Pheweb is a full-stack web application for building interactive PheWAS (Phenome-Wide Association Study) websites from GWAS summary statistics. It provides a command-line pipeline to ingest association files, annotate variants with rsIDs and genes, compute Manhattan and QQ plots, and generate a searchable, browsable web interface with LocusZoom region views, phenotype correlations, and top hits tables. The architecture is a Flask monolith with a JavaScript frontend using D3.js, jQuery, and Bootstrap. While the codebase is well-organized for its domain and includes some reusable components (e.g., a simple flat-file indexer and a CFFI matrix builder), it suffers from significant technical drift: outdated dependencies (Flask 1.1, jQuery 1.12, Bootstrap 3.3.7, D3 v5), deprecated Python patterns, and a successor project (PheWeb2) explicitly recommended in the README. The project is functionally complete but in maintenance mode, with limited test coverage and several known bugs documented in the changelog.
SocialFish is a modern dynamic phishing toolkit designed for credential harvesting, session hijacking, and social engineering attacks. It provides a Flask-based web application with an admin dashboard for managing cloned login pages, capturing credentials, intercepting OTP/2FA codes, tracking victim sessions, and injecting post-capture attack payloads (e.g., keyloggers, clipboard stealers, tab jacking). The system supports browser automation via Playwright and Selenium to clone JavaScript-heavy and SPA login flows, and includes tunneling via ngrok/cloudflared for exposing phishing URLs remotely. The architecture is a monolithic Flask app with SQLite storage, WebSocket real-time updates, and a mobile API authenticated by QR tokens. External dependencies include Flask, Flask-SocketIO, Flask-Login, Playwright, Selenium, nmap, qrcode, and PyLaTeX. Despite its feature-rich surface, the codebase exhibits significant quality issues: broken async flows, missing database columns, incomplete routes, version mismatches between requirements files, and security concerns such as default credentials and insecure secret key generation. The project is actively maintained (last commit 2026-05-20) but the code is not production-ready as claimed in documentation.
Lingtrain Studio is a web application for aligning texts in two languages to create parallel corpora and generate bilingual books. It features a Vue.js 2.x frontend with Vuetify and a Flask backend that integrates machine learning models (such as LaBSE and sentence-transformers) for automatic sentence alignment. Users can upload texts, split them into sentences, align them using batch processing, manually correct alignments, and export the results in various formats (HTML, TMX, PDF). The application is Dockerized for ease of deployment and includes tools for model fine-tuning and PDF generation from aligned XML.
This repository powers a multi-domain interactive programming tutorial platform (learnpython.org, learnjavaonline.org, etc.). The core is a Flask web application that serves Markdown-based lessons, provides an in-browser code editor via a vendored CodeMirror 3.x, and executes user code through the Ideone SOAP API. It supports 18+ programming languages with per-domain configuration (editor modes, language IDs, default code). A newer 'vibe coding' feature uses a local browser-based AI model (SmolLM2-360M) to generate code from prompts. The application is deployed via Docker and relies on environment variables for credentials and domain selection. Architecturally, the app is a monolith with a thin Flask layer, static asset serving, and template rendering via Jinja2. Tutorial content is stored as structured Markdown files with consistent headings (Tutorial, Exercise, Tutorial Code, Expected Output, Solution) and is parsed and rendered at runtime. The system is highly internationalized, with 20+ language translations of the core Python tutorials. User progress tracking and authentication are stubbed (501 responses). The codebase includes vendored copies of Python-Markdown, the suds SOAP library, and many CodeMirror modes/addons. The platform has grown organically with significant technical debt: outdated vendored libraries (CodeMirror v3, suds, Markdown), Python 2/3 compatibility hacks, incomplete translations, many empty tutorial pages, and a fragile translation pipeline dependent on a specific OpenAI model. The lack of automated testing beyond basic coverage and the reliance on a third-party code execution API (Ideone) are notable risks. However, the domain configuration pattern in constants.py and the Ideone client wrapper are well-structured and could be reused in similar projects.
This repository is a large collection of standalone Python scripts designed for the Termux environment on Android. It is marketed as an educational cybersecurity toolkit but contains functional phishing pages, credential harvesters, location trackers, camera/mic capture scripts, and a trojan for data exfiltration. The codebase also includes some legitimate utilities such as a password manager, file converter, network scanner, and backup tool. The architecture is highly fragmented: each script is self-contained with its own dependency auto-installation, Flask server, and cloudflared tunnel for public exposure. There is no shared module structure, and the code is heavily duplicated across English and Greek translations. The overall quality is low due to copy-paste patterns, hardcoded secrets, suppressed error logging, lack of testing, and reliance on external services like cloudflared. The repository poses significant legal and ethical risks due to its phishing and surveillance capabilities.