AI agents invoke stop_scan to trigger actions in AWS API 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.
This tool executes an action that interrupts a running process with side effects, but does not permanently delete data or modify its state irreversibly. Stopping a scan is a runtime operation that can affect security posture and compliance monitoring, but can typically be restarted. This makes it Execute rather than Destructive.
From the tool's definition Tool name 'stop_scan' and description 'Stop a running security scan' indicate an action that halts an external operation (a security scan) whose effects depend on runtime state and could impact ongoing security monitoring and audit activities.
Documented attack patterns abuse exactly the kind of access stop_scan gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and AWS API MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for stop_scan:
{
"version": "1",
"default": "deny",
"tools": {
"stop_scan": {
"limits": [
{
"counter": "stop_scan_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}stop_scan 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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Stop a running security scan. It is categorised as a Execute tool in the AWS API MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the AWS API MCP Server MCP server in PolicyLayer and add a rule for stop_scan: 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 AWS API MCP Server. Nothing to install.
stop_scan 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 stop_scan 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 stop_scan. 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.
stop_scan is provided by the AWS API MCP Server MCP server (awslabs.aws-api-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from AWS API 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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805 AWS API MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.