Network Recon logo

Network Recon

Organization
zero-lab-ai
network-recon

Plans authorized network reconnaissance, checks proposed targets against explicit IP scope, chooses scanning tools by cost, and audits completed scans for coverage. Use when mapping a network, enumerating hosts and services, deciding which scanner to run, or determining whether an empty scan is a finding or a failure.

Overview

Publisherzero-lab-ai
Repositoryskills
Skill namenetwork-recon
Stars
232
Forks
14
Bundled files
6
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by zero-lab-ai on GitHub. Read the source before you install it.

Installation

Install the Network Recon AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/zero-lab-ai/skills/tree/main/plugins/recon-operations/skills/network-recon
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/zero-lab-ai/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/recon-operations/skills/network-recon .claude/skills/network-recon
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Network Recon in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Network Recon on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Network Recon is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Network recon

Running a scanner is not the skill. Anyone can run nmap. The skill is choosing the right tool for the cost you can afford, and knowing when the output is lying to you.

An empty result and an unanswered question look identical. Most recon mistakes are made in the gap between those two.

When to Use

  • Mapping a network, enumerating hosts and services, deciding which scanner to run, or determining whether an empty scan is a finding or a failure.
  • Use only within explicit authorization and the stated rules of engagement.

When NOT to Use

  • Do not treat this skill as permission to access, test, or change a target.
  • Do not convert missing evidence into a clean result or a stronger claim.

This skill is loud, on purpose

It assumes penetration test conditions: an agreed scope, completeness as the deliverable, and noise that nobody is scoring you on. Every recommendation here optimises for not missing things.

Do not apply it to a red team operation. Red teaming optimises for the opposite thing — reaching an objective without being detected, and testing the security programme itself: people, processes, technology. A 65,535-port sweep is correct practice here and disqualifying there. The tooling overlaps; the optimisation function is reversed, and so is the right answer at almost every decision point.

If stealth is a requirement, you want a quiet-enumeration skill, and this is not it.

Scope first, always

Establish and write down the authorized scope before the first packet. Refuse targets outside it. A scan is an action against someone else's property; the scope statement is the only thing that makes it legitimate, and "it was in the same /16" is not a scope statement.

Treat authorization as a ceiling, not as a target list. When a request names specific proposed targets inside a wider authorized range, admit only those targets that pass the scope check. Do not expand discovery to the rest of the range unless the requested target set explicitly includes it.

Before scanning, record IP/CIDR scope and proposed targets in a manifest and run the deterministic check:

sh
uv run {baseDir}/scripts/check_scope.py scope.json
json
{
  "authorized": ["10.0.0.0/24"],
  "excluded": ["10.0.0.64/27"],
  "targets": ["10.0.0.12", "10.0.0.128/26"]
}

Exit 0 means every target is wholly contained in authorization and overlaps no exclusion. Exit 1 names targets to refuse. Exit 2 means the manifest is invalid or empty, so no scope decision was measured. The checker accepts IPs and CIDRs only; resolve and authorize hostnames explicitly rather than making the checker contact DNS.

Tool selection

Two stages, never one. Fast discovery to find what is alive and listening, then a targeted deep scan only on what answered. A single thorough scan across an undiscovered range is the most common way to burn a day.

Nmap carries ~99% of the work. The others earn their place by being faster at discovery, and they hand back to Nmap for fidelity.

GoalToolCostWhen it is the wrong choice
Find live hosts, layer 2 / local subnetnetdiscover (ARP)secondsUseless off-segment — ARP does not route
Sweep a large subnet for alive hostsmasscanseconds–minutesTrades precision and fingerprinting for raw speed. Alive-tracking only, then drop into Nmap
Find open TCP ports fast, all 65,535rustscansecondsSlow or lossy links can cost accuracy; it is a front end, not an answer
Initial TCP discoverynmap -sS + top-ports, tuned --min-rateseconds–minutesTop-ports alone will miss non-standard ports. Never the last scan
Full TCP coveragenmap -p- on discovered hostsminutes–hoursSkipping it is how low-hanging fruit on odd ports gets missed
Service and version fidelitynmap -sV -sC or --script=safe,defaultminutesNoisier and slower; without it, service names are guesses from port numbers
UDP, fastrustscan --udpseconds–minutesFinds only UDP ports that send back a response. Silent services are invisible — a clean result here proves very little
UDP, completenmap -sUhours to days on a full rangeAlmost always the wrong default. Scope it to the ports you care about and state the cost before starting

The standard chain: rustscan or masscan for discovery → pipe the open ports into nmap -sV -sC for identification → nmap -p- to confirm nothing was missed.

NSE: --script=safe,default is the useful, non-destructive tier — basic service information and versions without launching automated exploits. Treat anything outside safe,default as an action requiring its own authorization.

