Cerebro
APKiD
| Cerebro | APKiD | |
|---|---|---|
| 1 | 1 | |
| 19 | 1,904 | |
| - | 2.3% | |
| 1.9 | 7.3 | |
| about 1 year ago | 9 days ago | |
| YARA | YARA | |
| MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Cerebro
APKiD
-
What is your opinion about "app packers"? Should Google ban their use?
Turns out a little Googling was my friend, there's already an open source tool to identify most packers, obfuscators, and whatnot: https://github.com/rednaga/APKiD
What are some alternatives?
reversinglabs-yara-rules - ReversingLabs YARA Rules
AMAYARA-Lab - The アマヤラ Lab project provides a ready-to-use Jupyter Lab environment to help out with Android malware analysis using YARA rules.
malware-ioc - Indicators of Compromises (IOC) of our various investigations
yaralyzer - Visually inspect and force decode YARA and regex matches found in both binary and text data. With Colors.
audit-node-modules-with-yara - Audit Node Module folder with YARA rules to identify possible malicious packages hiding in node_moudles
binlex - A Binary Genetic Traits Lexer Framework
signature-base - YARA signature and IOC database for my scanners and tools
LibreAV - A free and open source anti-malware for android using machine learning.
Ukraine-Cyber-Operations - Curated Intelligence is working with analysts from around the world to provide useful information to organisations in Ukraine looking for additional free threat intelligence. Slava Ukraini. Glory to Ukraine.
MDML - Malware Detection using Machine Learning (MDML)