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wtf is llmvault?

cybersunil/llmvault — explained in plain English

Analysis updated 2026-05-18

231PythonAudience · developerComplexity · 2/5Setup · easy

TL;DR

A deliberately vulnerable, offline training platform of 25 unlockable labs for learning to attack and defend against OWASP's top LLM security risks.

Mindmap

mindmap
  root((LLMVault))
    What it does
      OWASP LLM training
      CTF style labs
      Learn the fix
    Tech stack
      Python
      Flask
      Docker
    Lab tiers
      Core 10 labs
      Advanced multi turn
      Expert encrypted
    Use cases
      Security training
      Team CTF range
    Audience
      Developers
      Security learners

Code map

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filefunction / class

Why would anyone build with this?

REASON 1

Practice exploiting common LLM vulnerabilities like prompt injection and system prompt leakage in a safe, offline environment.

REASON 2

Run a self hosted CTF style security training range for a team learning about AI security.

REASON 3

Study the built in defensive fix explanations after solving each lab to learn how to prevent that vulnerability.

REASON 4

Progress through core, advanced, and expert tiers to practice increasingly complex, multi turn AI attacks.

What's in the stack?

PythonFlaskDocker

How it stacks up

cybersunil/llmvaulthellogithub-team/hydrainclusionai/avernet
Stars231231231
LanguagePythonPythonPython
Setup difficultyeasymoderatemoderate
Complexity2/52/54/5
Audiencedeveloperdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you spin it up?

Difficulty · easy Time to first run · 5min

Runs fully offline with scripted assistants, no API key required, not meant to be exposed to the public internet.

Wtf does this do

LLMVault is a training platform for learning how AI chat systems can be attacked and defended, built around the OWASP Top 10 list of security risks for LLM applications. It is deliberately full of security holes on purpose, similar in spirit to older training tools like WebGoat, but focused entirely on AI systems instead of regular web apps. The README is clear that everything in it is intentionally insecure and meant only for authorized, self hosted learning, not for exposing to the public internet or reusing in a real product. The platform has 25 puzzle style labs split into three levels that unlock one after another. The first ten labs each cover one category from the OWASP list, things like prompt injection, leaking sensitive information, or a system giving an AI tool too much unchecked power. The next ten labs are harder and require a multi step conversation to solve, such as gradually talking a chatbot into breaking its own rules. The final five labs model real world attack patterns and are encrypted inside the repository, only unlocked by a private access key the project's author hands out once someone finishes the first two tiers. To use it, you install the Python requirements and run a single script, or you can run it with Docker instead, and it works fully offline with no external API key needed since the vulnerable chat assistants are scripted rather than connected to a real AI service. Your progress and score are saved to a simple file so they survive restarts, and there is no separate database to set up. As you play, you set a player name once, work through each lab to make its assistant reveal a hidden flag, and can spend points on hints if you get stuck. After finishing a tier you get a shareable completion card, and after solving a lab a panel explains the defensive fix behind that category's vulnerability, so the tool pairs breaking things with learning how to prevent them.

Yoink these prompts

Prompt 1
Walk me through solving the first core lab in LLMVault about prompt injection.
Prompt 2
Explain the difference between the core, advanced, and expert lab tiers in this repo.
Prompt 3
Show me how to run this project with Docker instead of installing Python dependencies directly.
Prompt 4
Summarize the OWASP LLM Top 10 categories this repo's core labs are based on.
Prompt 5
Explain how the completion card and expert access key unlock system works in this repo.

Frequently asked questions

wtf is llmvault?

A deliberately vulnerable, offline training platform of 25 unlockable labs for learning to attack and defend against OWASP's top LLM security risks.

What language is llmvault written in?

Mainly Python. The stack also includes Python, Flask, Docker.

How hard is llmvault to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is llmvault for?

Mainly developer.

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