Open Source Unix Shell Software Development Software for Linux

certificate-transparency-go is a Go codebase for building and interacting with Certificate Transparency (CT) systems, from low-level parsing to full log operation. It includes forked ASN.1 and X.509 packages tailored to accept and analyze real-world certificates, including pre-certificates that stricter libraries would reject, supporting CT’s role as an ecosystem observatory. A TLS parsing library, CT data types, and multiple client libraries enable access to CT logs over HTTP and DNS, along with scanners for traversing entire logs. The repository also provides command-line tools for verifying signed certificate timestamps, inspecting certificates and CRLs, and querying logs. For operators, a “CT personality” integrates with Trillian so you can run a CT log backed by a verifiable transparency log. The project is structured for contributors, with generators, mocks, linting, and presubmit tooling to keep changes consistent and reliable.

gVisor is an application kernel developed by Google that provides a strong layer of isolation between applications and the host operating system. Written in Go, it implements a Linux-compatible system call interface that runs entirely in user space, creating a secure sandboxed environment for containers. Unlike traditional virtual machines or lightweight syscall filters, gVisor follows a third approach that offers many of the security benefits of virtualization while maintaining the speed, resource efficiency, and flexibility of containers. Its key runtime, runsc, integrates seamlessly with container ecosystems such as Docker and Kubernetes, making it easy to deploy sandboxed workloads using familiar tools. By intercepting and safely handling syscalls from applications, gVisor reduces the attack surface of the host kernel, mitigating risks associated with running untrusted or potentially malicious code in containerized environments.

MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack

Open Source AI-ready PaaS and framework for building your own cloud on bare metal and running managed Kubernetes, virtual machines, Databases-as-a-Service or for creating your own AWS/GCP/Azure competitor for ISP/MSP/hosting providers. CNCF Project - Control your data - Cut dependence from the tech giants - Enable digital sovereignty - Use modern tools and APIs with any server - Fully utilize GPU resources for AI Who is it for? Banks and fintechs, AI-driven companies, service providers and data centers, governances, regulated and privacy-conscious organizations, integrators and independent IT consultants