AI agents invoke callback_check 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.
The description is empty, lowering confidence. However, given the server context (Kali Linux pentest toolkit) and sibling tools (credential dumping, lateral movement, password spraying), 'callback_check' likely triggers an out-of-band network callback (e.g., DNS/HTTP callback for SSRF or blind injection testing), which constitutes executing an external network operation.
From the tool's definition Tool name 'callback_check' on a Kali Linux penetration testing MCP server with sibling tools including ad_secretsdump, ad_password_spray, ad_psexec, and ad_wmiexec
Documented attack patterns abuse exactly the kind of access callback_check 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 callback_check:
{
"version": "1",
"default": "deny",
"tools": {
"callback_check": {
"limits": [
{
"counter": "callback_check_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}callback_check 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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callback_check. 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 callback_check: 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.
callback_check 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 callback_check 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 callback_check. 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.
callback_check 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.
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128 Zebbern Kali MCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.