AI agents invoke reboot_virtual_machine to trigger actions in CloudStack MCP Server. 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.
Rebooting a virtual machine is an Execute-category action: it triggers an external operation on infrastructure. While not permanently destructive, it causes service interruption and downtime for any workloads running on the VM. Misuse by an AI agent could disrupt production services, making severity high.
From the tool's definition 'Reboot a virtual machine' — triggers an external operation (reboot) on a running VM instance
Documented attack patterns abuse exactly the kind of access reboot_virtual_machine gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and CloudStack MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for reboot_virtual_machine:
{
"version": "1",
"default": "deny",
"tools": {
"reboot_virtual_machine": {
"limits": [
{
"counter": "reboot_virtual_machine_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} reboot_virtual_machine 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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Reboot a virtual machine. It is categorised as a Execute tool in the CloudStack MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the CloudStack MCP Server MCP server in PolicyLayer and add a rule for reboot_virtual_machine: 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 CloudStack MCP Server. Nothing to install.
reboot_virtual_machine 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 reboot_virtual_machine 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 reboot_virtual_machine. 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.
reboot_virtual_machine is provided by the CloudStack MCP Server MCP server (phantosmax/cloudstack-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from CloudStack MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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45 CloudStack MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.