IRIS
IRIS is a neurosymbolic framework that combines LLMs with static analysis for security vulnerability detection. IRIS uses LLMs to generate source and sink specifications and to filter false positive vulnerable paths.
Overview
At a high level, IRIS takes a project and a CWE (vulnerability class, such as path traversal vulnerability or CWE-22) as input, statically analyzes the project, and outputs a set of potential vulnerabilities (of type CWE) in the project.
Key Features
- Combines LLMs with static analysis for enhanced vulnerability detection
- Supports multiple vulnerability classes (CWEs)
- Works with various LLM models
- Provides detailed analysis and results
- Easy to set up with Docker or native installation
Getting Started
To get started with IRIS:
- Check out the Environment Setup guide
- Follow our Quickstart tutorial
- Learn about Supported CWEs and Models
- If you are interested in contributing, read our Guidelines