High Risk →

mathematical_proof

Prove mathematical statements via DeepSeek

Risk signalsSends prompts to external DeepSeek API

Part of the Deepseek server.

mathematical_proof can trigger actions in Deepseek, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents invoke mathematical_proof to trigger processes or run actions in Deepseek. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

mathematical_proof can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "mathematical_proof": {
      "limits": [
        {
          "counter": "mathematical_proof_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Deepseek policy for all 15 tools.

Get this rule live on your own Deepseek server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access mathematical_proof 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 mathematical_proof only ever does what you allow.

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Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the mathematical_proof tool do? +

Prove mathematical statements via DeepSeek. It is categorised as a Execute tool in the Deepseek MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on mathematical_proof? +

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

What risk level is mathematical_proof? +

mathematical_proof is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit mathematical_proof? +

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

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

mathematical_proof is provided by the Deepseek MCP server (@arikusi/deepseek-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Deepseek tool call.

Deterministic rules across all 15 Deepseek 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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