AI agents invoke send_input to trigger actions in Zebbern Kali 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.
Given the server context (Docker-based Kali Linux pentest toolkit with remote execution tools like psexec and wmiexec as siblings), 'send_input' almost certainly sends arbitrary input to a running shell or process within the container. This constitutes Execute-category behavior with critical severity, as it could drive any offensive operation.
From the tool's definition Tool is part of a Kali Linux penetration testing MCP server with sibling tools including ad_secretsdump, ad_psexec, ad_wmiexec, ad_password_spray — all offensive security tools.
Documented attack patterns abuse exactly the kind of access send_input gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Zebbern Kali MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for send_input:
{
"version": "1",
"default": "deny",
"tools": {
"send_input": {
"limits": [
{
"counter": "send_input_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}send_input 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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send_input. It is categorised as a Execute tool in the Zebbern Kali MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Zebbern Kali MCP server in PolicyLayer and add a rule for send_input: 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 Zebbern Kali MCP. Nothing to install.
send_input 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 send_input 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 send_input. 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.
send_input is provided by the Zebbern Kali MCP server (zebbern/zebbern-kali-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 128 Zebbern Kali MCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
128 Zebbern Kali MCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.