Medium Risk

save_file

Finalize a file. Full replacement - call get_file first to update existing files. Required: uuid, name, type. For significant changes, include context fields: summary, rationale, references, decisions.

Part of the Stellify server.

save_file can modify Stellify 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_file to create or modify resources in Stellify. 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_file 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 Stellify.

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

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

See the full Stellify policy for all 50 tools.

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

Finalize a file. Full replacement - call get_file first to update existing files. Required: uuid, name, type. For significant changes, include context fields: summary, rationale, references, decisions.. It is categorised as a Write tool in the Stellify 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_file? +

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

What risk level is save_file? +

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

Can I rate-limit save_file? +

Yes. Add a rate_limit block to the save_file 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_file completely? +

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

save_file is provided by the Stellify MCP server (Stellify-Software-Ltd/stellify-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Stellify tool call.

Deterministic rules across all 50 Stellify tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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