AuditCodex – Your AI-Powered Code and Security Auditor (github.com)

AuditCodex is an open-source, CLI-first AI developer assistant that automates code review, refactoring, testing, documentation, and security scanning across many languages. Designed as a modular, hexagonal-architecture tool, it provides AI-driven explanations of commits and functions, actionable refactor suggestions, generated test templates (with automatic language/framework selection like Dart→Flutter, TS/JS→Jest, Python→pytest), vulnerability scanning, and auto-generated docs and commit messages. Output is colorized and structured (console, markdown, JSON) with severity indicators and can post comments to GitHub PRs or be integrated into CI pipelines. For the AI/ML community this matters because AuditCodex combines multi-LLM support (OpenAI, local Ollama, Google Gemini) with a privacy-first stance, enabling offline or on-prem inference for sensitive code. Its language- and framework-aware analysis plus plugin-ready adapter model make it easy to extend for custom policies, tooling, or datasets, and its file-pattern and staged/unstaged review modes suit granular CI workflows. Technical implications include reproducible, machine-readable feedback for automated triage, faster developer feedback loops, and safer adoption in regulated environments where local LLMs or policy enforcement are required.