AI agents invoke run_docker to trigger actions in Pentester-MCP. 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.
Docker execution is a code execution primitive with unbounded capability. An AI agent given this tool could execute any containerized code, escalate privileges, access host resources, or pivot to other systems depending on Docker configuration. This is functionally equivalent to arbitrary code execution. The empty description increases risk as capabilities and constraints are unknown.
From the tool's definition Tool is named 'run_docker' and exists on Pentester-MCP server which 'Enables AI assistants to autonomously execute over 200 open-source penetration testing tools' through 'Docker sandboxing'. The tool allows arbitrary Docker container execution.
Documented attack patterns abuse exactly the kind of access run_docker gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Pentester-MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for run_docker:
{
"version": "1",
"default": "deny",
"tools": {
"run_docker": {
"limits": [
{
"counter": "run_docker_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}run_docker 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_docker. It is categorised as a Execute tool in the Pentester-MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Pentester- MCP server in PolicyLayer and add a rule for run_docker: 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 Pentester-MCP. Nothing to install.
run_docker 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_docker 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_docker. 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_docker is provided by the Pentester- MCP server (halilkirazkaya/pentester-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Pentester-MCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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337 Pentester-MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.