(Please consider using the latest code of our updated paper: MAB-Malware: A Reinforcement Learning Framework for Attacking Static Malware Classifiers.)

Adversarial Malware

This repository is the implementation of the paper "Automatic Generation of Adversarial Examples for Interpreting Malware Classifiers".

To ensure the ethical use of this code, please provide the following information by filling this form: https://docs.google.com/forms/d/e/1FAIpQLSdQGt53IQCVfINgvlx1wWo4rFt2W0eiaHDFhHSN-MnArYSZ4Q/viewform

I will let you know when the source code is ready to share with you.

If you use this code in a publication, please cite the following paper:

```
@article{song2020automatic,
  title={Automatic Generation of Adversarial Examples for Interpreting Malware Classifiers},
  author={Song, Wei and Li, Xuezixiang and Afroz, Sadia and Garg, Deepali and Kuznetsov, Dmitry and Yin, Heng},
  journal={arXiv preprint arXiv:2003.03100},
  year={2020}
}
```