Medium Risk

dataset_detail

Full catalog metadata for one ČSÚ dataset by id (kod): description, keywords, indicators (ukazatele), dimension variants (variantyDimenze), selection rules, update periodicity and themes. Catalog layer only — use data_summary / get_data for the actual numbers.

Part of the Czso Cz server.

dataset_detail can modify Czso Cz 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 dataset_detail to create or modify resources in Czso Cz. 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 dataset_detail 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 Czso Cz.

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

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

See the full Czso Cz policy for all 24 tools.

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

Full catalog metadata for one ČSÚ dataset by id (kod): description, keywords, indicators (ukazatele), dimension variants (variantyDimenze), selection rules, update periodicity and themes. Catalog layer only — use data_summary / get_data for the actual numbers.. It is categorised as a Write tool in the Czso Cz MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on dataset_detail? +

Register the Czso Cz MCP server in PolicyLayer and add a rule for dataset_detail: 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 Czso Cz. Nothing to install.

What risk level is dataset_detail? +

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

Can I rate-limit dataset_detail? +

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

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

dataset_detail is provided by the Czso Cz MCP server (https://gateway.pipeworx.io/czso-cz/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Czso Cz tool call.

Deterministic rules across all 24 Czso Cz tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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