Medium Risk

manage_task_status

Update task status and optionally add a comment in a GitHub Project (V2)

Part of the GitHub Projects server.

manage_task_status can modify GitHub Projects 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 manage_task_status to create or modify resources in GitHub Projects. 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 manage_task_status 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 GitHub Projects.

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

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

See the full GitHub Projects policy for all 19 tools.

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

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View all 19 tools →

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

Update task status and optionally add a comment in a GitHub Project (V2). It is categorised as a Write tool in the GitHub Projects MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on manage_task_status? +

Register the GitHub Projects MCP server in PolicyLayer and add a rule for manage_task_status: 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 GitHub Projects. Nothing to install.

What risk level is manage_task_status? +

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

Can I rate-limit manage_task_status? +

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

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

manage_task_status is provided by the GitHub Projects MCP server (devassistantai/github-projects). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every GitHub Projects tool call.

Deterministic rules across all 19 GitHub Projects tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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