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Risk signalsAdmin/system-level operation
Part of the AI Success Story server.
Free to start. No card required.
AI agents use approve_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 approve_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.
{
"version": "1",
"default": "deny",
"tools": {
"approve_pending": {
"limits": [
{
"counter": "approve_pending_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full AI Success Story policy for all 7 tools.
These attack patterns abuse exactly the kind of access approve_pending gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Admin-only. Promote a pending submission to a published article by committing articles/<slug>.md to the repo via the GitHub API. Heroku auto-deploys on push. Returns commit SHA.. 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.
Register the AI Success Story MCP server in PolicyLayer and add a rule for approve_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.
approve_pending is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the approve_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.
Set action: deny in the PolicyLayer policy for approve_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.
approve_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.
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.