Configure auto-scaling for the range. Args: enable: Enable or disable auto-scaling min_vms: Minimum number of VMs max_vms: Maximum number of VMs scaling_policy: Scaling policy configuration user_id: Optional user ID (admin only) Returns: Auto-scaling configuration result
AI agents use auto_scaling to create or update resources in Ludus FastMCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Ludus FastMCP environment.
This tool creates or modifies range infrastructure settings in a reversible manner. While the blast radius is significant (auto-scaling misconfiguration could cause resource exhaustion or unexpected infrastructure costs in a production cyber range), the changes can be undone by reconfiguring auto-scaling parameters. The 'admin only' user_id parameter indicates it requires elevated privileges.
From the tool's definition Tool modifies range infrastructure configuration parameters: 'enable' (toggle state), 'min_vms' and 'max_vms' (resource constraints), and 'scaling_policy' (operational rules).
Risk signalsAdmin/system-level operation
Documented attack patterns abuse exactly the kind of access auto_scaling gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Ludus FastMCP, and nothing reaches the server without passing your rules. This is the rule we recommend for auto_scaling:
{
"version": "1",
"default": "deny",
"tools": {
"auto_scaling": {
"limits": [
{
"counter": "auto_scaling_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}auto_scaling stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Configure auto-scaling for the range. Args: enable: Enable or disable auto-scaling min_vms: Minimum number of VMs max_vms: Maximum number of VMs scaling_policy: Scaling policy configuration user_id: Optional user ID (admin only) Returns: Auto-scaling configuration result. It is categorised as a Write tool in the Ludus FastMCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Ludus Fast MCP server in PolicyLayer and add a rule for auto_scaling: 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 Ludus FastMCP. Nothing to install.
auto_scaling 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 auto_scaling 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 auto_scaling. 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.
auto_scaling is provided by the Ludus Fast MCP server (tjnull/ludus-fastmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 201 Ludus FastMCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
201 Ludus FastMCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.