New Android Hook Malware Variant Locks Devices With Ransomware

Zimperium's research reveals the Hook Android malware is now a hybrid threat, using ransomware and spyware to steal…...

DRMD: Deep Reinforcement Learning for Malware Detection under Concept Drift

Malware detection in real-world settings must deal with evolving threats, limited labeling budgets, and uncertain predictions. Traditional classifiers, without additional mechanisms, struggle to maintain performance under concept drift in malware domains, as their supervised learning formulation...

MalLoc: toward Fine-Grained Android Malicious Payload Localization Via LLMs

The rapid evolution of Android malware poses significant challenges to the maintenance and security of mobile applications apps. Traditional detection techniques often struggle to keep pace with emerging malware variants that employ advanced tactics such as code obfuscation and dynamic behavior...

Fake Antivirus App Spreads Android Malware to Spy on Russian Users

Doctor Web warns of Android.Backdoor.916.origin, a fake antivirus app that spies on Russian users by stealing data, streaming…...

New Android Malware Wave Hits Banking via NFC Relay Fraud, Call Hijacking, and Root Exploits

Cybersecurity researchers have disclosed a new Android trojan called PhantomCard that abuses near-field communication NFC to conduct relay attacks for facilitating fraudulent transactions in attacks targeting banking customers in Brazil. "PhantomCard relays NFC data from a victim's banking card t...

PlayPraetor Android Trojan Infects 11,000+ Devices via Fake Google Play Pages and Meta Ads

Cybersecurity researchers have discovered a nascent Android remote access trojan RAT called PlayPraetor that has infected more than 11,000 devices, primarily across Portugal, Spain, France, Morocco, Peru, and Hong Kong. "The botnet's rapid growth, which now exceeds 2,000 new infections per week, ...

PlayPraetor Android Trojan Infects 11,000+ Devices via Fake Google Play Pages and Meta Ads

Cybersecurity researchers have discovered a nascent Android remote access trojan RAT called PlayPraetor that has infected more than 11,000 devices, primarily across Portugal, Spain, France, Morocco, Peru, and Hong Kong. "The botnet's rapid growth, which now exceeds 2,000 new infections per week, ...

Empirical Evaluation of Concept Drift in ML-Based Android Malware Detection

Despite outstanding results, machine learning-based Android malware detection models struggle with concept drift, where rapidly evolving malware characteristics degrade model effectiveness. This study examines the impact of concept drift on Android malware detection, evaluating two datasets and...

Understanding Concept Drift with Deprecated Permissions in Android Malware Detection

Permission analysis is a widely used method for Android malware detection. It involves examining the permissions requested by an application to access sensitive data or perform potentially malicious actions. In recent years, various machine learning ML algorithms have been applied to Android...

Fake Telegram Apps Spread via 607 Domains in New Android Malware Attack

Fake Telegram apps are being spread through 607 malicious domains to deliver Android malware, using blog-style pages and phishing tactics to trick users...

MH-FSF: a Unified Framework for Overcoming Benchmarking and Reproducibility Limitations in Feature Selection Evaluation

Feature selection is vital for building effective predictive models, as it reduces dimensionality and emphasizes key features. However, current research often suffers from limited benchmarking and reliance on proprietary datasets. This severely hinders reproducibility and can negatively impact...

Malware Surge Hits Android: Adware, Trojans and Crypto Theft Lead Q2 Threats

Dr.Web reports Android malware surge in Q2 with adware, banking trojans and crypto theft hidden in fake apps, firmware and spyware targeting users...

VOLTRON: Detecting Unknown Malware Using Graph-Based Zero-Shot Learning

The persistent threat of Android malware presents a serious challenge to the security of millions of users globally. While many machine learning-based methods have been developed to detect these threats, their reliance on large labeled datasets limits their effectiveness against emerging,...

New Android Malware Surge Hits Devices via Overlays, Virtualization Fraud, and NFC Theft

Cybersecurity researchers have exposed the inner workings of an Android malware called AntiDot that has compromised over 3,775 devices as part of 273 unique campaigns. "Operated by the financially motivated threat actor LARVA-398, AntiDot is actively sold as a Malware-as-a-Service MaaS on...

New Android Malware Surge Hits Devices via Overlays, Virtualization Fraud, and NFC Theft

Cybersecurity researchers have exposed the inner workings of an Android malware called AntiDot that has compromised over 3,775 devices as part of 273 unique campaigns. "Operated by the financially motivated threat actor LARVA-398, AntiDot is actively sold as a Malware-as-a-Service MaaS on...

MADCAT: Combating Malware Detection under Concept Drift with Test-Time Adaptation

We present MADCAT, a self-supervised approach designed to address the concept drift problem in malware detection. MADCAT employs an encoder-decoder architecture and works by test-time training of the encoder on a small, balanced subset of the test-time data using a self-supervised objective. Duri...

LAMDA: a Longitudinal Android Malware Benchmark for Concept Drift Analysis

Machine learning ML-based malware detection systems often fail to account for the dynamic nature of real-world training and test data distributions. In practice, these distributions evolve due to frequent changes in the Android ecosystem, adversarial development of new malware families, and the...

MalVis: a Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification

As technology advances, Android malware continues to pose significant threats to devices and sensitive data. The open-source nature of the Android OS and the availability of its SDK contribute to this rapid growth. Traditional malware detection techniques, such as signature-based, static, and...

A week in security (April 21 – April 27)

Last week on Malwarebytes Labs: AI is getting "creepy good" at geo-guessing Zoom attack tricks victims into allowing remote access to install malware and steal money Android malware turns phones into malicious tap-to-pay machines 4.7 million customers’ data accidentally leaked to Google by Blue...

FCGHunter: Towards Evaluating Robustness of Graph-Based Android Malware Detection

Graph-based detection methods leveraging Function Call Graphs FCGs have shown promise for Android malware detection AMD due to their semantic insights. However, the deployment of malware detectors in dynamic and hostile environments raises significant concerns about their robustness. While recent...