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More information we can see at DroidDetective GitHub repository. To know more about how DroidDdetective's pre-trained model works to find malware we can go to ashisdb's repository. Someone familiar with Android development can easily figure out what's wrong using DroidDetective, they doesn't need to read the whole program. This is how we can find if there is any malware or other malicious things inside an APK file.ĭuring the testing we noticed that some APK which doesn't contain malicious things also get detected by this tool due to misconfiguration or for some permission requirements. We can also saves the output in a json file by usng following command: python3 DroidDetective.py /home/kali/Desktop/browser.apk output.json That was a malware and DroidDetective found that there is some suspicious things within this malware. In the following screenshot we can see the output of the above command: First of all we need to clone DroidDetective's GitHub repository by using following command: git clone Now without wasting much time we are going to install DroidDetective on our Kali Linux system.
Using a RandomForest machine learning classifier, trained off the above data, from ~14 malware families and ~100 Google Play Store applications.Analysing the number of standard and proprietary permissions in use in the application's AndroidManifest.xml file.Analysing which of ~330 permissions are specified in the application's AndroidManifest.xml file.Some main features of DroidDetective is following: When provided with a path to an application (APK file) Droid Detective will make a prediction (using it's ML model) of if the application is malicious. DroidDetective written in Python and it is used for analyzing Android applications (APKs) for potential malware related behavior and configurations. It's a machine learning malware analysis framework for Android apps.
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