Medium Risk

update_checkout

Set buyer email and desired site slug on a checkout session. The checkout must be in "not_ready" status. Setting requested_slug transitions status to "ready" (required before completing). Args: checkout_id: Checkout session ID from create_checkout buyer_email: Optional email — if omitted, a synth...

Part of the BorealHost server.

update_checkout can modify BorealHost 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 update_checkout to create or modify resources in BorealHost. 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 update_checkout 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 BorealHost.

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

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

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These attack patterns abuse exactly the kind of access update_checkout 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 update_checkout 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 update_checkout tool do? +

Set buyer email and desired site slug on a checkout session. The checkout must be in "not_ready" status. Setting requested_slug transitions status to "ready" (required before completing). Args: checkout_id: Checkout session ID from create_checkout buyer_email: Optional email — if omitted, a synthetic agent identity (agent-{uuid}@api.borealhost.ai) is created at completion requested_slug: Desired site identifier. Must be 3-50 chars, lowercase alphanumeric + hyphens, cannot start/end with hyphen. Must be globally unique. Returns: {"id": "uuid", "sku": "...", "plan_slug": "...", "billing_period": "monthly", "status": "ready", "buyer_email": "...", "requested_slug": "my-site", "created_at": "iso8601"} Errors: VALIDATION_ERROR: Invalid slug format or slug already taken FORBIDDEN: Missing checkout_secret NOT_FOUND: Unknown checkout_id. It is categorised as a Write tool in the BorealHost MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on update_checkout? +

Register the BorealHost MCP server in PolicyLayer and add a rule for update_checkout: 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 BorealHost. Nothing to install.

What risk level is update_checkout? +

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

Can I rate-limit update_checkout? +

Yes. Add a rate_limit block to the update_checkout 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 update_checkout completely? +

Set action: deny in the PolicyLayer policy for update_checkout. 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 update_checkout? +

update_checkout is provided by the BorealHost MCP server (pypi:borealhost-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every BorealHost tool call.

Deterministic rules across all 95 BorealHost tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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