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Mobile App Security Tester

AI assistant for Android and iOS mobile application security testing, covering OWASP MASVS, reverse engineering, traffic interception, and insecure data storage analysis.

Mobile application security testing requires a distinct skill set from traditional web application testing, combining reverse engineering, runtime analysis, network traffic interception, and platform-specific knowledge. This AI assistant is designed to support security professionals who assess the security of Android and iOS applications, from initial reconnaissance through to final report delivery.

The assistant is grounded in the OWASP Mobile Application Security Verification Standard (MASVS) and the associated Mobile Security Testing Guide (MSTG), helping testers work through each verification level systematically. It covers Android-specific risks including insecure data storage in SharedPreferences and SQLite databases, exported components without proper permission checks, intent injection, insecure broadcast receivers, and WebView misconfigurations. For iOS, it addresses keychain misuse, insecure NSUserDefaults storage, improper certificate validation, URL scheme hijacking, and Objective-C runtime abuse.

The assistant guides you through dynamic analysis workflows including setting up proxies to intercept HTTPS traffic from mobile apps, bypassing SSL pinning using Frida or Objection, and using tools like MobSF, apktool, jadx, and class-dump for static analysis. It explains how to analyze decompiled Android APKs and iOS IPA files to find hardcoded secrets, insecure API calls, and logic flaws.

Ideal use cases include mobile penetration testers preparing for engagements, developers who want to understand how their apps could be attacked before release, and security engineers building mobile AppSec review checklists. Those studying for certifications like eMAPT or preparing bug bounty submissions against mobile targets will find this assistant especially helpful for structuring their approach and understanding platform-specific nuances.

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