EUVD-2022-36967

Malicious code in bioql PyPI...

EUVD-2022-27314

Malicious code in bioql PyPI...

EUVD-2025-29357

Malicious code in bioql PyPI...

EUVD-2024-21408

Malicious code in bioql PyPI...

EUVD-2025-10061

Malicious code in bioql PyPI...

EUVD-2025-15535

Malicious code in bioql PyPI...

EUVD-2025-14213

Malicious code in bioql PyPI...

AutoML in Cybersecurity: An Empirical Study

Automated machine learning AutoML has emerged as a promising paradigm for automating machine learning ML pipeline design, broadening AI adoption. Yet its reliability in complex domains such as cybersecurity remains underexplored. This paper systematically evaluates eight open-source AutoML...

Heritage Foundation Uses Bogus Stat to Push a Trans Terrorism Classification

By inflating numbers and narrowing definitions, Heritage promotes a false link between transgender identity and violence in its push for the FBI to create a new terrorism category...

Vision Transformers: the Threat of Realistic Adversarial Patches

The increasing reliance on machine learning systems has made their security a critical concern. Evasion attacks enable adversaries to manipulate the decision-making processes of AI systems, potentially causing security breaches or misclassification of targets. Vision Transformers ViTs have gained...

A Comparative Analysis of Ensemble-Based Machine Learning Approaches with Explainable AI for Multi-Class Intrusion Detection in Drone Networks

The growing integration of drones into civilian, commercial, and defense sectors introduces significant cybersecurity concerns, particularly with the increased risk of network-based intrusions targeting drone communication protocols. Detecting and classifying these intrusions is inherently...

UBUNTU-CVE-2025-59437

The ip aka node-ip package through 2.0.1 in NPM might allow SSRF because the IP address value 0 is improperly categorized as globally routable via isPublic. NOTE: this issue exists because of an incomplete fix for CVE-2024-29415. NOTE: in current versions of several applications, connection...

A Comparison of Selected Image Transformation Techniques for Malware Classification

Recently, a considerable amount of malware research has focused on the use of powerful image-based machine learning techniques, which generally yield impressive results. However, before image-based techniques can be applied to malware, the samples must be converted to images, and there is no...

Malicious code in image_classification (npm)

--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 33e5c05f2c70291fde5a4ace56b3aa015c8c407695c02395a9a4336285e964a3 Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...

MAL-2025-47017 Malicious code in image_classification (npm)

--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware 33e5c05f2c70291fde5a4ace56b3aa015c8c407695c02395a9a4336285e964a3 Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...

Malicious Package

Overview imageclassification is a malicious package. This package contains malicious code, and its content was removed from the official package manager. While this package might be attempting to impersonate a valid organization, there is no connection between that organization and this package...

Signal-Based Malware Classification Using 1D CNNs

Malware classification is a contemporary and ongoing challenge in cyber-security: modern obfuscation techniques are able to evade traditional static analysis, while dynamic analysis is too resource intensive to be deployed at a large scale. One prominent line of research addresses these limitatio...

Contrastive Self-Supervised Network Intrusion Detection Using Augmented Negative Pairs

Network intrusion detection remains a critical challenge in cybersecurity. While supervised machine learning models achieve state-of-the-art performance, their reliance on large labelled datasets makes them impractical for many real-world applications. Anomaly detection methods, which train...

Human-Written Vs. AI-Generated Code: a Large-Scale Study of Defects, Vulnerabilities, and Complexity

As AI code assistants become increasingly integrated into software development workflows, understanding how their code compares to human-written programs is critical for ensuring reliability, maintainability, and security. In this paper, we present a large-scale comparison of code authored by hum...

Non-Omniscient Backdoor Injection with a Single Poison Sample: Proving the One-Poison Hypothesis for Linear Regression and Linear Classification

Backdoor injection attacks are a threat to machine learning models that are trained on large data collected from untrusted sources; these attacks enable attackers to inject malicious behavior into the model that can be triggered by specially crafted inputs. Prior work has established bounds on th...