$ Featured Articles
>>Training-Time Attacks: Dataset Typosquatting as a Critical Security Risk in Machine Learning
Dataset typo squatting is a training time attack in which adversaries publish malicious datasets or pretrained models under names that closely resemble trusted resources. When these artifacts are unknowingly integrated into machine learning pipelines, poisoned data becomes embedded directly into model parameters through gradient-based optimization. Because the compromise occurs during training rather than at runtime, traditional security controls offer little protection. As ML ecosystems and automated workflows expand, verifying the integrity and provenance of training artifacts becomes a critical component of AI supply chain security.
>>Agentic AI: The Emerging Cognitive Threat Layer in India’s Digital Framework
Discover how India’s fast-growing AI ecosystem is quietly exposing hidden security and trust gaps. Dive into the unseen world of agentic AI—where machines think, act, and sometimes go beyond human control.
>>The Dark Reality of Modded Android Applications: A Silent Threat in Everyday Life
That “Pro” APK you installed didn’t just remove ads — it removed your security. This deep-dive explains how modded Android apps operate at the OS level, why antivirus scans often miss them, and how real users end up paying the price.
