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alipy

ALiPy: Active Learning in Python is an active learning python toolbox, which allows users to conveniently evaluate, compare and analyze the performance of active learning methods.

analyzepdf

Tool to help analyze PDF files

android-forensics

Open source Android Forensics app and framework

bayes

用java实现的贝叶斯分类算法。用于大数据的分类。

bert-for-cybersecurity-ner

An implementation of BERT for cybersecurity named entity recognition

binaryalert

BinaryAlert: Serverless, Real-time & Retroactive Malware Detection.

detection-of-pdf-malware

ember

feature-selector

Feature selector is a tool for dimensionality reduction of machine learning datasets

imagesetflower

This data set is created for identifying the source cameras of images.

kaggle-malware

Kaggle 'Microsoft Malware Classification Challenge' 3rd place solution

kaggle_microsoft_malware

code for kaggle competition Microsoft malware classification

kam1n0-community

The Kam1n0 Assembly Analysis Platform

learning_nlp

Learning nlp and reproduce some papers

machinelearning

malewaredetection

一个基于apk逆向分析并运用随机森林分类的重打包（恶意）apk检测的项目

malicious-document-detectation

Detecting malicious document based on file's signal processing.

malicious_document_scanner_pdf_and_office_file_using_ml

Tool for detecting malicious MS Office and PDF files by in depth OLE and Macro analysis.

malicious_pdf_detection

This project aims to detect if a pdf file is clean or malicious using Machine Leaning Techniques

malpdfobj

Builds json representation of PDF malware sample

malware

https://github.com/zbetcheckin/PDF_analysis.git

malware-classification

Microsoft Malware Classification Challenge in Spark on Kaggle competition.

malware-detection

Malware Detection and Classification Using Machine Learning

malware-detection-using-deep-learning

Firstly, we generate images from benign and malware executable files. Secondly, by using deep learning, we train a model to detect malware files. Then, by the trained model, we try to classify a file as malware or not. By using malware images and deep learning, we can detect malware fast since we do not need any static analysis or dynamic analysis.

malware-gan-attack

We implement MalGAN to attack several PDF classifiers and evaluate the robustness of those models.

malware-windows-audit-log-detection

Detection of malware using dynamic behavior and Windows audit logs

microsoft-malware-challenge

microsoft_malware_prediction_kaggle_2nd

This repository contains the winning solution (2nd place) of the Macrosoft Maleware Prediction Challenge on Kaggle.

modal

A modular active learning framework for Python

ngram2vec

Four word embedding models implemented in Python. Supporting arbitrary context features