Free Prompt Injection Lab
Practise prompt injection, jailbreaks and indirect injection against a simulated LLM assistant, mapped to the OWASP LLM Top 10 — with the defence for each. Free, from Neurobyte.
About this lab
Large language models introduce a new and unfamiliar attack surface, and prompt injection is its signature flaw — getting a model to ignore its instructions, leak its system prompt, or act on malicious content hidden in data it processes. This free prompt injection lab lets you practise direct injection, jailbreaks and indirect (data-borne) injection against a simulated assistant, each mapped to the OWASP Top 10 for LLM Applications, with the defence for every technique.
It's built for developers and security teams shipping AI features who need to understand these risks first-hand. Seeing how a guardrail is bypassed is the fastest way to learn how to build one that holds. Continue with our OWASP LLM Top 10 explorer and Secure AI Deployment Checklist to harden a real application.
Frequently asked questions
What is prompt injection?
Prompt injection is an attack on LLM applications where crafted input overrides the model's intended instructions — making it ignore safeguards, reveal its system prompt, or act on malicious instructions hidden in retrieved content (indirect injection).
How do you defend against prompt injection?
Treat model output as untrusted, separate instructions from user data, constrain tool/agent permissions, validate and sanitise inputs and outputs, and avoid putting secrets in prompts. The lab shows defences alongside each attack.
Who should use this lab?
Developers and security teams building features on LLMs, and anyone learning AI security. It maps directly to the OWASP LLM Top 10 so the practice translates to real risk reduction.