Lateral Movement Investigation logo

Lateral Movement Investigation

Organization
CDESpace
Lateral Movement Investigation

Investigate an escalated lateral-movement alert. Reconstructs the path an actor took between hosts — the source, the credentials used, the technique, and every asset reached — distinguishes admin or tooling traffic from an intruder pivoting, and returns a verdict with the full reached-asset scope and containment actions.

Overview

PublisherCDESpace
RepositoryDetection-Skills
Skill nameLateral Movement Investigation
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 Lateral Movement Investigation 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/investigation/Lateral%20Movement%20Investigation
  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.

Use it in TypingMind

Enable Lateral Movement Investigation 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 Lateral Movement Investigation 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 Lateral Movement Investigation 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.

Lateral Movement Investigation

Runs on alerts escalated by triage (see endpoint-recon-lateral-movement): a host made an internal connection — remote service creation, WMI/WinRM execution, RDP, SMB admin-share access, or a pass-the-hash shape — that triage judged anomalous. Triage established the hop looked wrong; investigation reconstructs the whole path and its reach. The question is not "did a host connect to another" — it did — but "who drove it, with what credential, and everywhere it went."

Inputs

  • The escalated alert (source host, destination host(s), technique, account used, timing) and the triage report.
  • Authentication logs (Windows 4624/4648/4672, Kerberos, VPN), endpoint process and remote-execution telemetry, and internal flow logs. Anchor on the account and the source host and expand outward.

Investigation steps

Collect all four signals; the verdict is derived from them at the end.

1. Source and entry reconstruction — signal A

Establish where the movement originated and how the actor got onto the source host. Signal A fires when the source host itself has an open or recent compromise signal — an earlier flagged sign-in, a beacon, a malware detection — tying the movement to a known foothold rather than a standalone admin action.

2. Credential attribution — signal B

Identify the credential used to authenticate to the destination and how it was obtained. Signal B fires on stolen-credential shapes: pass-the-hash or pass-the-ticket (logon type / ticket anomalies), a service or admin account used from a host it never runs on, or a credential that appeared on the source host through dumping rather than interactive logon. Note the privilege level — movement escalating toward domain admin weighs heavily.

3. Technique and path scoping — signal C

Map every hop: from the source, enumerate all destinations reached with the same credential or technique in the window, then repeat from each reached host. Signal C fires when the path fans out across multiple hosts, uses living-off-the-land remote execution (PsExec-style service creation, WMI/WinRM, scheduled tasks) inconsistent with normal administration, and reaches assets the account has no operational reason to touch.

4. Objective and impact — signal D

On the reached hosts, look for what the movement was for: credential dumping, data staging, backup/shadow-copy tampering, new persistence, or sensitive-system access. Signal D fires when the path terminates in actions on objective — this confirms an intrusion over a misread admin task and sets the real blast radius.

Verdict rule

  • malicious: signal B or C plus A or D — stolen-credential or fan-out movement tied to a foothold or ending in actions on objective. Movement reaching a domain controller or backup infrastructure with stolen credentials is malicious on its own.
  • suspicious: an anomalous hop (C) with an unusual credential where the source foothold and objective can't be established but a sanctioned admin explanation can't be shown either.
  • inconclusive: the path can't be reconstructed because authentication or endpoint logs for the hosts are missing.
  • benign: the movement resolves to sanctioned administration — a jump-host, a patch/config tool, or an admin whose account, source, and targets positively match their documented role and baseline — with no foothold, no stolen-credential shape, and no actions on objective.

Output

Verdict

One of malicious / suspicious / inconclusive / benign, with the signals that decided it.

Recommended actions

When not benign: isolate the source and every reached host, disable and rotate the credential used (and any credentials exposed on the path), revoke active sessions/tickets, preserve artifacts on the path for forensics, and hunt for the same credential and technique beyond the mapped hosts. Prioritize any domain-privileged or backup systems in the path.

Evidence

The reconstructed path (source → each hop with timestamps), the credential used and how it was obtained, the technique per hop, the full list of reached assets, the source host's foothold status, and any actions on objective found.

Reasoning

Name the signals and how they stacked — a beaconing workstation using a pass-the-hash admin credential to reach a file server and then a domain controller, dumping credentials on the way, is malicious; a backup service account touching its usual set of servers from the known backup host is benign.

Frequently asked questions

What does the Lateral Movement Investigation AI skill do?

Investigate an escalated lateral-movement alert. Reconstructs the path an actor took between hosts — the source, the credentials used, the technique, and every asset reached — distinguishes admin or tooling traffic from an intruder pivoting, and returns a verdict with the full reached-asset scope and containment actions.

Why use Lateral Movement Investigation on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/CDESpace/Detection-Skills/tree/main/skills/investigation/Lateral%20Movement%20Investigation. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Lateral Movement Investigation?

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 Lateral Movement Investigation?

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

Is the Lateral Movement Investigation 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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