Can Drift-Adaptive Malware Detectors Be Made Robust? Attacks and Defenses under White-Box and Black-Box Threats

Concept drift and adversarial evasion are two major challenges for deploying machine learning-based malware detectors. While both have been studied separately, their combination, the adversarial robustness of drift-adaptive detectors, remains unexplored. We address this problem with AdvDA, a rece...

CVE-2025-30371

Metabase is a business intelligence and embedded analytics tool. Versions prior to v0.52.16.4, v1.52.16.4, v0.53.8, and v1.53.8 are vulnerable to circumvention of local link access protection in GeoJson endpoint. Self hosted Metabase instances that are using the GeoJson feature could be potential...