SmokeDetector is a headless chatbot that monitors Stack Exchange for spam and abusive content in real time. It connects to the Stack Exchange WebSocket to receive new and edited posts, then runs them through a multi-layered detection engine that checks against extensive blacklists (keywords, websites, usernames, phone numbers, IP ranges, nameservers, ASNs) and applies heuristic rules including DNS lookups, homoglyph detection, and similarity analysis. Detected spam is reported to designated chat rooms on Stack Exchange Chat, where moderators can provide feedback that feeds back into the system via the Metasmoke statistics service. The architecture is event-driven: the main loop in `ws.py` listens for WebSocket events, enqueues posts for scanning via `bodyfetcher.py`, and dispatches results to `spamhandling.py` for chat reporting. A command system in `chatcommands.py` allows operators to manage blacklists, inspect posts, and control the bot through chat messages. Persistent state is stored in pickle files, and the bot integrates with GitHub for automated blacklist pull requests. The detection logic in `findspam.py` is rule-based with over 100 rules registered via a decorator pattern, each with configurable filters for site, reputation, and score. Key reusable components include a generic TTL cache (`metasmoke_cache.py`), an extensible blacklist parser hierarchy (`blacklists.py`), a phone number matching module with homoglyph support (`phone_numbers.py`), and a command registration decorator. The codebase is well-tested with extensive parametrized tests and has CI/CD pipelines. While the core detection file is large and tightly coupled, many supporting modules are cleanly separated and could be extracted for other projects.
Prosopo is a privacy-focused, self-hosted CAPTCHA alternative that provides multiple challenge types—image selection, puzzle (image jigsaw), proof-of-work, and frictionless (behavioral bot detection). The system comprises an Express-based provider API (with MongoDB and Redis for persistence and caching), a CLI for administrative tasks, client-side embeddable widgets (vanilla JS bundle, React/Angular/Vue/Svelte wrappers), and a suite of supporting libraries for cryptography, locale, datasets, and native Rust modules (JA4 TLS fingerprinting, Merkle tree acceleration, puzzle rendering). Bot detection is multi-layered: client-side behavioral data (mouse/keyboard/touch events, SIMD readings) is collected and server-side scored, combined with JA4 TLS fingerprint analysis, IP reputation (ipapi.is + MaxMind), DNS asymmetry detection, spam email heuristics, and custom decision machines per site key. The architecture is a monorepo with ~70 workspaces, leveraging Vite for bundling, Vitest for unit/integration tests, and Cypress for E2E visual regression testing. The provider enforces access policies (allow/block/restrict) via a Redis-backed rules engine and maintains usage counters for rate limiting. Asset sealing (AES-256-GCM) protects image CDN URLs, and puzzle difficulty is sampled with a CSPRNG-stratified ladder to frustrate solver calibration.
Spam Call Blocker is an Android application written in Kotlin that blocks unwanted incoming calls using a combination of local blocklists, pattern matching, and real-time checks against multiple online phone reputation services (UnknownPhone, Tellows, Truecaller, and regional directories). It registers a call screening service to intercept calls, evaluates them against user-defined rules and external APIs, and can block, mute, or answer-and-hangup spam calls. The app provides a full settings UI for managing blocked/whitelisted numbers, pattern-based blocking, API toggles, and export/import of configuration. It also includes a donation screen and automatic update checking via GitHub releases. The codebase is well-structured with clear separation of concerns, uses Kotlin coroutines for concurrent API checks, and supports multiple languages.
This repository is primarily a large collection of GPT prompt templates (markdown files) designed for use with AI chat platforms like FlowGPT or gptcall.net. Each prompt file defines a specific role or task for the AI, such as a resume editor, coding tutor, fitness planner, or creative writing assistant. The repository also includes an Android application (OpenClaw and Codex) referenced in the README, along with Node.js scripts (update.mjs, db.mjs) for managing the prompt data. The prompts are structured with placeholders for user input and often request specific output formats, enabling users to import them into chat interfaces to obtain specialized AI behavior without crafting prompts from scratch. While the prompt library is extensive, it contains significant duplication, minimal-effort entries, and some policy-risking content (e.g., jailbreaks, NSFW role-play), which affects overall quality and reuse potential.