GEF (GDB Enhanced Features) is a production-grade GDB plugin for exploit development, reverse engineering, and binary analysis. It is a single Python script (gef.py) that loads into GDB (>=10.0) and provides over 90 commands covering memory inspection, heap analysis, security mitigation checks (checksec), pattern generation, format string detection, and remote debugging. The architecture is monolithic but well-organized, with a clear separation of concerns via class hierarchies for architectures, memory regions, heap structures, and command registration. The test suite is extensive, using a Docker-based CI matrix that runs on multiple architectures (x86, ARM, AARCH64, etc.) and validates behaviour through RPyC-driven remote GDB sessions. While primarily an application, it also serves as a research tool for heap allocator internals and glibc version-specific behaviour, blending practical utility with deep system understanding.
This repository is the CTF Wiki, a comprehensive, community-driven knowledge base for Capture The Flag (CTF) security competitions. It is a static documentation site built with MkDocs and the Material theme, supporting multiple languages (Simplified Chinese, Traditional Chinese, English). The content covers a wide range of security topics including binary exploitation (pwn), cryptography, reverse engineering, web security, blockchain, Android security, and miscellaneous challenges. The repository itself is not a software application but a collection of Markdown files, images, and configuration files that are built into a static website. It includes CI/CD pipelines for deployment to Netlify and GitHub Pages, a Dockerfile for production serving, and a build script (scripts/docs.py) for multi-language management. While the documentation is extensive and well-organized, the codebase is primarily configuration and build tooling, with limited reusable software components. The project shows signs of maintenance with recent commits, but many pages are incomplete or outdated, and some dependencies (Python 3.8, pydantic 1.5.1) are lagging behind current versions.