AI agents invoke stop_proxify 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.
This tool executes a system-level operation (terminating a background process). While it does not delete data irreversibly or modify application state directly, it triggers an external operation whose effects depend on what is currently running. Process termination is an Execute action rather than Read or Write because it performs a control action on a running system component.
From the tool's definition Tool name 'stop_proxify' and description 'Terminates a running proxify background process' indicate execution of a process termination command.
Documented attack patterns abuse exactly the kind of access stop_proxify 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 stop_proxify:
{
"version": "1",
"default": "deny",
"tools": {
"stop_proxify": {
"limits": [
{
"counter": "stop_proxify_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}stop_proxify 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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Terminates a running proxify background process. 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 stop_proxify: 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.
stop_proxify 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 stop_proxify 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 stop_proxify. 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.
stop_proxify 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.
Free to start. No card required.
337 Pentester-MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.