Network Recon Scanning logo

Network Recon Scanning

Organization
CDESpace
Network Recon Scanning

Triage a network alert where one source fans out across many hosts or many ports — port and service scans, protocol probes, and host or segment sweeps. Reads flow records and firewall logs for direction, spread, and what the sweep reached to tell a sanctioned scanner apart from an internal foothold mapping the network, and decides escalate or dismiss.

Overview

PublisherCDESpace
RepositoryDetection-Skills
Skill nameNetwork Recon Scanning
Stars
57
Forks
5
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by CDESpace on GitHub. Read the source before you install it.

Installation

Install the Network Recon Scanning 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/CDESpace/Detection-Skills/tree/main/skills/triage/network-recon-scanning
  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/CDESpace/Detection-Skills.git /tmp/Detection-Skills
mkdir -p .claude/skills
cp -r /tmp/Detection-Skills/skills/triage/network-recon-scanning .claude/skills/cdespace-network-recon-scanning
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Network Recon Scanning 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 Scanning 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 Scanning 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.

Triage Steps

This class fires on fan-out traffic — one source touching many destinations or many ports, low bytes per flow. That shape is also what vulnerability scanners and asset inventory tools look like, so the fact that a sweep happened is not the signal. The signal is the story around it: where the source sits, what it reached, and whether scanning is that source's job. Recon is the prep step before lateral movement, so triage here is reading that story and deciding whether it looks like sanctioned scanning or like a host inside the network starting to map what it can reach. The core question is whether this is a known scanner or normal baseline, or an internal host quietly mapping its neighbors.

Begin with this detection's track record on this source and segment — a rule that fires daily on the same scanner range and is always closed benign starts the call near dismiss — then read the flow and firewall data for the leads below. None is required on its own; they stack, and a single strong one (an internal host sweeping a sensitive segment with flows completing) can carry the call.

Leads that point to a real threat — what to look for in the data:

  • Internal source scanning internally. A workstation or server as the source IP, the destinations also on internal subnets — not inbound from the internet. One internal host opening flows to dozens of internal IPs on :445, :3389, :22 in a short window is discovery from inside, the step before lateral movement.
  • The sweep reached sensitive assets. The destinations are databases, management interfaces, domain controllers, or OT/ICS segments, and the resource posture flags them (Wiz sensitive-data, high-business-impact). Flows landing on :1433, :3306, hypervisor or switch management ports, or a segregated control network is recon with a target in mind.
  • The scan succeeded. Flows completed and live services answered. Many completed low-byte flows to real listeners means the source now knows what is open — the sweep produced a map.
  • No baseline and no scanner match. The source has never done this before and does not belong to any range that scans by design. The asset inventory (Axonius, managed-devices) tells you what the source is — a user laptop suddenly emitting a port sweep is the unusual case; a dedicated scanner appliance doing it nightly is not. A malicious or suspicious reputation verdict on an external source adds weight when the sweep comes in from outside.

Leads that rule it out — benign context you can actually see in the data; if the data doesn't show it, you don't have it:

  • A confirmed scanner identity. The source IP belongs to the documented vulnerability- or attack-surface-scanning range, or a known asset-inventory host, whose whole job is to sweep, or an external source whose reputation is a known internet-wide scanner.
  • It matches the source's baseline. This source has emitted the same sweep shape on the same cadence before as normal activity, and nothing about the targets or timing changed this time.
  • Fleet-wide maintenance, not single-target. The sweep lines up with a scheduled scan window or a broad inventory pass across the environment — the shape of operations, which scans everything; an intrusion sweeps from one unexpected host.
  • Clean history. This rule has closed benign on this source or segment before, with nothing new in the direction or targets this time.

To confirm a lead instead of guessing, pull the thread: in the same window, did one of the swept hosts answer with a real session — a completed flow carrying bytes to a service the source had just probed? A probe that turns into a connection is recon turning into access.

Output

Decision

  • escalate: an internal source sweeping internal hosts, a sweep that reached sensitive assets, a scan that succeeded against live services, or an unknown source with no scanning baseline — especially two together, or any one with a real follow-on session after it.
  • dismiss: a confirmed scanner range, a baseline match, or a scheduled maintenance pass explains it — a corroborated authorized scanner (range, schedule, and scope confirmed) accounts for internal-to-internal sweeps, reaching sensitive segments, and the credentialed sessions a scan opens — and nothing follows that its authorized pattern does not explain. A dismiss is a positive call that the sweep is benign, made with that context in hand — a scanner range you matched, a sweep shape and cadence the baseline actually shows; a source you couldn't identify or a scan schedule you couldn't confirm is not that context, and absence of a bad sign is not proof it's good. Dismiss is logged and reopenable; when the benign context is missing or you're unsure — or an internal sweep hits sensitive targets with no corroborated scanner behind it, or a probe turns into a targeted session beyond that pattern — escalate.

Evidence

The scan's direction and source, whether the source matches a known scanner range or maintenance window and its reputation, the source's role from the asset inventory, the sensitivity of the targets reached and whether the resource posture flags them, and how this rule was handled on this source or segment before.

Reasoning

Name the leads that decided it and how they stacked — an internal host with no scanner standing sweeping a database segment with flows completing is escalate on its own; a documented scanner range doing its nightly pass on its usual cadence is dismiss.

Frequently asked questions

What does the Network Recon Scanning AI skill do?

Triage a network alert where one source fans out across many hosts or many ports — port and service scans, protocol probes, and host or segment sweeps. Reads flow records and firewall logs for direction, spread, and what the sweep reached to tell a sanctioned scanner apart from an internal foothold mapping the network, and decides escalate or dismiss.

Why use Network Recon Scanning on TypingMind?

Because you install it once and use it with any model. Network Recon Scanning 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 Scanning in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/CDESpace/Detection-Skills/tree/main/skills/triage/network-recon-scanning. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Network Recon Scanning?

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 Scanning?

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

Is the Network Recon Scanning AI skill free?

Yes. It is published on GitHub by CDESpace 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