A lab-aware AI mentor that guides your bug bounty learning without spoiling answers. Four modes let you choose how much help you need, from concept explanations to reasoning review.
Switch between modes depending on where you are in the learning process. Each mode adjusts the level of guidance to match your needs.
Ask the mentor to break down a security concept in plain language. If you do not understand what SSRF means or how CSP headers work, this mode gives you a clear explanation with examples before you attempt the lab.
Stuck on a lab step? The Nudge mode gives you a directional hint without revealing the solution. It might point you toward the right file to examine, suggest a technique to try, or ask a guiding question that narrows your focus.
After you submit an answer, ask the mentor to review your reasoning. It will evaluate your logic, identify gaps in your analysis, and explain where your thinking was correct or off-track without just telling you the right answer.
Once you have completed a lab or explicitly revealed the solution, this mode provides a full walkthrough. It covers the vulnerability, exploitation path, impact assessment, and remediation with code examples.
The mentor does not give generic advice. It understands the specific lab you are working on and tailors its guidance to the challenge at hand.
When you ask a question during a lab, the mentor has access to the lab’s scenario, the technology stack, the vulnerability category, and which step you are on. It uses this context to give relevant guidance.
The mentor knows which labs you have completed, which paths you are enrolled in, and what your quiz scores look like. It can recommend related labs or suggest revisiting concepts you have struggled with.
On beginner labs, the mentor explains more and nudges gently. On advanced labs, it assumes you know the basics and focuses on edge cases, novel techniques, or methodology refinements.
The mentor is designed for authorized security practice only. It enforces strict boundaries to prevent misuse.
The mentor will refuse to help with targeting real-world systems you do not own or do not have explicit permission to test. If you ask how to exploit a vulnerability against a live third-party website, it will decline and redirect you to the relevant BountyLabs lab instead.
The mentor will not generate malicious payloads for real-world use, provide exploit chains for unpatched vulnerabilities, or assist with any activity that falls outside authorized educational practice.
When discussing sensitive topics like authentication bypass or data exfiltration, the mentor always frames its guidance in the context of responsible disclosure, authorized testing, and educational understanding.
The mentor respects the BountyLabs scope. It encourages you to practice within contained labs and will not help you extend techniques to out-of-scope targets or real infrastructure.
Clear boundaries help you know when to ask the mentor and when to figure things out yourself.
See how the mentor responds in real learning scenarios across its four modes.
file parameter in the include statement. Where does user input first enter the application, and does it reach the include without sanitization? Try tracing from the query string to the sink.
Content-Security-Policy header would block inline script execution.
/api/orders/{id}. The endpoint checks authentication but not authorization. Changing the order ID in the URL to another user’s order ID returns their data. The fix: verify that the authenticated user owns the requested order before returning it. Use a server-side ownership check, not client-side filtering.
The AI mentor helps you learn security concepts deeply while keeping the challenge intact. Start a lab and ask the mentor whenever you need a nudge.
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