javascript-malware-collection - Collection of almost 40.000 javascript malware samples

  •        13

A collection of almost 40.000 Javascript malware samples. Sorted according a date of capture.

https://github.com/HynekPetrak/javascript-malware-collection

Tags
Implementation
License
Platform

   




Related Projects

malware-jail - Sandbox for semi-automatic Javascript malware analysis, deobfuscation and payload extraction

  •    Javascript

malware-jail is written for Node's 'vm' sandbox. Currently implements WScript (Windows Scripting Host) context env/wscript.js, at least the part frequently used by malware. Internet browser context is partialy implemented env/browser.js. Runs on any operating system. Developed and tested on Linux, Node.js v6.6.0.

theZoo - A repository of LIVE malwares for your own joy and pleasure

  •    Python

theZoo is a project created to make the possibility of malware analysis open and available to the public. Since we have found out that almost all versions of malware are very hard to come by in a way which will allow analysis, we have decided to gather all of them for you in an accessible and safe way. theZoo was born by Yuval tisf Nativ and is now maintained by Shahak Shalev. theZoo's purpose is to allow the study of malware and enable people who are interested in malware analysis (or maybe even as a part of their job) to have access to live malware, analyse the ways they operate, and maybe even enable advanced and savvy people to block specific malware within their own environment.

yarGen - yarGen is a generator for YARA rules

  •    Python

The main principle is the creation of yara rules from strings found in malware files while removing all strings that also appear in goodware files. Therefore yarGen includes a big goodware strings and opcode database as ZIP archives that have to be extracted before the first use. Since version 0.12.0 yarGen does not completely remove the goodware strings from the analysis process but includes them with a very low score depending on the number of occurences in goodware samples. The rules will be included if no better strings can be found and marked with a comment /* Goodware rule */. Force yarGen to remove all goodware strings with --excludegood. Also since version 0.12.0 yarGen allows to place the "strings.xml" from PEstudio in the program directory in order to apply the blacklist definition during the string analysis process. You'll get better results.

magento-malware-scanner - Scanner, signatures and the largest collection of Magento malware

  •    HTML

Magento is a profitable target for hackers. Since 2015, I have identified more than 40.000 compromised stores. In most cases, malware is inserted that will a) intercept customer data, b) divert payments or c) uses your customers for cryptojacking. This project contains both a fast scanner to quickly find malware, and a collection of Magento malware signatures. They are recommended by Magento and used by the US Department of Homeland Security, the Magento Marketplace, Magereport, the Mage Security Council and many others.


Limon - Limon is a sandbox developed as a research project written in python, which automatically collects, analyzes, and reports on the run time indicators of Linux malware

  •    Python

Limon is a sandbox developed as a research project written in python, which automatically collects, analyzes, and reports on the run time indicators of Linux malware. It allows one to inspect the Linux malware before execution, during execution, and after execution (post-mortem analysis) by performing static, dynamic and memory analysis using open source tools. Limon analyzes the malware in a controlled environment, monitors its activities and its child processes to determine the nature and purpose of the malware. It determines the malware's process activity, interaction with the file system, network, it also performs memory analysis and stores the analyzed artifacts for later analysis.

Yara - The pattern matching swiss knife for malware researchers

  •    C

YARA is a tool aimed at (but not limited to) helping malware researchers to identify and classify malware samples. With YARA you can create descriptions of malware families (or whatever you want to describe) based on textual or binary patterns. Each description, a.k.a rule, consists of a set of strings and a boolean expression which determine its logic.

multiscanner - Modular file scanning/analysis framework

  •    Javascript

MultiScanner is a file analysis framework that assists the user in evaluating a set of files by automatically running a suite of tools for the user and aggregating the output. Tools can be custom built Python scripts, web APIs, software running on another machine, etc. Tools are incorporated by creating modules that run in the MultiScanner framework. Modules are designed to be quickly written and easily incorporated into the framework. Currently written and maintained modules are related to malware analytics, but the framework is not limited to that scope. For a list of modules you can look in modules/. Descriptions and config options can be found on the Analysis Modules page.

malware - Malware Samples

  •    C++

Malware Samples. Uploaded to GitHub for those want to analyse the code. This repository is for research purposes only, the use of this code is your responsibility.

linux.mirai - Leaked Linux.Mirai Source Code for Research/IoC Development Purposes

  •    C

Uploaded for research purposes and so we can develop IoC's and such. See "post.txt" (transcribed in post.md) for the post in which it leaks, if you want to know how it is all set up and the likes.

fame - FAME Automates Malware Evaluation

  •    Python

FAME is a recursive acronym meaning “FAME Automates Malware Evaluation”. It is meant to facilitate analysis of malicious files, leveraging as much knowledge as possible in order to speed up and automate end-to-end analysis.

