manage_aws_glue_resource_policies

WHAT IT DOES

What manage_aws_glue_resource_policies does on Amazon SageMaker AI MCP Server

AI agents use manage_aws_glue_resource_policies to create or update resources in Amazon SageMaker AI MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Amazon SageMaker AI MCP Server environment.

WHY IT NEEDS A POLICY

Why manage_aws_glue_resource_policies needs a policy

Without a description, classification relies on the tool name. 'Manage' resource policies implies Write operations (policy creation/modification), which are reversible but impact access control. This could affect multiple resources if misconfigured by an agent. Severity is high due to the blast radius of incorrect policy changes, but not critical since policies can typically be corrected.

From the tool's definition Tool name 'manage_aws_glue_resource_policies' suggests policy modification capabilities. The verb 'manage' typically encompasses create, update, and modify operations on AWS Glue resource policies.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

manage_aws_glue_resource_policies Rate-limited

manage_aws_glue_resource_policies 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "manage_aws_glue_resource_policies": {
      "limits": [
        {
          "counter": "manage_aws_glue_resource_policies_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Amazon SageMaker AI MCP Server, so you can run agents against it safely.

FAQ

Questions about manage_aws_glue_resource_policies

What does the manage_aws_glue_resource_policies tool do? +

manage_aws_glue_resource_policies. It is categorised as a Write tool in the Amazon SageMaker AI MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on manage_aws_glue_resource_policies? +

Register the Amazon SageMaker AI MCP Server MCP server in PolicyLayer and add a rule for manage_aws_glue_resource_policies: 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 Amazon SageMaker AI MCP Server. Nothing to install.

What risk level is manage_aws_glue_resource_policies? +

manage_aws_glue_resource_policies is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit manage_aws_glue_resource_policies? +

Yes. Add a rate_limit block to the manage_aws_glue_resource_policies 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_glue_resource_policies completely? +

Set action: deny in the PolicyLayer policy for manage_aws_glue_resource_policies. 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_glue_resource_policies? +

manage_aws_glue_resource_policies is provided by the Amazon SageMaker AI MCP Server MCP server (awslabs.sagemaker-ai-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.