Medium Risk

reject_pending

Admin-only. Drop a pending submission. Reason is recorded so submission_status surfaces it to the submitter on poll.

Risk signalsAdmin/system-level operation

Part of the AI Success Story server.

reject_pending can modify AI Success Story data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

SECURE AI SUCCESS STORY →

Free to start. No card required.

AI agents use reject_pending to create or modify resources in AI Success Story. 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 reject_pending 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 AI Success Story.

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

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

See the full AI Success Story policy for all 7 tools.

Get this rule live on your own AI Success Story server in minutes. PolicyLayer enforces it on every call, before it runs.

ENFORCE ON MY AI SUCCESS STORY →

These attack patterns abuse exactly the kind of access reject_pending 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 reject_pending only ever does what you allow.

SECURE AI SUCCESS STORY →

Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the reject_pending tool do? +

Admin-only. Drop a pending submission. Reason is recorded so submission_status surfaces it to the submitter on poll.. It is categorised as a Write tool in the AI Success Story MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on reject_pending? +

Register the AI Success Story MCP server in PolicyLayer and add a rule for reject_pending: 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 AI Success Story. Nothing to install.

What risk level is reject_pending? +

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

Can I rate-limit reject_pending? +

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

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

reject_pending is provided by the AI Success Story MCP server (https://ai-success-story-20f19ed7769b.herokuapp.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every AI Success Story tool call.

Deterministic rules across all 7 AI Success Story 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.

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.