Medium Risk

update_checkout

Update fields on a Shopify checkout session. UCP-canonical dev.ucp.shopping.checkout.update_checkout — Curie's wrapper performs a PUT-semantics-safe diff (fetches current state, merges your partial input, forwards the full payload) so omitting a field doesn't silently delete it. Set clear_fields[...

Part of the Curie Commerce server.

update_checkout can modify Curie Commerce 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 Curie Commerce. 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 Curie Commerce.

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"
        }
      ]
    }
  }
}

See the full Curie Commerce policy for all 29 tools.

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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? +

Update fields on a Shopify checkout session. UCP-canonical dev.ucp.shopping.checkout.update_checkout — Curie's wrapper performs a PUT-semantics-safe diff (fetches current state, merges your partial input, forwards the full payload) so omitting a field doesn't silently delete it. Set clear_fields[] to explicitly clear values.. It is categorised as a Write tool in the Curie Commerce 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 Curie Commerce 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 Curie Commerce. 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 Curie Commerce MCP server (https://chat.curie.app/api/mcp/global). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Curie Commerce tool call.

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