Learn how to protect Model Context Protocol (MCP) from quantum-enabled adversarial attacks using automated threat detection and post-quantum security.

Abstract: Unsupervised anomaly detection (UAD) methods typically detect anomalies by learning and reconstructing the normative distribution. However, since anomalies constantly invade and affect their ...

The GlassWorm supply-chain campaign has returned with a new, coordinated attack that targeted hundreds of packages, ...

Overview: Automated Python EDA scripts generate visual reports and dataset summaries quicklyLibraries such as YData Profiling ...

Python libraries for cybersecurity help automate threat detection, network monitoring, and vulnerability analysis. Tools like Scapy, Nmap, and Requests enable penetration testing and network security ...

Horror games are one of the best genres on Roblox, but the amount of jumpscares Scary Shawarma Kiosk the Anomaly brings is amazing. The game lets you run a shawarma shop while finding anomalies and ...

On Saturday, tech entrepreneur Siqi Chen released an open source plugin for Anthropic’s Claude Code AI assistant that instructs the AI model to stop writing like an AI model. Called “Humanizer,” the ...

Abstract Recent studies highlighted a practical setting of unsupervised anomaly detection (UAD) that builds a unified model for multi-class images. Despite various advancements addressing this ...

Strengthen your agency’s edge by using AI code detection to spot risky AI-generated sections early and protect quality, security, and client trust. Build a repeatable review process by scanning repos, ...

Abstract: In the domain of image anomaly detection, significant progress has been made in unsupervised and self-supervised methods with datasets containing only normal samples. Although these methods ...

PythoC lets you use Python as a C code generator, but with more features and flexibility than Cython provides. Here’s a first look at the new C code generator for Python. Python and C share more than ...