OpenFang is an open-source Agent Operating System built entirely in Rust, designed for deploying genuinely autonomous AI agents that operate independently without constant user prompts. Unlike traditional chatbot frameworks that wait for user input, OpenFang agents run on schedules and complete complex tasks around the clock. The project compiles to a single 32MB binary with cold start times under 200ms and idle memory usage of just 40MB, making it dramatically more resource-efficient than Python-based alternatives. OpenFang ships with 7 pre-built agent modules called Hands, including Researcher, Lead Generator, Browser, Twitter Manager, Content Clipper, Collector, and Predictor. Each Hand is a self-contained autonomous unit that can be scheduled to perform complex multi-step tasks independently. The system provides 40 channel adapters for integration with platforms including Telegram, Discord, Slack, WhatsApp, Signal, and Microsoft Teams. It supports 27 LLM providers with access to 123+ models through an OpenAI-compatible API with 140+ endpoints. Security is a core design principle with 16 discrete security layers including WASM dual-metered sandbox execution, Merkle hash-chain audit trails, taint tracking, Ed25519 signed manifests, SSRF protection, secret zeroization, and prompt injection scanning. The codebase consists of 137,728 lines of Rust across 14 crates with 1,767+ passing tests and zero Clippy warnings. OpenFang supports both Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication standards. Released as v0.1.0 in February 2026, the project is dual-licensed under MIT and Apache-2.0.