Medium Risk

sub_issue_id

The ID of the sub-issue to add. ID is not the same as issue number (number, required)

Part of the GitHub server.

sub_issue_id can modify GitHub 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 sub_issue_id to create or modify resources in GitHub. 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 sub_issue_id 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.

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

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

See the full GitHub policy for all 256 tools.

Get this rule live on your own GitHub 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 sub_issue_id 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 sub_issue_id 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 sub_issue_id tool do? +

The ID of the sub-issue to add. ID is not the same as issue number (number, required). It is categorised as a Write tool in the GitHub MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on sub_issue_id? +

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

What risk level is sub_issue_id? +

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

Can I rate-limit sub_issue_id? +

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

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

sub_issue_id is provided by the GitHub MCP server (oci:ghcr.io/aifity/omnigit-mcp:0.5.0). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every GitHub tool call.

Deterministic rules across all 256 GitHub tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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