Medium Risk

laddro.settings.updateModel

Configure the AI provider and model for BYOK (Bring Your Own Key). Saves an encrypted API key for the chosen provider.

Risk signalsHandles credentials or secrets (apiKey)

Part of the Laddro Career server.

laddro.settings.updateModel can modify Laddro Career 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 laddro.settings.updateModel to create or modify resources in Laddro Career. 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 laddro.settings.updateModel 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 Laddro Career.

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

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "laddro.settings.updateModel": {
      "limits": [
        {
          "counter": "laddro.settings.updatemodel_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Laddro Career policy for all 18 tools.

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These attack patterns abuse exactly the kind of access laddro.settings.updateModel 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 laddro.settings.updateModel 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 laddro.settings.updateModel tool do? +

Configure the AI provider and model for BYOK (Bring Your Own Key). Saves an encrypted API key for the chosen provider.. It is categorised as a Write tool in the Laddro Career MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on laddro.settings.updateModel? +

Register the Laddro Career MCP server in PolicyLayer and add a rule for laddro.settings.updateModel: 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 Laddro Career. Nothing to install.

What risk level is laddro.settings.updateModel? +

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

Can I rate-limit laddro.settings.updateModel? +

Yes. Add a rate_limit block to the laddro.settings.updateModel 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 laddro.settings.updateModel completely? +

Set action: deny in the PolicyLayer policy for laddro.settings.updateModel. 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 laddro.settings.updateModel? +

laddro.settings.updateModel is provided by the Laddro Career MCP server (@laddro/career-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Laddro Career tool call.

Deterministic rules across all 18 Laddro Career 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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