Medium Risk

save_field_mapping

Teach AutoApply how to answer a recurring question. Provide the label pattern (partial match is fine) and the answer to always use. Example: pattern='located in san francisco', value='Yes'. Next time fill_known_fields sees that label, it fills it automatically.

Part of the Autoapply server.

save_field_mapping can modify Autoapply 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 save_field_mapping to create or modify resources in Autoapply. 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 save_field_mapping 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 Autoapply.

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

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

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

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so save_field_mapping 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 save_field_mapping tool do? +

Teach AutoApply how to answer a recurring question. Provide the label pattern (partial match is fine) and the answer to always use. Example: pattern='located in san francisco', value='Yes'. Next time fill_known_fields sees that label, it fills it automatically.. It is categorised as a Write tool in the Autoapply MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on save_field_mapping? +

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

What risk level is save_field_mapping? +

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

Can I rate-limit save_field_mapping? +

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

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

save_field_mapping is provided by the Autoapply MCP server (preetrajdeo/autoapply-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Autoapply tool call.

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