AI agents invoke simulate_principal_policy to trigger actions in AWS Support 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.
The tool name 'simulate_principal_policy' strongly suggests it invokes the AWS IAM SimulatePrincipalPolicy API, which evaluates IAM policies to determine what actions a principal is allowed or denied. This is an Execute-category action as it runs a simulation/evaluation of policies. While it is primarily a read/query operation in practice, it can reveal sensitive IAM permission details that could be exploited.
From the tool's definition Tool name 'simulate_principal_policy' — no description provided.
Documented attack patterns abuse exactly the kind of access simulate_principal_policy gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and AWS Support MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for simulate_principal_policy:
{
"version": "1",
"default": "deny",
"tools": {
"simulate_principal_policy": {
"limits": [
{
"counter": "simulate_principal_policy_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} simulate_principal_policy 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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simulate_principal_policy. It is categorised as a Execute tool in the AWS Support MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the AWS Support MCP Server MCP server in PolicyLayer and add a rule for simulate_principal_policy: 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 Support MCP Server. Nothing to install.
simulate_principal_policy 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 simulate_principal_policy 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 simulate_principal_policy. 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.
simulate_principal_policy is provided by the AWS Support MCP Server MCP server (awslabs.aws-support-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from AWS Support MCP Server, 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.
805 AWS Support MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.