1110 matches found
MAL-2025-6381 Malicious code in web3-rtc (npm)
--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware e9dca49a40515fc43ab5bb3d987aa551a6464961dd1aee2b3e4cadae66831a01 Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...
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...
MAL-2025-6262 Malicious code in blank-pkg (npm)
The package communicates with a domain associated with malicious activity. --- -= Per source details. Do not edit below this line.=- Source: ossf-package-analysis e2f49c661af4e850b4d2aa252c5bdfc2d7409efbbae9396ac2901d0e9fc0f910 The OpenSSF Package Analysis project identified 'blank-pkg' @ 10.0.1...
Regression-Aware Continual Learning for Android Malware Detection
Malware evolves rapidly, forcing machine learning ML-based detectors to adapt continuously. With antivirus vendors processing hundreds of thousands of new samples daily, datasets can grow to billions of examples, making full retraining impractical. Continual learning CL has emerged as a scalable...
MAL-2025-6080 Malicious code in chime-utils (npm)
The package communicates with a domain associated with malicious activity. --- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 4c47d81929483a169d2ee7d4f0f5c08d14518a52a1efa368fc87e2101bd75de5 Any computer that has this package installed or running should be considered...
MAL-2025-6199 Malicious code in sha256-validator-pack (npm)
--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 453f997676ddfb37b97659a39bdc5de8d8c2fc1b070f5feeda72545030850113 Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...
A Crowdsensing Intrusion Detection Dataset for Decentralized Federated Learning Models
This paper introduces a dataset and experimental study for decentralized federated learning DFL applied to IoT crowdsensing malware detection. The dataset comprises behavioral records from benign and eight malware families. A total of 21,582,484 original records were collected from system calls,...
MAL-2025-6487 Malicious code in crto0 (PyPI)
--- -= Per source details. Do not edit below this line.=- Source: kam193 8bdcf6d997fa4676ca2da647171f21e944f9b7d0f34010e6ea8da42364a2d03d Importing the module starts downloading or decrypting, and then executing an executable being a wide recognized malware/Infostealer Redline family --- Category...
ADAPT: a Pseudo-Labeling Approach to Combat Concept Drift in Malware Detection
Whitepaper called ADAPT: A Pseudo-Labeling Approach To Combat Concept Drift In Malware Detection...
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,...
MAL-2025-5654 Malicious code in malicus (PyPI)
--- -= Per source details. Do not edit below this line.=- Source: kam193 d151385056670ff22bfb80dc356c10ff622a77e115f8d81ee5f066220e05fda1 The only goal of the package is to execute a webhook or a suspicious file during installation. Closely related to 2025-07-0x9xnx - created after previous...
MAL-2025-5480 Malicious code in webgl-fingerprinting (npm)
The package communicates with a domain associated with malicious activity. --- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 016147915e679ae2b97b3c040f72eb1171882e3785e1ae3aea0765497138c268 Any computer that has this package installed or running should be considered...
MAL-2025-5221 Malicious code in art19-web-player (npm)
--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 833f7a38c823fdd26727d7a6aec9c75365b96860e4723badca46db54163128da Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...
Efficient Malware Detection with Optimized Learning on High-Dimensional Features
Malware detection using machine learning requires feature extraction from binary files, as models cannot process raw binaries directly. A common approach involves using LIEF for raw feature extraction and the EMBER vectorizer to generate 2381-dimensional feature vectors. However, the high...
MAL-2025-5168 Malicious code in readium-shared-js (npm)
Malicious preinstall script exfiltrates system info hostname, user, pwd, id to a remote server. Likely a malware. --- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 0c907ca12944ad675a60dbfd27a1680a1b2ebf1186512d0106676795741a558a Any computer that has this package...
MAL-2025-4984 Malicious code in dojo.aspect (npm)
--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware d31fd63b97c3cdde47f88984fbd8825829cf78c16098685c438206151cbc31f2 Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...
Empirical Quantification of Spurious Correlations in Malware Detection
End-to-end deep learning exhibits unmatched performance for detecting malware, but such an achievement is reached by exploiting spurious correlations -- features with high relevance at inference time, but known to be useless through domain knowledge. While previous work highlighted that deep...
MAL-2025-4723 Malicious code in 0x000asdqwe (npm)
--- -= Per source details. Do not edit below this line.=- Source: ossf-package-analysis 9ea8c61fc9f49cdc0f6a22b805c76011ff8bd9143b77d223068fdb6f7d0d342e The OpenSSF Package Analysis project identified '0x000asdqwe' @ 5.0.0 npm as malicious. It is considered malicious because: - The package...
Network Threat Detection: Addressing Class Imbalanced Data with Deep Forest
With the rapid expansion of Internet of Things IoT networks, detecting malicious traffic in real-time has become a critical cybersecurity challenge. This research addresses the detection challenges by presenting a comprehensive empirical analysis of machine learning techniques for malware detecti...
Are Trees Really Green? A Detection Approach of IoT Malware Attacks
Nowadays, the Internet of Things IoT is widely employed, and its usage is growing exponentially because it facilitates remote monitoring, predictive maintenance, and data-driven decision making, especially in the healthcare and industrial sectors. However, IoT devices remain vulnerable due to the...