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DansPK

Kali MCP

by DansPK

responder

Poison LLMNR, NBT-NS, and mDNS responses to capture NTLMv2 password hashes from Windows systems on local networks. Useful for internal assessments to obtain credentials for cracking.

Instructions

LLMNR, NBT-NS, and mDNS poisoner. Responds to name resolution requests on the local network and captures NTLMv2 password hashes from Windows systems. Use on internal network assessments to capture credentials when systems attempt to resolve names. Run on a network interface with an IP on the target subnet. Output: captured NTLMv2 hashes that can be cracked with hashcat (mode 5600).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
optsNoAdditional responder options (e.g. '-A' to analyze mode, '-w' to start WPAD server)
interfaceYesNetwork interface to listen on (e.g. eth0, tun0). Must be on target network.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral disclosure burden. It clearly states the active poisoning behavior, the protocols involved, the credential-capture outcome, and the expected output in terms of hashcat mode 5600. It does not mention privilege requirements, indefinite listener behavior, or potential network side effects, but it is substantially transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the core purpose before moving to usage and output. There is some redundancy between 'captures NTLMv2 password hashes' and 'Output: captured NTLMv2 hashes,' but every sentence still contributes useful information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with only one required parametera and no output schema or annotations, the description provides enough context to use it: what it does, when to use it, where to run it, and what result to expect. It omits operational details such as needing elevated privileges or how to stop the listener, but the core invocation context is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already provides 100% coverage for both parameters: interface is described as the network interface to listen on and opts includes example flags. The description adds no additional per-parameter detail beyond roughly restating the schema's interface requirement, so the baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as an LLMNR, NBT-NS, and mDNS poisoner that responds to name-resolution requests and captures NTLMv2 hashes from Windows systems. This is a specific verb+resource pairing that distinguishes it from sibling tools like hashcat (which cracks hashes) or nmap (which scans networks).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly says to use the tool during internal network assessments when systems attempt to resolve nameshol and instructs running it on an interface with an IP on the target subnet. It does not name alternative tools or state when not to use it, so it stops short of a full 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.