Noriben - Noriben - Portable, Simple, Malware Analysis Sandbox

  •    Python

Noriben is a Python-based script that works in conjunction with Sysinternals Procmon to automatically collect, analyze, and report on runtime indicators of malware. In a nutshell, it allows you to run your malware, hit a keypress, and get a simple text report of the sample's activities. Noriben allows you to not only run malware similar to a sandbox, but to also log system-wide events while you manually run malware in ways particular to making it run. For example, it can listen as you run malware that requires varying command line options, or user interaction. Or, to watch the system as you step through malware in a debugger.

awesome-yara - A curated list of awesome YARA rules, tools, and people.

  •    

A curated list of awesome YARA rules, tools, and resources. Inspired by awesome-python and awesome-php. YARA is an ancronym for: YARA: Another Recursive Ancronym, or Yet Another Ridiculous Acronym. Pick your choice.

malsub - A Python RESTful API framework for online malware analysis and threat intelligence services

  •    Python

malsub is a Python 3.6.x framework that wraps several web services of online malware and URL analysis sites through their RESTful Application Programming Interfaces (APIs). It supports submitting files or URLs for analysis, retrieving reports by hash values, domains, IPv4 addresses or URLs, downloading samples and other files, making generic searches and getting API quota values. The framework is designed in a modular way so that new services can be added with ease by following the provided template module and functions to make HTTP GET and POST requests and to pretty print results. This approach avoids having to write individual and specialized wrappers for each and every API by leveraging what they have in common in their calls and responses. The framework is also multi-threaded and dispatches service API functions across a thread pool for each input argument, meaning that it spawns a pool of threads per each file provided for submission or per each hash value provided for report retrieval, for example. Most of these services require API keys that are generated after registering an account in their respective websites, which need to be specified in the apikey.yaml file according to the given structure. Note that some of the already bundled services are limited in supported operations due to the fact that they were developed with free API keys. API keys associated with paid subscriptions are allowed to make additional calls not open to the public and may not be restricted by a given quota. Yet, malsub can process multiple input arguments and pause between requests as a workaround for cooldown periods.

botnets - This is a collection of #botnet source codes, unorganized. For EDUCATIONAL PURPOSES ONLY

  •    C++

Many projects are duplicates or revisions of each other. Many of them have outdated depedencies. My goal is to collectively put them together so that they are compilable and help people interested in malware research analyze them and learn from these samples.

Malware - Course materials for Malware Analysis by RPISEC

  •    

This repository contains the materials as developed and used by RPISEC to teach Malware Analysis at Rensselaer Polytechnic Institute in Fall 2015. This was a university course developed and run soley by students, primarily using the Practical Malware Analysis book by Michael Sikorski and Andrew Honig, to teach skills in reverse engineering, malicious behaviour, malware, and anti-analysis techniques. The Practical Malware Analysis (PMA) book is where many RPISEC members and alumn started. The book reads very well, is full of information, and the lab walkthroughs in the back are invaluable. We didn't want to re-invent the wheel so we structured most of the class around the book. Students were expected to have read the relevant PMA book chapters before class, allowing us to spend much more class time demonstrating skills and techniques and walking through hands-on examples with the students.

malcom - Malcom - Malware Communications Analyzer

  •    Python

Malcom is a tool designed to analyze a system's network communication using graphical representations of network traffic, and cross-reference them with known malware sources. This comes handy when analyzing how certain malware species try to communicate with the outside world. The aim of Malcom is to make malware analysis and intel gathering faster by providing a human-readable version of network traffic originating from a given host or network. Convert network traffic information to actionable intelligence faster.

HaboMalHunter - HaboMalHunter is a sub-project of Habo Malware Analysis System (https://habo

  •    Python

HaboMalHunter is a sub-project of Habo Malware Analysis System (https://habo.qq.com), which can be used for automated malware analysis and security assessment on the Linux system. The tool help security analyst extracting the static and dynamic features from malware effectively and efficiently. The generated report provides significant information about process, file I/O, network and system calls. The tool can be used for the static and dynamic analysis of ELF files on the Linux x86/x64 platform.

gym-malware

  •    Python

This is a malware manipulation environment for OpenAI's gym. OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms. This makes it possible to write agents that learn to manipulate PE files (e.g., malware) to achieve some objective (e.g., bypass AV) based on a reward provided by taking specific manipulation actions. Create an AI that learns through reinforcement learning which functionality-preserving transformations to make on a malware sample to break through / bypass machine learning static-analysis malware detection.

al-khaser - Public malware techniques used in the wild: Virtual Machine, Emulation, Debuggers, Sandbox detection

  •    C++

al-khaser is a PoC "malware" application with good intentions that aims to stress your anti-malware system. It performs a bunch of common malware tricks with the goal of seeing if you stay under the radar. You can download the latest release here: x86 | x64.