Map GoldenCheck findings to recommended GoldenFlow transforms. Bridge tool for Check-to-Flow handoff.
Part of the GoldenFlow server.
Free to start. No card required.
AI agents use select_from_findings to create or modify resources in GoldenFlow. 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 select_from_findings 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 GoldenFlow.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"select_from_findings": {
"limits": [
{
"counter": "select_from_findings_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full GoldenFlow policy for all 10 tools.
These attack patterns abuse exactly the kind of access select_from_findings 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.
Map GoldenCheck findings to recommended GoldenFlow transforms. Bridge tool for Check-to-Flow handoff.. It is categorised as a Write tool in the GoldenFlow MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the GoldenFlow MCP server in PolicyLayer and add a rule for select_from_findings: 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 GoldenFlow. Nothing to install.
select_from_findings 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 select_from_findings 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 select_from_findings. 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.
select_from_findings is provided by the GoldenFlow MCP server (goldenflow). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 10 GoldenFlow 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.