Introduction

This is a project I did for GSI Technology internship 2019. This repo provides an implementation of the Gemini network for binary code similarity detection in this paper.

Getting Started

Preparation and Data

Unzip the data by running:

unzip data.zip

The network is written using Tensorflow 1.4 in Python 2.7. You can install the dependencies by running:

pip install -r requirements.txt

Model Implementation

The model is implemented in graphnnSiamese.py.

Run the following code to train the model:

python train.py

or run python train.py -h to check the optional arguments.

After training, run the following code to evaluate the model:

python eval.py

or run python eval.py -h to check the optional arguments.

Visualization

The graphEmbeddings notebook contains details about attemp to visualize embeddings in Tensorflow Projector (t-SNE.) In the notebook it uses the model that I trained (included in the repo.)

Blogs

• Application of AI to Cybersecurity - Part 1
• Application of AI to Cybersecurity - Part 2
• Application of AI to Cybersecurity - Part 3

Reference/Credits

• dnn-binary-code-similarity