AI agents invoke run_get_ad_computers 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 'run_' prefix combined with the Pentester-MCP server context (which executes penetration testing tools) and the tool name referencing Active Directory enumeration indicates this executes a reconnaissance command. This is Execute rather than Read because it autonomously triggers external tooling with effects dependent on the target environment, not a simple query.
From the tool's definition Tool name 'run_get_ad_computers' contains 'run', and the server description explicitly states it 'enables AI assistants to autonomously execute over 200 open-source penetration testing tools' including 'reconnaissance'.
Documented attack patterns abuse exactly the kind of access run_get_ad_computers 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_get_ad_computers:
{
"version": "1",
"default": "deny",
"tools": {
"run_get_ad_computers": {
"limits": [
{
"counter": "run_get_ad_computers_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} run_get_ad_computers 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_get_ad_computers. 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_get_ad_computers: 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_get_ad_computers 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_get_ad_computers 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_get_ad_computers. 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_get_ad_computers 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.