Static and dynamic Android application security analysis
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Updated
Jun 2, 2024 - Python
Static and dynamic Android application security analysis
The Ptidej tool suite to evaluate and enhance the quality of object-oriented programs, promoting the use of patterns, at the language-, design-, or architectural-levels
Find and verify secrets
Triton is a dynamic binary analysis library. Build your own program analysis tools, automate your reverse engineering, perform software verification or just emulate code.
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The Mobile Application Security Testing Guide (MASTG) is a comprehensive manual for mobile app security testing and reverse engineering. It describes the technical processes for verifying the controls listed in the OWASP Mobile Application Security Verification Standard (MASVS).
Terminator is a compact utility coded in C#, designed to end processes that have RtlSetProcessIsCritical enabled.
A multi-body simulation software
Radare2 and Frida better together.
The Spacedyn is a library for the kinematic and dynamic analysis and simulation of articulated multi-body systems with a moving base written as MATLAB toolbox or C++ library. Examples of such systems are a satellite with mechanical appendages, a free-flying space robot, a wheeled mobile robot, and a walking robot, all of which make motions in th…
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Python API Monitor for Android apps
Mobile Security Framework (MobSF) is an automated, all-in-one mobile application (Android/iOS/Windows) pen-testing, malware analysis and security assessment framework capable of performing static and dynamic analysis.
⚙️ A curated list of dynamic analysis tools and linters for all programming languages, binaries, and more.
Automated code reviews via mutation testing - semantic code coverage.
Platform for Architecture-Neutral Dynamic Analysis
Collect crash (or UndefinedBehaviorSanitizer error) reports, triage, and estimate severity.
Binary instrumentation framework based on FRIDA
DIG is a numerical invariant generation tool. It infers program invariants or properties over (i) program execution traces or (ii) program source code. DIG supports many forms of numerical invariants, including nonlinear equalities, octagonal and interval properties, min/max-plus relations, and congruence relations.
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