High Risk →

run_self_heal

Autonomous self-healing for detected drift issues. Fixes orphaned verification cycles

Part of the Nodebench server.

run_self_heal can trigger actions in Nodebench, 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 run_self_heal to trigger processes or run actions in Nodebench. 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.

run_self_heal 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": {
    "run_self_heal": {
      "limits": [
        {
          "counter": "run_self_heal_rate",
          "window": "minute",
          "max": 10,
          "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 run_self_heal 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 run_self_heal 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 run_self_heal tool do? +

Autonomous self-healing for detected drift issues. Fixes orphaned verification cycles. It is categorised as a Execute tool in the Nodebench MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on run_self_heal? +

Register the Nodebench MCP server in PolicyLayer and add a rule for run_self_heal: 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 run_self_heal? +

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

Can I rate-limit run_self_heal? +

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

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

run_self_heal 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.

Free to start. No card required.

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

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