Kodezi Chronos is a debugging-first language model that achieves state-of-the-art results on SWE-bench Lite (80.33%) and 67% real-world fix accuracy, over six times better than GPT-4. Built with Adaptive Graph-Guided Retrieval and Persistent Debug Memory. Model available Q1 2026 via Kodezi OS.

C++ 20 Control Flow Obfuscation library for Windows Binaries

Reimplementation of GTA:SA 1.0 US

Community Patch to fix and improve original Generals Zero Hour 1.04

A Dynamic Symbolic Execution (DSE) engine for JavaScript. ExpoSE is highly scalable, compatible with recent JavaScript standards, and supports symbolic modelling of strings and regular expressions.

A comprehensive code domain benchmark review of LLM researches.

This repository is the home of Restoration Mod for Payday 2

Static Analysis meets Large Language Models

Resolves severe noise in the widely spread CASIA2.0 dataset ground-truth for Image Manipulation Detection

Efficient patch generation engine for C/C++ programs

Semantic Crash Bucketing

Bug detection and fixing using prompt engineering and fine-tuning with Llama 3 and a custom mutation-based dataset. Includes a user-friendly interface and performance evaluation metrics.

⏳ A Command-Line Sandbox Tester for Different Environments

This Chrome extension fixes the long-standing compatibility issues between Google Translate(including other translation plugins) and React (and other modern JavaScript frameworks) that have been plaguing user and developers since 2018.

A smart local proxy that fixes the “No Internet, Secured” error in Windows by safely emulating msftconnecttest.com and restoring real connectivity detection.

KubeTaK - Kube Attack. Exploit your K8s cluster and workloads running in it. PenTest K8s. Inspired by the concept of kubesploit by CyberArk and StackHawk.

Code Buddy Assist is a tool that enhances your coding experience by integrating Large Language Models (LLMs) to provide comprehensive support, from high-level architecture decisions to detailed bug fixing. It creates project snapshots, enabling AI to understand your code context and offer tailored guidance and assistance.

Automatically fix all software bugs.

Automated LLM-powered pipeline that uses AI agents to analyze, locate, and fix software bugs in Docker containers.

This project uses HTTP requests to connect with APIs or web servers for essential data tasks in data science workflows, including retrieval, submission, and updating. In this project, I utilize Python, HTML, and Flask frameworks to refactor and fix bugs identified for the Scribble app.