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run_checkov

run_checkov

How to control run_checkov ↓

What run_checkov does on Amazon Data Processing MCP Server

AI agents invoke run_checkov to trigger actions in Amazon Data Processing 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.

High Risk

Why run_checkov needs a policy

Despite the empty description limiting certainty, the tool name 'run_checkov' clearly indicates execution of an external analysis tool. This falls under Execute category as it triggers an external operation (Checkov scanning) whose effects depend on the scanned files/code arguments.

From the tool's definition Tool name 'run_checkov' indicates execution of Checkov, an infrastructure-as-code static analysis tool. Checkov performs scanning and validation operations on cloud infrastructure code.

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

How to control run_checkov

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 run_checkov:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "run_checkov": {
      "limits": [
        {
          "counter": "run_checkov_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

run_checkov 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.

  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.
RATE-LIMIT THIS TOOL →

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Related tools and policies

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Questions about run_checkov

What does the run_checkov tool do? +

run_checkov. It is categorised as a Execute tool in the Amazon Data Processing 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 run_checkov? +

Register the Amazon Data Processing MCP Server MCP server in PolicyLayer and add a rule for run_checkov: 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 run_checkov? +

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

Can I rate-limit run_checkov? +

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

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

run_checkov 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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