Medium Risk

qnevt_fair_select

Pick 1 or more items fairly from a list using the requested entropy_source, defaulting to server_csprng via auto. Generates proof_url and proof_json_url that should be shared with the user.

Part of the QnEvt Verifiable Randomness MCP server.

qnevt_fair_select can modify QnEvt Verifiable Randomness MCP 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 qnevt_fair_select to create or modify resources in QnEvt Verifiable Randomness MCP. 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 qnevt_fair_select 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 QnEvt Verifiable Randomness MCP.

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

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

See the full QnEvt Verifiable Randomness MCP policy for all 7 tools.

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

Pick 1 or more items fairly from a list using the requested entropy_source, defaulting to server_csprng via auto. Generates proof_url and proof_json_url that should be shared with the user.. It is categorised as a Write tool in the QnEvt Verifiable Randomness MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on qnevt_fair_select? +

Register the QnEvt Verifiable Randomness MCP server in PolicyLayer and add a rule for qnevt_fair_select: 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 QnEvt Verifiable Randomness MCP. Nothing to install.

What risk level is qnevt_fair_select? +

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

Can I rate-limit qnevt_fair_select? +

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

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

qnevt_fair_select is provided by the QnEvt Verifiable Randomness MCP server (https://qnevt.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every QnEvt Verifiable Randomness MCP tool call.

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