Competition Kernel Container Escape

CommunityPopular

zhaoxuya520

competition-kernel-container-escape

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for kernel attack surface, namespace and cgroup boundaries, container isolation assumptions, syscall paths, and escape primitive verification. Use when the user asks to analyze container-to-host escape paths, kernel exploit prerequisites, namespace crossover, capability misuse, or prove whether an exploit primitive crosses the sandbox boundary. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

Overview

Publisher	zhaoxuya520
Repository	`reverse-skill`
Skill name	`competition-kernel-container-escape`
Stars	36.3K
Forks	5K
Bundled files	2
License	MIT
Links	Skill source Repository

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 Kernel Container Escape AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/zhaoxuya520/reverse-skill/tree/main/CTF-Sandbox-Orchestrator/competition-kernel-container-escape

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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-kernel-container-escape .claude/skills/competition-kernel-container-escape

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Competition Kernel Container Escape 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 Kernel Container Escape 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 Kernel Container Escape 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 Kernel Container Escape

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 step is proving a boundary crossing between containerized context and host or higher-privilege kernel context.

Reply in Simplified Chinese unless the user explicitly requests English.

Quick Start

Map runtime isolation first: namespaces, cgroups, seccomp, capabilities, LSM, and mount boundaries.
Separate exploit prerequisite, primitive, and boundary-crossing proof.
Record kernel version, config hints, runtime options, and reachable syscall surface.
Keep instrumented observations separate from pristine challenge path.
Reproduce one minimal primitive-to-boundary-crossing chain.

Workflow

1. Map Isolation And Kernel Surface

Record namespace map, cgroup mode, capabilities, seccomp profile, AppArmor or SELinux state, mounted filesystems, and runtime sockets.
Note kernel version, distro build hints, module exposure, and container runtime behavior.
Keep host and container observations linked to exact node and context.

2. Prove Exploit Primitive And Crossover

Show controllable input, trigger condition, affected object, and observable kernel or runtime state change.
Capture before and after identity, namespace, mount, or process visibility to prove boundary crossing.
Distinguish crash-only behavior from stable capability gain.

3. Reduce To Decisive Escape Chain

Compress to: prerequisite state -> primitive trigger -> boundary crossing evidence -> resulting host-level capability.
State whether root cause is kernel vulnerability, runtime misconfiguration, capability overgrant, or namespace leak.
If path relies mostly on credential replay after initial foothold, hand off to Linux credential pivot skill.

Read This Reference

Load references/kernel-container-escape.md for isolation checklist, primitive checklist, and parity guidance.

What To Preserve

Kernel and runtime context, capability set, seccomp or LSM state, and namespace map
Primitive trigger data, boundary crossing evidence, and resulting capability
One minimal reproducible chain from container context to host-relevant effect

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 Kernel Container Escape AI skill do?

Why use Competition Kernel Container Escape on TypingMind?

Because you install it once and use it with any model. Competition Kernel Container Escape 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 Kernel Container Escape in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zhaoxuya520/reverse-skill/tree/main/CTF-Sandbox-Orchestrator/competition-kernel-container-escape. 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 Kernel Container Escape?

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 Kernel Container Escape?

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

Is the Competition Kernel Container Escape 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.

View all

Eval Harness

affaan-m

CommunityPopular

Framework formal de evaluación para sesiones de Claude Code que implementa principios de desarrollo orientado a evals (EDD)

Frontend Patterns

Patrones de desarrollo frontend para React, Next.js, gestión de estado, optimización de rendimiento y buenas prácticas de UI.

Golang Patterns

Patrones idiomáticos de Go, buenas prácticas y convenciones para construir aplicaciones Go robustas, eficientes y mantenibles.

Golang Testing

Patrones de pruebas Go incluyendo pruebas basadas en tablas, subpruebas, benchmarks, fuzzing y cobertura de código. Sigue la metodología TDD con prácticas idiomáticas de Go.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Competition Kernel Container Escape

Quick Start

Workflow

1. Map Isolation And Kernel Surface

2. Prove Exploit Primitive And Crossover

3. Reduce To Decisive Escape Chain

Read This Reference

What To Preserve

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now