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bighub_actions_dry_run

Dry-run action evaluation (non-persistent) via /actions/evaluate with dry_run=true.

Risk signalsAccepts raw HTML/template content (payload)

Part of the BIGHUB server.

bighub_actions_dry_run can trigger actions in BIGHUB, 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 bighub_actions_dry_run to trigger processes or run actions in BIGHUB. 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.

bighub_actions_dry_run 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": {
    "bighub_actions_dry_run": {
      "limits": [
        {
          "counter": "bighub_actions_dry_run_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full BIGHUB policy for all 125 tools.

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

Dry-run action evaluation (non-persistent) via /actions/evaluate with dry_run=true.. It is categorised as a Execute tool in the BIGHUB MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on bighub_actions_dry_run? +

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

What risk level is bighub_actions_dry_run? +

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

Can I rate-limit bighub_actions_dry_run? +

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

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

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

Enforce policy on every BIGHUB tool call.

Deterministic rules across all 125 BIGHUB tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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