sam_init · Amazon SageMaker AI MCP Server MCP: Risk & Policy

WHAT IT DOES

What sam_init does on Amazon SageMaker AI MCP Server

AI agents invoke sam_init to trigger actions in Amazon SageMaker AI 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 RISK

High Risk

Why sam_init needs a policy

The name 'sam_init' strongly implies execution of the AWS SAM CLI 'init' command, which creates and scaffolds new serverless application projects. This is an Execute-category action as it triggers external operations and generates project structure. However, the description is empty, which significantly lowers confidence.

From the tool's definition Tool name 'sam_init' suggests AWS SAM (Serverless Application Model) initialization, which executes project scaffolding and infrastructure setup operations

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

POLICY

How to control sam_init

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

policy.json

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

sam_init 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 Amazon SageMaker AI 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 →

Free to start. No card required.

EXPLORE

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High-risk tools in Amazon SageMaker AI MCP Server → Every high-risk tool this server exposes, in one view.
All high-risk MCP tools → Every high-risk tool across the catalogue, and the policy pattern that contains them.
The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Agent sandbox → Bounding what an agent can execute and where the boundary should sit.
Least privilege for MCP → Granting agents the minimum tool surface the task needs.
Rate Limiting MCP Tool Calls: A Practical Guide →
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PolicyLayer vs alternatives → How deterministic, per-call MCP policy compares with gateways, identity layers, and authorisation platforms.

FAQ

Questions about sam_init

What does the sam_init tool do? +

sam_init. It is categorised as a Execute tool in the Amazon SageMaker AI 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 sam_init? +

Register the Amazon SageMaker AI MCP Server MCP server in PolicyLayer and add a rule for sam_init: 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 sam_init? +

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

Can I rate-limit sam_init? +

Yes. Add a rate_limit block to the sam_init 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 sam_init completely? +

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

sam_init 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.

Enforce policy on every Amazon SageMaker AI MCP Server tool call.

Start from Amazon SageMaker AI MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →

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