A simple framework to extract actionable data like C&C servers and phone numbers from Android malware samples.
Maldrolyzer is a Python-based framework for extracting actionable data from Android malware samples, such as command-and-control servers, phone numbers, and other indicators of compromise. It uses a modular plugin system to identify malware families and extract relevant information, helping security researchers analyze threats efficiently.
Security researchers, malware analysts, and threat intelligence professionals who need to quickly analyze Android APK samples and extract actionable intelligence for investigations.
It offers a simple, extensible framework with a plugin-based architecture, making it easy to add support for new malware families without complex modifications, and integrates with tools like Androguard for static analysis.
Simple framework to extract "actionable" data from Android malware (C&Cs, phone numbers etc.)
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Enables easy extension for new malware families by inheriting from the Plugin class, as described in the README, allowing researchers to add support without core modifications.
Provides a straightforward way to analyze APK samples with a single command, outputting structured data like hashes and C&C details, making it quick for initial assessments.
Leverages Androguard for static analysis, ensuring robust extraction of data from Android apps without reinventing analysis tools, as noted in the installation requirements.
Allows post-extraction tasks like database integration or C&C validation through output processors, enhancing flexibility for threat intelligence workflows, per the README.
Requires manual installation of multiple packages like Androguard, PyCrypto, and yara, which can be error-prone and time-consuming, as highlighted in the README's installation steps.
Relies on community contributions for plugins, so out-of-the-box support for malware families is sparse, forcing users to write custom plugins for new threats.
Focuses solely on static analysis via Androguard, lacking dynamic analysis capabilities that are essential for comprehensive malware behavior investigation.