected so all routes serve index.html. If your zip already includes a _redirects file, it is preserved. IMPORTANT — Zip file paths must use forward slashes (/), not backslashes (\). On Windows, zips created with built-in tools use backslashes, which causes all files to be served as text/html (breaking JS/CSS with MIME errors). On Windows use Git Bash or WSL to run: cd dist && zip -r ../frontend.zip . Common errors: - RESOURCE_NOT_FOUND: App doesn't exist Idempotency: Not idempotent — creates a new deployment each time (replaces existing on free plan). Your frontend will be deployed to https://<app-name>.butterbase.dev. Next steps: Upload your zip to the returned URL, then call manage_frontend (action: "start_deployment").. It is categorised as a Write tool in the Mcp MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on create_frontend_deployment? +

Register the MCP server in PolicyLayer and add a rule for create_frontend_deployment: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Mcp. Nothing to install.

What risk level is create_frontend_deployment? +

create_frontend_deployment is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit create_frontend_deployment? +

Yes. Add a rate_limit block to the create_frontend_deployment rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block create_frontend_deployment completely? +

Set action: deny in the PolicyLayer policy for create_frontend_deployment. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides create_frontend_deployment? +

create_frontend_deployment is provided by the MCP server (@butterbase/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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