# Shinobi Security Blog ## blog - [Using AI to find logic flaws](https://blog.shinobi.security/using-ai-to-find-logic-flaws.md): How an AI Agent discovered a business logic flaw in a Popular Web Application - [AI Pentesting VS AI Code Scanning](https://blog.shinobi.security/ai-pentesting-vs-ai-code-scanning.md): A bakeoff between a next-gen pentester and code scanner - [More Than an Invoice: How Shinobi Averted a Child Safety Crisis](https://blog.shinobi.security/more-than-an-invoice-how-shinobi-averted-a-child-safety-crisis.md): Discover how our AI pentester, Shinobi, used human-like reasoning to uncover a critical data leak in a camp booking app that exposed the sensitive personal data of parents and the specific whereabouts - [The Ghost in the API: How Shinobi Turned a Single Flaw into Super Admin Access](https://blog.shinobi.security/the-ghost-in-the-api-how-shinobi-turned-a-single-flaw-into-super-admin-access.md): Follow our autonomous AI pentester, Shinobi, as it chains multiple critical API flaws to uncover a hidden super admin account and achieve a complete takeover of a modern IoT platform. - [One Parameter to Rule Them All: How a User Flaw Unlocked an Admin Fortress](https://blog.shinobi.security/one-parameter-to-rule-them-all-how-a-user-flaw-unlocked-an-admin-fortress.md): Follow the trail as our AI pentester, Shinobi, turns a simple parameter flaw on a user portal into the key that unlocks full administrative access to a supposedly secure backend, demonstrating a human - [Meet the world’s first AI-powered mobile app pentester](https://blog.shinobi.security/meet-the-worlds-first-ai-powered-mobile-app-pentester.md) - [Leaking OpenAI's Hidden GPT-5 System Prompt via Context Poisoning](https://blog.shinobi.security/leaking-openais-hidden-gpt-5-system-prompt-via-context-poisoning.md): A post-mortem on a critical vulnerability where a "smarter" reasoning model was tricked by a fundamental architectural flaw. What is "Juice: 64"? --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on a page URL with the `ask` query parameter: ``` GET https://blog.shinobi.security/using-ai-to-find-logic-flaws.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.