Table of Contents

• 1. Introduction
• 2. Installation
  • 2.1. Dependencies
  • 2.2. Building
• 3. Configuration
  • 3.1. Unpacking the SDK
  • 3.2. Path to Executables
  • 3.3. Android Virtual Device
• 4. Usage
• 5. Emulab
• 6. Copyright

Introduction

maline is a free software Android malware detection framework. If you are an Org-mode user, you might want to read the executable version of this readme (the README.org file in the root). If you are interested in running extensive experiments with maline, take a look at the README file in the env/emulab directory, where you can find a lot of information on setting up a reproducible research environment.

Installation

*NOTE: We are in the process of debugging instructions for running maline in a virtual machine as there are some issues with that. Us, authors, got it successfully working on physical machines only.*

maline has been developed under Ubuntu 12.04.3 LTS. It is very likely it will work under other POSIX systems too (GNU/Linux and Mac alike). The Android version we tested maline with is Android 4.4.3 (API version 19), which is assumed throughout the readme.

To make it easier to start using maline, we created a Vagrant configuration file that sets up a virtual machine and install maline in it. If you want to run maline in such a way, you can simply run the following command in the root of this project:

vagrant up

and skip the rest of this section on dependencies and installing them. However, you will need to install an Android Virtual Device, as described below.

Dependencies

To use maline, you need the following:

• Android SDK - please download and use our build of the SDK. It is a stripped-down version with multiple bug fixes applied. Based on our experience, it is very unlikely maline will work correctly with the official version provided by Google. The official version ships without the fixes for multiple showstopping bugs.
• OpenJDK 7
• apktool - maline already ships with apktool, which is licensed under the Apache License 2.0.
• GNU Octave - a programming language for numerical computations. It is available through a Ubuntu's default repository.
• LIBSVM - maline already ships with LIBSVM, which is licensed under the Modified BSD License.
• R - an environment for statistical computing and graphics.
• Bash - ships with Ubuntu.
• Python - pretty much every system has an installation of it. We tested the tool with version 2.7.3.
• expect - a command line tool that automates interactive applications. It is available through a Ubuntu's default repository.

There are other dependencies we used throughout the project - such as for building Android from source - that you might not need to simply use maline. An extensive list of such dependencies and particular packages of the tools listed above can be found in env/emulab/prepare-node.sh.

Building

First obtain maline, e.g. from Github:

mkdir ~/projects
cd ~/projects
git clone git@github.com:soarlab/maline.git

Then change directory and build maline by running make:

cd maline
make

Configuration

Unpacking the SDK

Let's assume you have downloaded the custom SDK into your home directory. This is how you would unpack it:

tar -C ~/projects/ -xf ~/custom-android-sdk.tar.xz

Path to Executables

maline needs an environment variable named $MALINE, which should point to the tool root directory. In addition, it's bin/ directory should be in the PATH variable. A few tools provided with the SDK should be on the path as well. Therefore, execute the following commands:

export MALINE=~/projects/maline
PATH=$MALINE/bin:~/projects/custom-android-sdk/tools:~/projects/custom-android-sdk/platform-tools:$PATH

Android Virtual Device

maline executes Android apps in the Android Emulator, which comes within the Android SDK. The Emulator is a QEMU-based emulator that runs Android Virtual Devices (AVDs). By default, the ARM architecture is emulated, but that is very slow. Instead, on an x86 host machine it is better to create an x86 architecture-based virtual device image.

To create an x86-based AVD device, run:

avd-create.sh -a x86 -d maline-avd

The device creation process usually takes about 5 minutes.

Now you have a clean environment where each app can be executed. That is so because the above executed avd-create.sh command creates an AVD device with a clean snapshot that will be reloaded every time a new app is analyzed.

You can check that the device is created by executing:

android list avd

You should see a device with a name maline-avd.

Usage

In order to execute Android apps in maline, one first needs to create a list of the apps. For example, let's assume that there are 6 apps in the apps/ sub-directory within the root maline directory. Then their list can be stored to a file apk-list-file that has paths to the apps:

~/projects/maline/apps/com.nephoapp.anarxiv_1.apk
~/projects/maline/apps/org.ale.scanner.zotero_2.apk
~/projects/maline/apps/ed8a51225a3862e30817640ba7ec5b88ee04c98a.apk
~/projects/maline/apps/vu.de.urpool.quickdroid_49.apk
~/projects/maline/apps/to.networld.android.divedroid_1.apk
~/projects/maline/apps/4147f7d801c4bc5241536886309d507c5124fe3b.apk

It is assumed that malicious applications have file names consisting of 64 hexadecimal characters. That is how maline distinguishes malicious from benign apps in its learning phase.

To execute the apps and get their execution logs, run the following:

maline.sh -f apk-list-file -d maline-avd

As maline is executing, obtained .log files are parsed and as a result one .graph file per .log file is generated. From the .graph files we generate a feature vector for every analyzed app by executing:

create-feature-matrix.sh regular

Now it is possible to classify the data by running the following:

run-classdroid.sh FEATURES_FILE SHUFFLE_MODE [0 | 1]

The classification used is Support Vector Machine (SVM). A new folder will be created to store the temporary file used for the classification process and a file called "result.dat" will contain the final results.

The SVM methods used consists in classify the features using Linear and Polynomial Kernel (from 1st to 4th degree) applying 50% or 90% of the data set for training.

Emulab

In the development of maline, we have been using Emulab extensively. Emulab is a network testbed developed by The Flux Research Group from the University of Utah. We are thankful to the group for providing us with such an amazing computing infrastructure!

Copyright

maline is a free software framework licensed under the terms of the GNU Affero General Public License, version 3 or (at your option) any later version. You can find the text of the license in COPYING.

There are software dependencies for maline. All of them are free software too. Read their copyright notices for more information.

To the extent possible under law, Marko Dimjašević has waived all copyright and related or neighboring rights to this README (CC0).