Competition Cloud Metadata Path logo

Competition Cloud Metadata Path

CommunityPopular
zhaoxuya520
competition-cloud-metadata-path

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for cloud metadata services, instance identity, workload identity, link-local credential paths, role assumption, and metadata-to-privilege trust edges. Use when the user asks to inspect metadata-service access, instance credentials, pod or workload identity, link-local token paths, SSRF-to-metadata escalation, or explain how metadata-derived credentials turn into accepted cloud or control-plane privilege. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

Overview

Publisherzhaoxuya520
Repositoryreverse-skill
Skill namecompetition-cloud-metadata-path
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 Cloud Metadata Path 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-cloud-metadata-path .claude/skills/competition-cloud-metadata-path
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Competition Cloud Metadata Path 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 Cloud Metadata Path 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 Cloud Metadata Path 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 Cloud Metadata Path

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 decisive edge is not just reaching metadata, but proving how metadata-derived identity becomes accepted privilege.

Reply in Simplified Chinese unless the user explicitly requests English.

Quick Start

  1. Identify which metadata surface is active: instance metadata, workload identity, node identity, task role, or platform-specific token endpoint.
  2. Record the exact reachability path: local process, pod, container, proxy, SSRF surface, or host route.
  3. Separate metadata reachability from credential issuance and from downstream privilege acceptance.
  4. Keep token format, role identity, scope, and accepting API in compact evidence blocks.
  5. Reproduce the smallest metadata-to-accepted-privilege path that proves the challenge edge.

Workflow

1. Map Metadata Reachability

  • Record the metadata endpoint, required headers, hop limits, session tokens, workload selectors, or path prefixes.
  • Note whether access comes from direct local calls, pod networking, SSRF, sidecar, or host-level routing.
  • Keep the reaching surface and the metadata endpoint in one chain.

2. Prove Credential Or Identity Issuance

  • Show how the metadata response becomes a token, temporary credential, signed identity doc, or platform-specific workload identity.
  • Record expiration, role name, subject, audience, issuer, or cloud account mapping that matters downstream.
  • Distinguish raw metadata from usable credential material.

3. Reduce To The Decisive Trust Path

  • Compress the result to the smallest sequence: reaching surface -> metadata call -> credential issued -> accepted cloud or cluster action.
  • State clearly whether the weakness lives in reachability, metadata config, role trust, downstream policy, or workload binding.
  • If the challenge narrows to RBAC or cluster mutation after credential issuance, switch back to the tighter control-plane skill.

Read This Reference

  • Load references/cloud-metadata-path.md for the reachability checklist, token checklist, and evidence packaging.
  • If the hard part is first proving a server-side fetch primitive, SSRF reachability, or internal endpoint traversal before metadata itself, prefer $competition-ssrf-metadata-pivot.

What To Preserve

  • Metadata endpoints, required headers, reachability path, issued tokens or creds, and accepted APIs
  • Role names, audiences, issuers, account bindings, and privilege-bearing actions
  • The smallest replayable metadata-to-privilege chain

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 Cloud Metadata Path AI skill do?

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for cloud metadata services, instance identity, workload identity, link-local credential paths, role assumption, and metadata-to-privilege trust edges. Use when the user asks to inspect metadata-service access, instance credentials, pod or workload identity, link-local token paths, SSRF-to-metadata escalation, or explain how metadata-derived credentials turn into accepted cloud or control-plane privilege. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

Why use Competition Cloud Metadata Path on TypingMind?

Because you install it once and use it with any model. Competition Cloud Metadata Path 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 Cloud Metadata Path in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zhaoxuya520/reverse-skill/tree/main/CTF-Sandbox-Orchestrator/competition-cloud-metadata-path. 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 Cloud Metadata Path?

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 Cloud Metadata Path?

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

Is the Competition Cloud Metadata Path 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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