Protocol-specific enumeration

Once ports are known, stop using a network scanner and pivot:

ServiceTool
Web — configuration and known issuesnikto
Web — content and directory discoverygobuster, feroxbuster, ffuf
SMB / Windows — shares, users, null sessionsenum4linux, netexec (formerly CrackMapExec)

"Allowed" is context, not a property

Lists of permitted tools belong to the context that issued them. The tiering above reflects what is sanctioned in OffSec exam conditions, which is a useful baseline because it was drawn to exclude automated exploitation. It is not a permission slip anywhere else. In an engagement the authority is the client's rules of engagement, and in a lab it is the lab's. Check the authority that actually governs the target in front of you.

Reading results

Four readings that are wrong by default. Each one has cost real engagement time.

filtered is not closed. A blocked path and a closed port are indistinguishable from a port scanner and are different facts. Before concluding a segment is empty, prove a route exists to it — check the routing table from the hosts you already hold. A segment that returns all filtered, nothing open is more often unrouted than hardened.

Clean with no coverage is not clean. A scan that never reached the target reports the same silence as a hardened host. Always audit coverage before reporting a negative result; a scanner that cannot reach a box and calls it clean is the worst output a scanner can produce.

Absence is not evidence. No UDP findings from a TCP-only scan is not a finding about UDP. No service versions from a scan without version detection means the service names are guesses from port numbers — do not write them into a report as identified.

"The environment is broken" is a live hypothesis. When several independent signals converge on nothing — no hosts responding, an unreachable subnet, no credential anywhere, empty data stores — treat an unseeded or misconfigured environment as a real possibility and verify it. Verifying the environment is a skill, not a cop-out, and it beats hours spent grinding a target that was never populated.

Audit the scan before trusting it

sh
uv run {baseDir}/scripts/audit_scan.py scan.xml          # nmap -oX (preferred) or -oG
uv run {baseDir}/scripts/audit_scan.py scan.xml --json

Reports coverage, not findings: hosts that actually responded, ports actually probed, protocols covered, and which flags narrowed the scan. Exit 0 only when there was real coverage; 1 on coverage gaps; 2 when nothing responded or no port was ever probed. Zero coverage cannot exit 0, by design — see references/coverage-checks.md.

Recon handoff

The handoff should make the denominator visible, not just list discovered services:

FieldMinimum content
Scope decisionAuthorized ranges, exclusions, proposed targets, and checker result
Discovery coverageMethods used, hosts attempted, hosts that responded, and route limitations
Port coverageTCP and UDP ranges actually probed, including any rate or timing constraints
Service evidenceObserved protocol or version evidence; label port-based guesses as guesses
Open workUnreached segments, filtered paths, incomplete UDP work, and blocked follow-up
Next actionThe smallest authorized step that resolves the most important unknown

An empty service list with nonempty open work is an incomplete assessment, not a clean network.

Rationalizations to reject

ThoughtReality
"The scan came back clean, so it's clean."Clean with zero coverage is an unanswered question. Audit coverage first.
"All ports are filtered, so the host is locked down."More often there is no route. Prove reachability before concluding hardening.
"No UDP results, so no UDP services."You did not scan UDP. Absence of a scan is not absence of a service.
"nmap said it's SSH."Without version detection that is a guess from port 22. Do not report it as identified.
"I'll just run the full sweep to be safe.""Safe" that costs days is a choice, not a default. State the cost and get it confirmed.
"The target is in the same range, close enough."Scope is written down or it does not exist.
"The whole range is authorized, so I can discover all of it."Authorization permits work; it does not request every permitted target. Preserve the supplied target set.
"Nothing is here, the range is empty."Consider that the environment is unseeded or your path is wrong before concluding emptiness.
"It's faster to scan everything once than think about it."The thinking is the skill. The scan is the easy part.
"Recon is recon — I'll use this on the red team engagement too."No. This skill optimises for completeness and makes noise doing it. On a red team operation that noise is the finding, and it is the blue team's point.

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Network Recon AI skill do?

Plans authorized network reconnaissance, checks proposed targets against explicit IP scope, chooses scanning tools by cost, and audits completed scans for coverage. Use when mapping a network, enumerating hosts and services, deciding which scanner to run, or determining whether an empty scan is a finding or a failure.

Why use Network Recon on TypingMind?

Because you install it once and use it with any model. Network Recon is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Network Recon in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zero-lab-ai/skills/tree/main/plugins/recon-operations/skills/network-recon. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Network Recon?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Network Recon?

As many as you like. As long as a model supports skills, you can use Network Recon with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Network Recon AI skill free?

Yes. It is published on GitHub by zero-lab-ai under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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