AI agents invoke run_checkov to trigger actions in AWS API 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.
Checkov execution scans code/infrastructure and can have side effects like writing reports, triggering remediation logic, or affecting build pipelines. This is an Execute category tool because it runs an external process/analysis whose side effects depend on the scanned code and Checkov's configuration.
From the tool's definition Tool name 'run_checkov' indicates execution of Checkov, a static code analysis and infrastructure-as-code security scanning tool. No description provided, but the name strongly implies running an external analysis process.
Documented attack patterns abuse exactly the kind of access run_checkov gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and AWS API MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for run_checkov:
{
"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.
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run_checkov. It is categorised as a Execute tool in the AWS API MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the AWS API 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 AWS API MCP Server. Nothing to install.
run_checkov is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
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.
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.
run_checkov is provided by the AWS API MCP Server MCP server (awslabs.aws-api-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from AWS API 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 AWS API MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.