EMBER_CDD__Wdis 1.2.1

Elastic Malware Benchmark for Empowering Researchers

EMBER Feature Extraction

This repository allows the user to easily create a dataset using EMBERv3 features, starting from a collection of PE files.

If you want to work with EMBER2017 dataset (containing features from 1.1 million PE files scanned in or before 2017) or the EMBER2018 dataset (containing features from 1 million PE files scanned in or before 2018), or EMBER2024 please refer to the official repository.

Details of the selected features is available here: https://arxiv.org/pdf/2506.05074

Prerequisites

• Make sure you have a running and active version of Docker.

Usage:

1. Clone the repository and change directory:

   git clone [e-mail]:w-disaster/ember.git && cd ember
   

2. Setup the directory containing PE files. The directory should have the following structure:

   <YOUR_PE_MALWARE_DIR>/
   ├── <FAMILY_0>/
   │   ├── SHA_0_0
   │   ├── SHA_0_1
   │   ├── ...
   │   └──
   ├── <FAMILY_1>/
   │   ├── SHA_1_0
   │   ├── ...
   │   └──
   ├── ...
   └── 
   

   where FAMILY_0, FAMILY_1, ... are the directories named with the malware family and SHA_0_0, SHA_0_1, ... are the PE files named with their SHA256.

   The directory structure doesn't change if you want to do malware detection: simply create two directories benign and malicious as the malware families.

3. Configure the env variables and Run the static features extraction:

   MALWARE_DIR_PATH=<YOUR_MALWARE_DIR>
   PE_DATASET_NAME=<YOUR_PE_DATASET_NAME>
   EMBER_DATA_DIR=<YOUR_EMBER_OUTPUT_DIR>
   
   docker run \
   --name ember-feature-extraction \
   -e MALWARE_DIR_PATH=/usr/input_data/malware/ \
   -e FINAL_DATASET_FILENAME=/usr/app/dataset/$PE_DATASET_NAME.pkl \
   -e N_PROCESSES=64 \
   -v $MALWARE_DIR_PATH:/usr/input_data/malware/ \
   -v $EMBER_DATA_DIR:/usr/app/dataset/ \
   ghcr.io/malware-concept-drift-detection/ember-features-extraction:master