Hackers use credentials stolen in the GlassWorm campaign to access GitHub accounts and inject malware into Python repositories.

Abstract: In this paper, we propose an anomaly detection model based on Extended Isolation Forest and Denoising Autoencoder, which achieves unsupervised anomaly detection with good generalization ...

Abstract: Industrial few-shot anomaly detection (FSAD) requires identifying various abnormal states by leveraging as few normal samples as possible (abnormal samples are unavailable during training).

This tool captures network packets, analyzes traffic patterns, and uses machine learning to detect anomalous behavior. It integrates with network security scanners to provide comprehensive threat ...