Search Results for "network config"

edgetunnel is a modified version of a serverless tunnelling solution designed to run on platforms like Cloudflare Workers and Pages, enabling protocols such as VLESS and Trojan to be exposed through edge-functions rather than traditional servers. The project’s fork by cmliu emphasizes conversion of protocol configuration (especially VLESS) into subscription links, so that users can deploy and then generate “Clash” or “Sing-box” compatible subscription content easily. It provides a...

AndroidLibXrayLite is a lightweight Android library that bundles the Xray networking core as an embeddable component for apps. Its purpose is to provide a minimal, size-optimized build of the native core with a clear Java/Kotlin interface to start, stop, and configure network tunnels. By exposing the core as an AAR with per-ABI artifacts, it keeps application footprints small while supporting common CPU architectures. The library abstracts process management and log streaming so host apps...

Russh provides a Rust library for implementing SSH clients and servers with a modern, async-friendly design. It exposes building blocks for authentication, channel management, port forwarding, and key handling, allowing you to embed SSH functionality directly into Rust applications. The API is designed to be explicit and composable, making it possible to implement custom behaviors like reverse tunnels, interactive shells, and service multiplexing. Because performance and safety are central,...

Surge-rules is a project devoted to maintaining and distributing rule sets compatible with the Surge proxy application (for macOS/iOS), intended for domain- or routing-based traffic management. Instead of manually building or maintaining Surge configuration files, users can rely on this repo to obtain up-to-date “RULE-SET” or “DOMAIN-SET” configurations that reflect community-curated lists of domains/IPs for direct access, proxying, blocking, or custom routing. Because network and domain...

compare_gan is a research codebase that standardizes how Generative Adversarial Networks are trained and evaluated so results are comparable across papers and datasets. It offers reference implementations for popular GAN architectures and losses, plus a consistent training harness to remove confounding differences in optimization or preprocessing. The library’s evaluation suite includes widely used metrics and diagnostics that quantify sample quality, diversity, and mode coverage. With...