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Endpoint Recon Lateral Movement

Organization
CDESpace
Endpoint Recon Lateral Movement

Triage a host alert where the environment is being mapped or the actor is moving between hosts — system, account, and network discovery commands run on the host, and remote execution or remote-session pivots to other machines. Reads the actor and host role against the breadth of discovery or the destination of a pivot to tell sanctioned scanning and admin paths apart from an attacker fanning out, and decides escalate or dismiss.

Overview

PublisherCDESpace
RepositoryDetection-Skills
Skill nameEndpoint Recon Lateral Movement
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 Endpoint Recon Lateral Movement 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/endpoint-recon-lateral-movement
  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/endpoint-recon-lateral-movement .claude/skills/cdespace-endpoint-recon-lateral-movement
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Endpoint Recon Lateral Movement 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 Endpoint Recon Lateral Movement 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 Endpoint Recon Lateral Movement 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 commands that admins, inventory tools, and ordinary tooling run constantly — a single discovery command or one remote session is low-conviction noise on its own. What makes it a signal is breadth and authority: many distinct discovery techniques from one host in a short window, or a pivot reaching a destination the actor has no documented reason to touch. The thing to read is the actor and host role against what they are doing — an inventory scanner on a management host enumerating the fleet is its job, while a standard workstation running account, network, and security-product discovery back-to-back is mapping. Triage here is reading that mismatch and deciding whether this is expected admin work or someone getting their bearings and fanning out.

Start from this detection's track record on this actor and host — a scanner that sweeps nightly and always closes benign starts the call near dismiss — then read the leads below. None is required on its own; they stack, and one strong lead (a burst of distinct discovery from a user workstation, a non-admin authenticating to a domain controller) can carry the call. When this co-fires with a credential-theft or persistence alert on the same host, fold this alert into that higher-priority triage rather than triaging it independently; credential-based lateral movement — the same credential appearing on multiple targets — is a call the credential-theft skill owns.

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

  • A burst of distinct discovery techniques. Several different categories run in a short window from the same process tree — account enumeration, network topology, process or security-product discovery, credential-store location: net user /domain, net group "Domain Admins", nltest /dclist, whoami /all, tasklist /svc in quick succession. Breadth and density, not any single command, are the tell.
  • Directory enumeration at scale. Programmatic LDAP queries pulling users, groups, or computers wholesale, or queries for high-value targets and trust relationships — the shape of mapping a directory rather than looking up one record.
  • Pivot to a sensitive or unusual destination. A non-admin authenticating to many hosts, or any account reaching a domain controller, backup server, or other sensitive target it has no documented reason to reach: \\host\ADMIN$ writes, a remote-service install, WMI or WinRM remote execution to a server outside the actor's normal scope. An actor the identity directory already flags (risky-users) adds weight.
  • Recognized remote-execution toolmarks reaching an unexpected target. Characteristic named objects, a service-install signature, or tool-specific process-name patterns left by remote-exec tooling, landing on a destination outside the actor's documented, recurring management pattern — these escalate regardless of the account. A toolmark on a host pair already on record as routine, recurring management is a mechanism-creation question, not a movement one.
  • Authentication-based movement with no tool. The same account authenticating to an unusual number of targets in a short window, or credential material appearing where it should not — a hash or token presented in a context where only an interactive logon belongs (pass-the-hash). Cross-reference credential-theft alerts on the originating host; if one is present, defer to that skill and treat this as supporting context.

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:

  • The actor and host role explain it. A confirmed admin or a recognized management service running from a known scanner or jump host — the asset inventory (Axonius, managed-devices) confirms the host's role — following a recognizable admin path.
  • It matches the host's baseline. The same discovery shape, or the same jump-host-to-target session, has run here before as normal activity.
  • Expected destination within baseline. A single session from a jump host to a server the actor routinely manages, reaching a target it has a documented reason to touch.
  • Fleet-wide, not single-target. The identical discovery command sweeps the environment on an inventory cadence — the shape of a scanner, which queries broadly; an intruder's recon comes from one foothold.
  • Clean history, no new scope. This rule has closed benign on this actor before, with no new destination, no new technique, and no widened scope this time.

To confirm a lead instead of guessing, pull the thread: did the discovery burst precede a connection attempt, a download, or a privilege change, and did the pivot land on a host the actor never reaches? Corroboration turns scattered commands into a confirmed fan-out.

Output

Decision

  • escalate: a burst of distinct discovery techniques, directory enumeration at scale, a pivot to a sensitive or unusual destination, recognized remote-execution toolmarks, or authentication-based movement to an unusual number of targets — especially when recon precedes a download, connection, or privilege change.
  • dismiss: a confirmed admin or recognized scanner on a known management or jump host, a baseline match, or a single expected session within baseline explains it, with no new destination or widened scope. A dismiss is a positive call that the activity is benign, made with that context in hand — a scanner's management-host role you verified, a repeated discovery shape you recognized; an actor you couldn't confirm or a baseline you couldn't establish is not that context, and absence of a bad sign is not proof it's good. Dismiss is logged and reopenable; when the actor is a non-admin, the breadth is unusual, the destination is sensitive, or you're unsure, escalate.

Evidence

The actor and host role (admin or scanner vs standard user or workstation), whether discovery is a single command or a burst of distinct techniques in a short window, whether a pivot's destination is expected or sensitive, the presence of recognized offensive toolmarks, and what preceded or followed in the same window.

Reasoning

Name the leads that decided it and how they stacked — for discovery, a workstation running several distinct enumeration techniques in minutes is escalate while one lookup is noise; for movement, a non-admin reaching a domain controller is escalate while an admin's routine jump-host session is dismiss.

Frequently asked questions

What does the Endpoint Recon Lateral Movement AI skill do?

Triage a host alert where the environment is being mapped or the actor is moving between hosts — system, account, and network discovery commands run on the host, and remote execution or remote-session pivots to other machines. Reads the actor and host role against the breadth of discovery or the destination of a pivot to tell sanctioned scanning and admin paths apart from an attacker fanning out, and decides escalate or dismiss.

Why use Endpoint Recon Lateral Movement on TypingMind?

Because you install it once and use it with any model. Endpoint Recon Lateral Movement 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 Endpoint Recon Lateral Movement in TypingMind?

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

Which AI models can use Endpoint Recon Lateral Movement?

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 Endpoint Recon Lateral Movement?

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

Is the Endpoint Recon Lateral Movement 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.

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