Medium Risk

chieflab_retry_blocked_action

P13 — re-check a blocked publishAction's connector readiness. Returns whether the channel is now ready (so the agent can re-fire chiefmo_publish_approved_post / chiefmo_send_approved_email) or still blocked with the up-to-date connect path. USE WHEN the user has just connected a missing provider ...

Part of the ChiefLab server.

chieflab_retry_blocked_action can modify ChiefLab 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 chieflab_retry_blocked_action to create or modify resources in ChiefLab. 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 chieflab_retry_blocked_action 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 ChiefLab.

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

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

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

P13 — re-check a blocked publishAction's connector readiness. Returns whether the channel is now ready (so the agent can re-fire chiefmo_publish_approved_post / chiefmo_send_approved_email) or still blocked with the up-to-date connect path. USE WHEN the user has just connected a missing provider and the agent needs to know if the action can fire.. It is categorised as a Write tool in the ChiefLab MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on chieflab_retry_blocked_action? +

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

What risk level is chieflab_retry_blocked_action? +

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

Can I rate-limit chieflab_retry_blocked_action? +

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

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

chieflab_retry_blocked_action is provided by the ChiefLab MCP server (@chieflab/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 ChiefLab tool call.

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