Run an App Store compliance audit on a mobile app project via greenlight preflight.
AI agents invoke fleet_audit_run to trigger actions in Fleet. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool executes a compliance audit workflow on mobile app projects. While audits are typically read-heavy, the explicit verb 'Run' combined with 'greenlight preflight' indicates active execution of an external process whose side effects (audit state, compliance records, potential blocking issues) depend on the project state and audit rules.
From the tool's definition 'Run an App Store compliance audit' indicates execution of an external audit process (greenlight preflight) that triggers checks and potentially generates reports or state changes in a mobile app project.
Documented attack patterns abuse exactly the kind of access fleet_audit_run gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Fleet, and nothing reaches the server without passing your rules. This is the rule we recommend for fleet_audit_run:
{
"version": "1",
"default": "deny",
"tools": {
"fleet_audit_run": {
"limits": [
{
"counter": "fleet_audit_run_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} fleet_audit_run stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Run an App Store compliance audit on a mobile app project via greenlight preflight. It is categorised as a Execute tool in the Fleet MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Fleet MCP server in PolicyLayer and add a rule for fleet_audit_run: 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 Fleet. Nothing to install.
fleet_audit_run is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the fleet_audit_run 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 fleet_audit_run. 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.
fleet_audit_run is provided by the Fleet MCP server (wrxck/fleet). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Fleet, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
39 Fleet tools catalogued and risk-classified — across an index of 43,000+ MCP servers.