Medium Risk

put_role_policy

put_role_policy

How to control put_role_policy ↓

What put_role_policy does on Amazon Data Processing MCP Server

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

Medium Risk

Why put_role_policy needs a policy

This tool creates or updates IAM inline policies attached to roles, modifying access control configurations. While reversible (policies can be updated or deleted), it grants or modifies permissions and poses high risk if an agent misuses it to escalate privileges or grant unintended access. Classified as Write rather than Execute because it modifies policy documents rather than executing code.

From the tool's definition Tool name 'put_role_policy' indicates creation or modification of IAM role policies. Sibling tools include 'add_inline_policy' and 'add_user_to_group', confirming this server handles AWS IAM operations.

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

How to control put_role_policy

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

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "put_role_policy": {
      "limits": [
        {
          "counter": "put_role_policy_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

put_role_policy 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.

  1. Create a free account and register Amazon Data Processing MCP Server — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
LIMIT THIS TOOL →

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Related tools and policies

Go deeper

Questions about put_role_policy

What does the put_role_policy tool do? +

put_role_policy. It is categorised as a Write tool in the Amazon Data Processing 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 put_role_policy? +

Register the Amazon Data Processing MCP Server MCP server in PolicyLayer and add a rule for put_role_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 Amazon Data Processing MCP Server. Nothing to install.

What risk level is put_role_policy? +

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

Can I rate-limit put_role_policy? +

Yes. Add a rate_limit block to the put_role_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.

How do I block put_role_policy completely? +

Set action: deny in the PolicyLayer policy for put_role_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.

What MCP server provides put_role_policy? +

put_role_policy is provided by the Amazon Data Processing MCP Server MCP server (awslabs.aws-dataprocessing-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 Amazon Data Processing MCP Server tool call.

Start from Amazon Data Processing 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 Amazon Data Processing MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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