maldrolyzer

maldrolyzer Simple framework to extract "actionable" data from Android malware C&Cs, phone numbers etc. Installation You have to install the following packets before you start using this project: Androguard git clone https://github.com/androguard/androguard; cd androguard; sudo python setup.py...

MalConfig

MalConfig This is part of a module for the framework that i'm constantly developing. Robots images are provided by robohash.org Flag icons are provided by famfamfam The decoders were mostly making use of Androguard to extract the C2 or malware authors' credentials One of the decoder is making use...

avpass

AVPASS AVPASS is a tool for leaking the detection model of Android malware detection systems i.e., antivirus software, and bypassing their detection logics by using the leaked information coupled with APK obfuscation techniques. AVPASS is not limited to detection features used by detection system...

silverboxcc

Reverse engineered android malware called Red Alert V2.0. At the time of analysis, there were no longer any C2 servers running and so we were unable to observe any traffic between the malware and the C2 server. So we figured out the C2 protocol and wrote this control panel. Bot's traffic from the...

LiveHiddenCamera

Live Hidden Camera Live Hidden Camera LHC is a library which record live video and audio from Android device without displaying a preview. Motivation I'm working on a research based Android Malware and decided to create a multi function RAT Remote Administration Tool. I was working on Live Stream...

MalEval

MalEval Article: Is “Knowing It’s Malicious” Enough? Evaluating LLMs for Fine-Grained Malware Behavior Auditing Article DOI: 10.1145/3832187 MalEval is a framework for evaluating Android malware behavior reports generated by large language models. The code in this repository implements two...

cuckoo-droid

CuckooDroid - Automated Android Malware Analysis. Contributed By Check Point Software Technologies LTD. CuckooDroid is an extension of Cuckoo Sandbox the Open Source software for automating analysis of suspicious files, CuckooDroid brigs to cuckoo the capabilities of execution and analysis of...

engine

Moteur Droidefense Framework avancé d'analyse de malwares Android Dernière version Télécharger Qu'est-ce que Droidefense Droidefense initialement nommé atom : a nalysis t hrough o bservation m achine est le nom de code d'un outil d'analyse/rétro-ingénierie d'applications/malwares Android. Il a ét...

DroidDetective

🕵️ A machine learning malware analysis framework for Android apps. ☢️ DroidDetective is a Python tool for analysing Android applications APKs for potential malware related behaviour and configurations. When provided with a path to an application APK file Droid Detective will make a prediction using...

MADLIRA

MADLIRA Malware detection using learning and information retrieval for Android Overview MADLIRA is a tool for Android malware detection. It consists in two components: TFIDF component and SVM learning component. In gerneral, it takes an input a set of malwares and benwares and then extracts the...

amtracker

amtracker Android Malware Tracker This was originally part of a module for the framework that i'm constantly developing. The decoders were mostly making use of Androguard to extract the C2 or malware authors' credentials One of the decoder is making use of LIEF to extract the C2 from the android...

avpass

AVPASS AVPASS est un outil permettant de divulguer le modèle de détection des systèmes de détection de malwares Android c'est-à-dire les antivirus et de contourner leur logique de détection en utilisant les informations divulguées couplées à des techniques d'obfuscation d'APK. AVPASS ne se limite...

MalwareSourceCode

managed by vx-underground | follow us on Twitter | download malware samples at the VXUG/samples page 免責事項： 適用される法律で許容される最大限の範囲において、vx-underground およびコンテンツを vx-underground に提出した関連会社は、間接的、偶発的、特別、結果的、懲罰的損害賠償、または直接間接を問わず発生した利益や収入の損失、データ、使用、のれん、その他の無形資産の損失について、以下の事由に起因する場合、一切の責任を負いません。i...

BIDO

BIDO Данный код относится к работе "BIDO: A Unified Approach to Address Obfuscation and Concept Drift Challenges in Image-based Malware Detection". Авторы Авторы: Junhui Li1, Chengbin Feng2, Zhiwei Yang1, Qi Mo1 и Wei Wang1. Учреждения Учреждение1: Школа программного обеспечения, Юньнаньский...

Manic Android Malware Exfiltrates Data From Offline Phones via Nearby Infected Devices

A new Android threat codenamed Manic has been observed actively targeting Ukrainian banks, government and identity services, and messaging applications, as well as Russian and European financial institutions, global fintech and cryptocurrency services, and military-focused communications. "Manic...

WindRelay Android Malware Turns Victims' Phones Into NFC Relays for Payment Fraud

A previously unseen Android near field communication NFC relay malware family dubbed WindRelay is being deployed in conjunction with a known remote access trojan RAT called SpyNote as part of a contactless payment fraud scheme. The purpose-built malware, according to Group-IB, is designed to...

ShielDroid: A Hybrid Approach Integrating Machine and Deep Learning for Android Malware Detection

The rapid advancement of modern technology has led to a significant increase in the use of smart devices, such as smartphones and tablets, resulting in the widespread adoption of mobile applications. Although applications are required to undergo malware screening before being published on officia...

DroidBreaker: Practical and Functional Problem-Space Attacks on Machine-Learning Android Malware Detectors

Adversarial APKs are Android applications modified in the problem space to evade machine-learning malware detectors. In this work, we first show that, despite claims, existing problem-space attacks remain largely impractical. Most techniques leverage software transplantation to inject entire beni...

The Sound of Malware: A Memory Forensics Approach for Android Malware Analysis Via Audio Signals

Android malware analysis is currently facing increasing challenges in achieving robust classification and detecting stealth attacks. Modern threats employ advanced evasion strategies such as code obfuscation, dynamic loading, packing, and even steganographic manipulation of traditional static and...

Don't Trust Us: A Privacy-By-Design Android Malware Detection Pipeline

Android malware detection increasingly relies on collecting and processing sensitive user data, including device identifiers, network artifacts, and runtime traces, while privacy is too often treated as a secondary concern. Existing privacy-aware approaches typically enforce privacy after data...