fanqiang

Fscan is an open-source intranet security scanning tool developed as a Go project. It discovers hosts with ICMP probing, scans TCP ports, identifies services and web technologies, performs credential and hash-based authentication tests, detects selected vulnerabilities and unauthorized access, and provides exploitation and local information-gathering modules. Its inputs include IP addresses, CIDR ranges, domains, URLs, and batch files; results can be written as TXT, JSON, or CSV. The tool is organized around service, web, and local plugins. It supports common service fingerprinting, Xray- and Afrog-format web POCs, DNSLog-based detection, HTTP and SOCKS5 proxies, interface selection, rate and timeout controls, independent scan concurrency settings, and configurable exclusions. Its local modules include system and domain information collection, credential acquisition, persistence mechanisms, shells, security-software detection, and log-cleaning utilities. The repository also provides a Go SDK under pkg/fscan for embedding scan tasks in agents or security platforms, with pause/resume control and progress callbacks, plus an optional web management interface enabled through a build tag.

Shadowrocket-ADBlock-Rules-Forever is a maintained collection of routing and ad-blocking rule files for the iOS Shadowrocket app. It provides configurations that determine which domains use a proxy or direct connection, including blacklist, whitelist, domestic/international split, return-to-China, global proxy, global direct, and ad-block-only variants. The project generates its rules automatically with Python from sources including GFWList, Greatfire Analyzer blocked-domain data, EasyList, EasyList China, Peter Lowe's ad and privacy-tracking lists, 乘风 rules, and project-specific rules. It also provides separate files for iOS web, app, and video advertising, plus optional lazy configurations with proxy groups. The repository states that published rules are rebuilt daily at 08:00 Beijing time and can be downloaded or automatically updated through Shadowrocket and iOS Shortcuts. The rules are plain-text configuration files and do not themselves provide proxy access.

OpenFlux is a network-stack research tool that creates a TCP tunnel with pluggable transports. A client exposes a SOCKS5 proxy, sends TCP packets through a selected transport to an exit node, and the exit node decapsulates and forwards them to the destination. The repository provides transports using Yandex Docs cursor messages and MAX Messenger WebRTC DataChannel; custom transports can implement its Transport interface. It includes desktop, Android, and iOS build paths and is distributed under the GNU General Public License v3.0 or later. The README describes the MAX transport as experimental and warns that using external infrastructure or accounts may lead to account restrictions.

FuXi is a self-contained terminal AI coding agent developed by FUXI. Built in Go and distributed as a static binary, it uses a Think → Act → Verify loop to read and edit code, run shell commands, drive tools, connect to MCP servers, and route requests across multiple LLM providers with automatic failover and cost-aware settings. Its built-in capabilities include file operations, shell execution, code search, web fetching, LSP diagnostics, Jupyter, browser use, background tasks, and parallel sub-agents. Shell commands pass an AST-based safety classifier, while permissions and audit logs govern autonomous actions. Sessions persist to disk, with checkpoints for resuming, rolling back, or forking; the TUI also supports memory consolidation and automatic context compaction. FuXi supports provider API keys or FuXi OAuth, configurable OpenAI-compatible endpoints, MCP clients, hooks, skills, plugins, and slash commands. The repository contains documentation, installers, release information, and issue-tracking materials; it states that the product source is proprietary and not published.

QRFerry transfers files between two devices as a live animated QR stream. The sender and receiver run in the browser, and the file is not uploaded to an application server. The protocol optionally compresses the file with Brotli or gzip, then divides the payload into QR frames containing binary headers, RaptorQ source or repair symbols, and CRC-32 checksums. Fountain coding lets the receiver reconstruct the file from enough unique symbols while tolerating blurred, missing, out-of-order, or mid-stream frames. The receiver verifies frame, compressed-payload, RaptorQ-object, and original-file checksums before saving the file. QR rendering, scanning, and RaptorQ encoding and decoding use WebAssembly implementations of fast_qr, ZXing-C++, and an RFC 6330 RaptorQ implementation.