How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
The main features of abrignoni/aleapp are: OS X and Mobile Forensics, Mobile Forensics.
Projects with overlapping indexed features include: vgmoose/openbackupextractor — A free program for extracting data (like voicemails) from iPhone and iPad backups. mobsf/mobile-security-framework-mobsf — Mobile Security Framework is an automated security testing platform designed for the analysis of Android, iOS, and… jfarley248/meat — This toolkit aims to help forensicators perform different kinds of acquisitions on iOS devices. den4uk/andriller — 📱 Andriller - is software utility with a collection of forensic tools for smartphones. It performs read-only,… mac4n6/ios-frequent-locations-dumper — Dump the iOS Frequent Location binary plist files. azeemidrisi/phonesploit-pro — PhoneSploit-Pro is an Android exploitation and remote administration toolkit. It provides a system for remotely…
Dump the iOS Frequent Location binary plist files
📱 Andriller - is software utility with a collection of forensic tools for smartphones. It performs read-only, forensically sound, non-destructive acquisition from Android devices.
This toolkit aims to help forensicators perform different kinds of acquisitions on iOS devices
Mobile Security Framework is an automated security testing platform designed for the analysis of Android, iOS, and Windows mobile application binaries. It functions as a comprehensive suite for identifying security vulnerabilities, privacy risks, and malicious code within mobile software packages. The framework distinguishes itself by combining static and dynamic analysis techniques to evaluate application behavior. It performs static inspection of source code and binaries to detect insecure patterns, while simultaneously utilizing dynamic instrumentation and containerized sandboxing to monit