Software Vulnerability Detection

Installation

$ pip install -r requirements.txt

$ python setup.py install

Development

This project includes a number of helpers in the Makefile to streamline common development tasks.

Environment Setup

The following demonstrates setting up and working with a development environment:

### create a virtualenv for development

$ make virtualenv

$ source env/bin/activate


### run svd cli application

$ svd --help


### run pytest / coverage

$ make test

Releasing to PyPi

Before releasing to PyPi, you must configure your login credentials:

~/.pypirc:

[pypi]
username = YOUR_USERNAME
password = YOUR_PASSWORD

Then use the included helper function via the Makefile:

$ make dist

$ make dist-upload

Deployments

Docker

Included is a basic Dockerfile for building and distributing SVD, and can be built with the included make helper:

$ make docker

$ docker run -it svd --help

Usage

In this example the working directory is the project directory:

$ cd project_root_path/svd

Curate dataset:

$ svd curate -d dataset/dataset.json -o dataset/prepare/dataset.json

Mine dataset:

$ svd mine -d dataset/prepare/dataset.json -o dataset/feature_models/ -nlp dataset/extracted_features/nlp_features/

Evaluate ML models:

$ svd evaluate -d dataset/prepare/dataset.csv -nlp dataset/extracted_features/nlp_features -rp dataset/results -mp dataset/models -t 8 -m KNN

Evaluate CNN model:

$ svd evaluate-cnn -d dataset/prepare/dataset.csv -mp dataset/models/cnn

Plot zipf-log:

$ svd zipf -d dataset/dataset.json 

Plot histogram:

$ svd histogram -d dataset/dataset.json