AI agents invoke run_raise_child 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.
The tool description is empty, reducing confidence slightly, but the server context and sibling tools strongly indicate this executes external commands or processes. The naming pattern and server purpose classify this as Execute rather than Write, as penetration testing tools typically trigger external operations whose effects depend on attacker-supplied arguments.
From the tool's definition Tool is on Pentester-MCP server which 'enables AI assistants to autonomously execute over 200 open-source penetration testing tools' including 'web exploitation' and 'brute-forcing'; name 'run_raise_child' suggests executing or spawning a process; sibling…
Documented attack patterns abuse exactly the kind of access run_raise_child 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_raise_child:
{
"version": "1",
"default": "deny",
"tools": {
"run_raise_child": {
"limits": [
{
"counter": "run_raise_child_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} run_raise_child 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_raise_child. 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_raise_child: 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_raise_child 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_raise_child 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_raise_child. 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_raise_child 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.