manage_aws_emr_serverless_job_runs

THE RISK

High Risk

Why manage_aws_emr_serverless_job_runs needs a policy

The tool name suggests managing AWS EMR Serverless job runs, which involves starting, stopping, or otherwise controlling distributed compute jobs. 'Manage' implies execution-level control over external compute operations. Without a description, confidence is reduced, but the most likely interpretation is Execute (triggering or controlling job runs).

From the tool's definition Tool name: manage_aws_emr_serverless_job_runs — description is empty/uninformative

Documented attack patterns abuse exactly the kind of access manage_aws_emr_serverless_job_runs gives an agent:

POLICY

How to control manage_aws_emr_serverless_job_runs

PolicyLayer is an MCP gateway — it sits between your AI agents and Prometheus MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for manage_aws_emr_serverless_job_runs:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "manage_aws_emr_serverless_job_runs": {
      "limits": [
        {
          "counter": "manage_aws_emr_serverless_job_runs_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

manage_aws_emr_serverless_job_runs 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.

Create a free account and register Prometheus MCP Server — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

RATE-LIMIT THIS TOOL →

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EXPLORE

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All high-risk MCP tools → Every high-risk tool across the catalogue, and the policy pattern that contains them.
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FAQ

Questions about manage_aws_emr_serverless_job_runs

What does the manage_aws_emr_serverless_job_runs tool do? +

manage_aws_emr_serverless_job_runs. It is categorised as a Execute tool in the Prometheus MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on manage_aws_emr_serverless_job_runs? +

Register the Prometheus MCP Server MCP server in PolicyLayer and add a rule for manage_aws_emr_serverless_job_runs: 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 Prometheus MCP Server. Nothing to install.

What risk level is manage_aws_emr_serverless_job_runs? +

manage_aws_emr_serverless_job_runs is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit manage_aws_emr_serverless_job_runs? +

Yes. Add a rate_limit block to the manage_aws_emr_serverless_job_runs 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.

How do I block manage_aws_emr_serverless_job_runs completely? +

Set action: deny in the PolicyLayer policy for manage_aws_emr_serverless_job_runs. 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.

What MCP server provides manage_aws_emr_serverless_job_runs? +

manage_aws_emr_serverless_job_runs is provided by the Prometheus MCP Server MCP server (awslabs.prometheus-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Prometheus MCP Server tool call.

Start from Prometheus 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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