📰 Originally published on Securityelites — AI Red Team Education — the canonical, fully-updated version of this article.
🤖 AI/LLM HACKING COURSE
FREE
Part of the AI/LLM Hacking Course — 90 Days
Day 30 of 90 · 33.3% complete
⚠️ Authorised Targets Only: Bug bounty testing is only authorised within the specific program scope. Read the scope carefully before testing any AI feature — many programs added AI features after their original scope was written and the coverage is ambiguous. When in doubt, contact the program before testing.
The first AI bug bounty report I submitted was technically accurate and completely ineffective. I’d found a system prompt extraction on a major AI product, documented the T6 translation technique, shown the extracted content, calculated the CVSS score. Triage marked it Informational after four days. I asked why. The response: “The system prompt doesn’t contain sensitive data and prompt extraction in your own session doesn’t affect other users.” They were right. The finding was real, the technique was correct, and the specific target I’d chosen had a system prompt containing nothing more sensitive than the product’s name and tone instructions. I’d found a Medium vulnerability and submitted it expecting Critical payout.
The lesson took about a week to sink in. Bug bounty payout isn’t proportional to the sophistication of the technique. It’s proportional to the business impact of the specific finding on that specific target. The same extraction technique that produced an Informational on the first target produced a Critical finding three months later when I applied it to a different target — one whose system prompt contained a production API key with write access to a billing system. Same technique. Different target. Completely different outcome. Day 30 covers how to find and report AI vulnerabilities in ways that actually get paid: target selection, impact maximisation, report quality, and the platform-specific considerations that determine whether your finding gets triaged up or down.
Have you submitted an AI security finding to a bug bounty program?
No — I didn’t know AI bugs were in scope I’ve submitted one or two I’ve received rewards for AI findings Regular AI bug bounty hunter
🎯 What You’ll Master in Day 30
Read bug bounty scope documents to identify AI coverage and ambiguity
Select high-value AI targets based on feature access, data sensitivity, and tool integration
Apply the Day 27 phased methodology within the bug bounty time and constraint context
Write AI bug reports that triage teams can follow and reproduce exactly
Calculate and justify CVSS severity for AI findings to defend your payout tier
Handle duplicate decisions and scope disputes professionally
⏱️ Day 30 · 3 exercises · Think Like Hacker + Browser + Kali Terminal ### ✅ Prerequisites - Day 25 — AI Security Report Writing — the finding format and CVSS guidance from Day 25 applies directly to bug bounty reports; the audience is different but the structure is identical - Day 27 — AI Red Team Operations — the phased methodology from Day 27 applies within bug bounty constraints; understanding the full methodology helps adapt it to the bounty context - Active accounts on HackerOne and Bugcrowd — Exercise 2 reads live program scope documents ### 📋 AI Bug Bounty — Day 30 Contents 1. Scope Analysis — Is This AI Feature Actually In Scope? 2. High-Value Target Selection for AI Bug Bounty 3. Impact Maximisation — What Determines AI Finding Value 4. Writing the AI Bug Report That Gets Paid 5. Defending Your Severity Rating 6. Platform-Specific Notes for AI Bug Bounty in 2026 Day 30 marks one-third of the course complete. Everything from Days 1 through 29 — OWASP LLM Top 10, automation, extraction, agent assessment, supply chain, adversarial ML, enterprise frameworks — feeds into the bug bounty workflow. Day 31 goes deeper on LLM data exfiltration techniques — the specific attack paths that produce the LLM02 and LLM07 findings that consistently earn the highest bug bounty payouts.
Scope Analysis — Is This AI Feature Actually In Scope?
Scope documents for established bug bounty programs were usually written before the AI features they’re now running. An AI chat assistant added to a web application in 2024 may or may not be explicitly covered by a scope document written in 2022. Three patterns: the AI feature is at a subdomain explicitly in scope (test it), the AI feature calls a third-party API that’s explicitly out of scope (the underlying API is out of scope, but the application’s handling of its output may still be in scope), and the AI feature is ambiguously covered (ask the program before testing).
The ask-before-testing approach is worth the 24-48 hour delay. A question submitted to the program creates a paper trail that “the AI feature was discussed before testing” — which protects you if the program later claims the feature was out of scope. Keep the question and the answer. If they confirm the AI feature is in scope, you have written authorisation. If they say it’s out of scope, you saved the testing time for something else.
High-Value Target Selection for AI Bug Bounty
AI features worth targeting in bug bounty are the ones where the blast radius of a successful injection or extraction is high enough to justify the testing time. The hierarchy: AI agents with tool access (LLM06 chain findings, typically Critical), AI features handling authenticated user data (LLM02 with sensitivity multiplier), AI systems with RAG pipelines that contain proprietary or regulated content (LLM08 persistent injection), and AI-powered decision systems where the AI’s output influences real-world decisions (biased or manipulated output = high business impact).
📖 Read the complete guide on Securityelites — AI Red Team Education
This article continues with deeper technical detail, screenshots, code samples, and an interactive lab walk-through. Read the full article on Securityelites — AI Red Team Education →
This article was originally written and published by the Securityelites — AI Red Team Education team. For more cybersecurity tutorials, ethical hacking guides, and CTF walk-throughs, visit Securityelites — AI Red Team Education.
Top comments (0)