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Trivy: Comprehensive Vulnerability, Misconfiguration, Secret, and SBOM Scanner for Containers, Kubernetes, Code Repositories, and Cloud Environments

Trivy, developed by aquasecurity, is a powerful and versatile security scanner designed to identify vulnerabilities, misconfigurations, secrets, and Software Bill of Materials (SBOMs) across various components of the modern software development lifecycle. It supports scanning containers, Kubernetes clusters, code repositories, and cloud environments, providing a unified solution for enhancing security posture. The tool aims to help developers and security teams proactively detect and address potential security risks.

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Trivy, a project by aquasecurity, offers a robust solution for identifying critical security issues within diverse technological landscapes. It is engineered to detect vulnerabilities, misconfigurations, secrets, and generate Software Bill of Materials (SBOMs). The scanning capabilities extend across several key areas, including container images, Kubernetes deployments, code repositories, and cloud infrastructure. This broad coverage makes Trivy a valuable tool for maintaining security throughout the development and deployment pipeline. By providing a comprehensive overview of potential risks, Trivy assists organizations in strengthening their security posture and mitigating threats effectively.

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FreeMoCap: Democratizing Motion Capture for Everyone – A New Open-Source Project Trending on GitHub

FreeMoCap, an innovative project, is making waves on GitHub Trending, aiming to democratize motion capture technology. The project's core mission is to enable "everyone to freely motion capture," suggesting an accessible and user-friendly approach to a technology traditionally requiring specialized equipment and expertise. Launched by 'freemocap' and published on February 22, 2026, this initiative promises to open up new possibilities for creators, developers, and enthusiasts by making motion capture widely available.

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Google Research Unveils TimesFM: A Pre-trained Foundation Model for Advanced Time Series Forecasting

Google Research has introduced TimesFM (Time Series Foundation Model), a new pre-trained foundation model specifically designed for time series forecasting. Developed by Google's research division, TimesFM aims to enhance the accuracy and efficiency of predictions across various time-dependent data sets.

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Hugging Face Introduces 'Skills' for AI/ML Task Definition and Interoperability with Major Coding Agents

Hugging Face has unveiled 'Skills,' a new framework designed to define tasks within the AI/ML domain, encompassing activities like dataset creation, model training, and evaluation. These skills are built for seamless interoperability with leading coding agent tools, including OpenAI Codex, Anthropic's Claude Code, and Google De, aiming to streamline AI/ML workflows.