Competition Windows Pivot logo

Competition Windows Pivot

CommunityPopular
zhaoxuya520
competition-windows-pivot

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Kerberos, WinRM, SMB, RDP, Windows credential material, replayable tickets, delegation edges, and host-to-host pivot chains. Use when the user asks to replay Kerberos material, trace a WinRM, SMB, or RDP pivot, understand host-to-host privilege movement, or prove which Windows service accepted a credential or ticket. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

Overview

Publisherzhaoxuya520
Repositoryreverse-skill
Skill namecompetition-windows-pivot
Stars
36.3K
Forks
5K
Bundled files
2
LicenseMIT
Links
Skill sourceRepository
  • 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.

  • 2 bundled files

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

  • Open source

    Published by zhaoxuya520 on GitHub. Read the source before you install it.

Installation

Install the Competition Windows Pivot 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.
  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/zhaoxuya520/reverse-skill.git /tmp/reverse-skill
mkdir -p .claude/skills
cp -r /tmp/reverse-skill/CTF-Sandbox-Orchestrator/competition-windows-pivot .claude/skills/competition-windows-pivot
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Competition Windows Pivot 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 Competition Windows Pivot 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 Competition Windows Pivot 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.

Competition Windows Pivot

Use this skill only as a downstream specialization after $ctf-sandbox-orchestrator is already active and has established sandbox assumptions, node ownership, and evidence priorities. If that has not happened yet, return to $ctf-sandbox-orchestrator first.

Use this skill when the challenge path is dominated by host-to-host movement, replayable ticket material, or Windows privilege edges.

Reply in Simplified Chinese unless the user explicitly requests English.

Quick Start

  1. Compress the pivot into a concrete chain: foothold -> recovered artifact -> replay path -> pivot host -> resulting capability.
  2. Separate stored credential material from usable privilege.
  3. Keep host evidence, ticket evidence, and privilege effect on one timeline.
  4. Record the exact accepting service or host for every replayed artifact.
  5. Reproduce the smallest pivot that still proves the privilege edge.

Workflow

1. Recover The Replay Material

  • Inspect SAM, SECURITY, SYSTEM, NTDS, DPAPI, LSA secrets, browser stores, PowerShell history, ETW, Sysmon, and event logs in the active path.
  • Distinguish password, hash, ticket, cookie, vault blob, or gMSA material by where it can actually be used.

2. Trace The Pivot Chain

  • Map the protocol actually used: WinRM, SMB, RDP, WMI, admin shares, remote registry, or service control.
  • When Kerberos matters, record SPN, delegation, PAC or group data, encryption type, and the accepting service.
  • When AD edges matter, inspect ACLs, GPO links, SIDHistory, delegation, certificate templates, and replication rights.

3. Report The Edge

  • Keep the pivot path concrete and replayable.
  • State what artifact crossed which boundary and what capability appeared on the destination host.

Read This Reference

  • Load references/windows-pivot.md for the pivot checklist, Kerberos evidence block, and common replay mistakes.
  • If the task is specifically about DPAPI masterkeys, browser or vault stores, protected blobs, or proving where a recovered DPAPI secret is accepted, prefer $competition-dpapi-credential-chain.
  • If the task is specifically about LSASS memory, ticket caches, replayable session material, or host-resident credential extraction, prefer $competition-lsass-ticket-material.
  • If the task is specifically about delegation edges, SPN trust, S4U flow, or which service accepts the delegated ticket, prefer $competition-kerberos-delegation.
  • If the hard part is forced authentication, coercion primitives, relay targets, or the service that accepts relayed auth, prefer $competition-relay-coercion-chain.

What To Preserve

  • Host names, logon IDs, SIDs, SPNs, ticket fields, service names, and event IDs
  • Exact replay point and resulting logon session, token, or group change
  • Raw host artifacts and derived timeline separately

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 Competition Windows Pivot AI skill do?

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Kerberos, WinRM, SMB, RDP, Windows credential material, replayable tickets, delegation edges, and host-to-host pivot chains. Use when the user asks to replay Kerberos material, trace a WinRM, SMB, or RDP pivot, understand host-to-host privilege movement, or prove which Windows service accepted a credential or ticket. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

Why use Competition Windows Pivot on TypingMind?

Because you install it once and use it with any model. Competition Windows Pivot 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 Competition Windows Pivot in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zhaoxuya520/reverse-skill/tree/main/CTF-Sandbox-Orchestrator/competition-windows-pivot. 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 Competition Windows Pivot?

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 Competition Windows Pivot?

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

Is the Competition Windows Pivot AI skill free?

Yes. It is published on GitHub by zhaoxuya520 under the MIT 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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