Medium Risk

open_dive_dashboard

Open the NodeBench UI Dive dashboard in a browser. Shows the full flywheel cycle:

Part of the Nodebench server.

open_dive_dashboard can modify Nodebench 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 open_dive_dashboard to create or modify resources in Nodebench. 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 open_dive_dashboard 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 Nodebench.

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

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

See the full Nodebench policy for all 724 tools.

Get this rule live on your own Nodebench 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 open_dive_dashboard gives an agent. Each links to the full case and the policy that stops it:

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

Open the NodeBench UI Dive dashboard in a browser. Shows the full flywheel cycle:. It is categorised as a Write tool in the Nodebench MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on open_dive_dashboard? +

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

What risk level is open_dive_dashboard? +

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

Can I rate-limit open_dive_dashboard? +

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

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

open_dive_dashboard is provided by the Nodebench MCP server (nodebench-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Nodebench tool call.

Deterministic rules across all 724 Nodebench 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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