Collaborative malware analysis framework

Originally presented at [SSTIC 2016] ( https://www.sstic.org/2016/presentation/demarche_d_analyse_collaborative_de_codes_malveillants/ )

This is a beta version, use at your own risk!

This platform is designed to help analysts to reverse malwares, as a team. We provide an engine to automate the analysis tasks, and identify hotpoints in the binary, and collaboratively reverse binaries.

Tasks are loaded from the app/controllers/tasks directory, and must inherit from the Task object. In particular, several tasks are already implemented:

• AnalyzeIt, a ruby script based on metasm, wich is used to identify interesting points in the binary. The goal is to help the analyst by giving hints about where to start. For example, we try to identify crypto loops, functions wich calls sensitive API (file, process, network, ...)

• Peinfo : We load the PE metadata with the peinfo library.

• Strings : extract ASCII and Unicode strings

We use several signature models to classify malware:

• Yara
• imphash
• Machoc

Machoc is a CFG-based algorithm to classify malware. For more informations, please refer to the following [paper] (https://www.sstic.org/media/SSTIC2016/SSTIC-actes/demarche_d_analyse_collaborative_de_codes_malveill/SSTIC2016-Article-demarche_d_analyse_collaborative_de_codes_malveillants-chevalier_le-berre_pourcelot.pdf)

This is an IDAPython script, wich is used to synchronize the names and comments with the knowledge base, and with other users database

On a Ubuntu derivative: sudo apt-get install -y git virtualenv ruby libffi-dev python-dev graphviz gcc libssl-dev python-pip

    ./install.sh
    ./utils/db_create.py

    ./run.py

Access it at http://localhost:5000

We use virtualenv, so don't forget to activate the environment

    source flask/bin/activate