This repository contains sample programs that mimick behavior found in real-world malware. The goal is to provide source code that can be compiled and used for learning purposes, without having to worry about handling live malware.

Malware Sample Sources

A large repository of malware samples with 2500+ malware samples & source codes for a variety of platforms by Cryptware Apps.

Malware source code samples leaked online uploaded to GitHub for those who want to analyze the code

ph0neutria is a malware zoo builder that sources samples straight from the wild. Everything is stored in Viper for ease of access and manageability.

A simple, open-source, easy to use, and free download manager for malware samples.

A feed of malware samples curated from threat intelligence sources.

Malware source code samples leaked online uploaded to GitHub for those who want to analyze the code

Samples or source code obtained while analyzing malware.

MalwareMiner is an open source automatic malware sample collection framework.

Malware samples I have found & investigated in the wild. Not pulled from existing sources.

This repository contains original samples and decompiled sources of malware attacking commonly used in Industrial Control Systems (ICS) Triconex Safety Instrumented System (SIS) controllers. For more information scroll to "Learn More".

This is a collection of Random source codes, unorganized. For EDUCATIONAL PURPOSES ONLY 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 Many of them have outdated depedencies.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.

label VirusShare malware samples using various av sources (fpscan and clamav)

In this project, I developed a comprehensive malware analysis framework using YARA, an open-source tool designed for identifying and classifying malware samples based on textual or binary patterns. The project involved several key steps:

Malware analysis toolkit developed in Python via Google Colab. It leverages the VirusTotal API to analyze live malicious samples sourced from MalwareBazaar, providing deep insights into threat behavior and network infrastructure.

MALWAREGUARD is a powerful and user-friendly solution for performing static analysis on malware samples. This open-source tool equips users with the capability to gain in-depth insights into the architecture, content, and potential threats posed by malware files, enhancing their ability to make informed decisions regarding security risks.

This is the *Official* one and only Repository i will do, i will add all of my hacking "bag of tricks" here, mainly for myself as a toolbox i can access from anywhere and run from any device. I will have a live malware sample zoo repository(credit will be given to original sources) and all sorts of techniques ive found myself, plus some tutorials im gonna whip up to make ethical hacking open source and easy & free to learn and understand. Leave notes please!! Notes improve performance.

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Malware samples and sources

repository contains random samples and sources from Malwares samples

Multi-source malware sample aggregator (URLhaus, ThreatFox, Hybrid Analysis)

Classification of malware samples open sourced by Microsoft using tree based classifiers

This is sample of malware in log of network traffic. Disclaimer this sample is not mine but from some open source

This is the source code of a redline malware sample I unpacked and then decompiled using ILSpy

Python scripts for analyzing malware samples, building threat profiles, integrating data from open sources (e.g., AlienVault OTX API), and creating YARA rules for detection.

This tool automates the discovery, download, and cross-verification of malware samples (IOCs) associated with specific ransomware groups. It facilitates incident response and threat intelligence workflows by aggregating samples from multiple sources.

Repository of IOCs collected through static and dynamic analysis of malware samples from known APT groups. Includes hashes, network indicators, and artifacts identified via IDA Pro, sandboxes, and open sources