malware-detection
There are 493 repositories under malware-detection topic.
vxunderground/MalwareSourceCode
Collection of malware source code for a variety of platforms in an array of different programming languages.
wazuh/wazuh
Wazuh - The Open Source Security Platform. Unified XDR and SIEM protection for endpoints and cloud workloads.
InQuest/awesome-yara
A curated list of awesome YARA rules, tools, and people.
APKLab/APKLab
Android Reverse-Engineering Workbench for VS Code
rednaga/APKiD
Android Application Identifier for Packers, Protectors, Obfuscators and Oddities - PEiD for Android
hasherezade/hollows_hunter
Scans all running processes. Recognizes and dumps a variety of potentially malicious implants (replaced/implanted PEs, shellcodes, hooks, in-memory patches).
last-byte/PersistenceSniper
Powershell module that can be used by Blue Teams, Incident Responders and System Administrators to hunt persistences implanted in Windows machines. Official Twitter/X account @PersistSniper. Made with ❤️ by @last0x00 and @dottor_morte
airbnb/binaryalert
BinaryAlert: Serverless, Real-time & Retroactive Malware Detection.
eliasgranderubio/dagda
a tool to perform static analysis of known vulnerabilities, trojans, viruses, malware & other malicious threats in docker images/containers and to monitor the docker daemon and running docker containers for detecting anomalous activities
reversinglabs/reversinglabs-yara-rules
ReversingLabs YARA Rules
JPCERTCC/EmoCheck
Emotet detection tool for Windows OS
horsicq/XAPKDetector
APK/DEX detector for Windows, Linux and MacOS.
horsicq/Nauz-File-Detector
Linker/Compiler/Tool detector for Windows, Linux and MacOS.
0xDanielLopez/TweetFeed
TweetFeed collects Indicators of Compromise (IOCs) shared by the infosec community at Twitter. Here you will find malicious URLs, domains, IPs, and SHA256/MD5 hashes.
chenerlich/FCL
FCL (Fileless Command Lines) - Known command lines of fileless malicious executions
Virus-Samples/Malware-Sample-Sources
Malware Sample Sources
PUNCH-Cyber/stoq
An open source framework for enterprise level automated analysis.
mxmssh/drltrace
Drltrace is a library calls tracer for Windows and Linux applications.
XiaoxiaoMa-MQ/Awesome-Deep-Graph-Anomaly-Detection
Awesome graph anomaly detection techniques built based on deep learning frameworks. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in anomaly detection, graph representation learning, and graph anomaly detection to join this project as contributors and boost further research in this area.
bartblaze/Yara-rules
Collection of private Yara rules.
MalwareSamples/Malware-Feed
Bringing you the best of the worst files on the Internet.
OpticFusion1/MCAntiMalware
Anti-Malware for minecraft
ANSSI-FR/SecuML
Machine Learning for Computer Security
secrary/DrSemu
DrSemu - Sandboxed Malware Detection and Classification Tool Based on Dynamic Behavior
sapphirex00/Threat-Hunting
Personal compilation of APT malware from whitepaper releases, documents and own research
projectmatris/antimalwareapp
Anti-malware for Android using machine learning
pandora-analysis/pandora
Pandora is an analysis framework to discover if a file is suspicious and conveniently show the results
CalebFenton/apkfile
Android app analysis and feature extraction library
stamparm/blackbook
Blackbook of malware domains
prodaft/malware-ioc
This repository contains indicators of compromise (IOCs) of our various investigations.
CybercentreCanada/assemblyline
AssemblyLine 4: File triage and malware analysis
alik604/cyber-security
Machine Learning for Network Intrusion Detection & Misc Cyber Security Utilities
maoqyhz/DroidCC
🤖Android malware detection using deep learning, contains android malware samples, papers, tools etc.🐛
JPCERTCC/YAMA
Yet Another Memory Analyzer for malware detection
We5ter/Flerken
A Solution For Cross-Platform Obfuscated Commands Detection presented on CIS2019 China. 动静态Bash/CMD/PowerShell命令混淆检测框架 - CIS 2019大会
AFAgarap/malware-classification
Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification