Competition Ssrf Metadata Pivot logo

Competition Ssrf Metadata Pivot

CommunityPopular
zhaoxuya520
competition-ssrf-metadata-pivot

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for SSRF reachability, internal route probing, metadata-service access, credential pivoting, and token-to-accepted-privilege chains. Use when the user asks to trace SSRF sources, internal hosts, metadata endpoints, link-local tokens, service-account credentials, or explain how a server-side fetch edge turns into accepted access. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

Overview

Publisherzhaoxuya520
Repositoryreverse-skill
Skill namecompetition-ssrf-metadata-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 Ssrf Metadata 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-ssrf-metadata-pivot .claude/skills/competition-ssrf-metadata-pivot
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Competition Ssrf Metadata 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 Ssrf Metadata 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 Ssrf Metadata 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 SSRF Metadata 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 decisive path runs through server-side request capability, internal service reachability, or metadata-derived credentials.

Reply in Simplified Chinese unless the user explicitly requests English.

Quick Start

  1. Separate the SSRF source, forwarding layer, reachable target, and accepted downstream credential edge.
  2. Record request method, URL construction, header behavior, redirects, DNS or host overrides, and response shaping before mutation.
  3. Map internal host, metadata endpoint, token extraction, and accepting service as one chain.
  4. Distinguish read-only reachability from credential-bearing access.
  5. Reproduce the smallest SSRF-to-accepted-access path.

Workflow

1. Map SSRF Reachability

  • Record source primitive: URL parameter, webhook, image fetcher, importer, proxy endpoint, or backend callback.
  • Note normalization steps: scheme filtering, host allowlists, redirects, DNS resolution, path rewrite, and header injection.
  • Keep target host, protocol, and response behavior tied to the exact SSRF source.

2. Trace Metadata And Credential Pivot

  • Show whether metadata endpoints, internal control APIs, or workload identity services are reachable.
  • Record token fields, role scope, service account, expiration, and where the token is accepted.
  • Distinguish credential extraction success from accepted privilege at a downstream service.

3. Reduce To Decisive SSRF Chain

  • Compress to: SSRF source -> internal or metadata target -> credential or sensitive response -> accepted replay or API access.
  • State whether the decisive edge is parser bypass, allowlist bypass, redirect abuse, header confusion, or metadata trust.
  • If the task becomes mostly cloud identity policy analysis, hand off to the tighter cloud metadata skill.

Read This Reference

  • Load references/ssrf-metadata-pivot.md for SSRF checklists, metadata pivots, and evidence packaging.

What To Preserve

  • SSRF source point, URL construction rules, reachable hosts, and response deltas
  • Extracted token or credential fields, scope, and accepting service
  • One minimal SSRF-to-accepted-access replay path

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 Ssrf Metadata Pivot AI skill do?

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for SSRF reachability, internal route probing, metadata-service access, credential pivoting, and token-to-accepted-privilege chains. Use when the user asks to trace SSRF sources, internal hosts, metadata endpoints, link-local tokens, service-account credentials, or explain how a server-side fetch edge turns into accepted access. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

Why use Competition Ssrf Metadata Pivot on TypingMind?

Because you install it once and use it with any model. Competition Ssrf Metadata 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 Ssrf Metadata 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-ssrf-metadata-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 Ssrf Metadata 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 Ssrf Metadata Pivot?

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

Is the Competition Ssrf Metadata 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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