
OGhidra — Updated!
OGhidra bridges Large Language Models (LLMs) via Ollama with the Ghidra reverse engineering platform, enabling AI-driven binary analysis through natural language. Interact with Ghidra using conversational queries and automate complex reverse engineering workflows.
OGhidra 3 - AI-Powered Reverse Engineering with Ghidra
For the version using a Claude-inspired Orchestrator, see https://github.com/llnl/OGhidra/tree/orchestrator
OGhidra bridges Large Language Models with Ghidra's reverse engineering platform, enabling AI-driven binary analysis through natural language. Analyze binaries conversationally, automate complex workflows, and maintain complete privacy with local AI models.
YouTube Setup Tutorial
What is OGhidra?
OGhidra enhances Ghidra with AI capabilities, allowing you to:
- Natural Language Analysis - Ask questions about functions, strings, imports in plain English
- Automated Workflows - Rename functions, detect patterns, generate comprehensive reports
- Local AI Models - Complete privacy with models running on your hardware (Ollama)
- Cloud AI Support - Connect to external APIs (OpenAI, Google Gemini, Anthropic Claude)
- Malware Detection - Automatic pattern matching for 12+ evasion and injection techniques
- Smart Enumeration - Build queryable knowledge graphs from binary analysis
- Multi-Instance Analysis - Run multiple Ghidra instances for parallel analysis
How It Works
graph TD
A[User Query] --> B[Planning Phase]
B --> C{Execution Phase}
C -- Tool Calls --> D[Ghidra/LLM]
D --> C
C --> E[Review Phase]
E -- Agentic Loop --> B
E --> F[Final Response]
style E fill:#f9f,stroke:#333,stroke-width:2px
style B fill:#bbf,stroke:#333,stroke-width:2px
Agentic Loop: OGhidra uses an adaptive planning system. After each execution cycle, results are reviewed and the AI can choose to gather more information or refine its analysis before providing the final response.
Quick Start
Prerequisites
- Python 3.12+ - Check version:
python --version - Ghidra 12.0.3 (Recommended) - Download from Ghidra Releases
- Plugin build/install path is documented for Ghidra 12.0.3
- Tested with: Ghidra 11.0.3, 11.3.2, 12.0.2, 12.0.3
- Java 21 - Required to build the Ghidra 12.0.3 extension:
java -version - Ollama (optional, for local models) - Install from ollama.com
Installation
# Clone repository
git clone https://github.com/LLNL/OGhidra.git
cd OGhidra
# Install dependencies (choose one)
uv sync # Using UV (recommended)
pip install -r requirements.txt # Using pip
# Configure environment
cp .env.example .env
# Edit .env with your settings
Setup Ghidra Plugin
The OGhidraMCP plugin build steps below target Ghidra 12.0.3 (recommended). There's also a YouTube video tutorial: https://www.youtube.com/watch?v=hBD92FUgR0Y
Building the GhidraMCP Extension
As a developer, you'll need to build the GhidraMCP extension before installing it in Ghidra:
-
Prerequisites:
- Ghidra 12.0.3 installed
- Java 21
-
Option 1: Using the automated build scripts:
-
Windows:
# Set the path to your Ghidra installation (will attempt to find last run copy of Ghidra if not set) set GHIDRA_INSTALL_DIR=C:\path\to\ghidra_12.0.3_PUBLIC # Run the build script build_ghidra_plugin.bat -
Unix/Linux/Mac:
# Set the path to your Ghidra installation (will attempt to find the last run copy of Ghidra if not set) export GHIDRA_INSTALL_DIR=/path/to/ghidra_12.0.3_PUBLIC # Run the build script (make it executable first if needed) chmod +x build_ghidra_plugin.sh ./build_ghidra_plugin.sh
-
-
Option 2: Manual build process:
-
Create/update
OGhidraMCP/gradle.propertieswith your Ghidra install path:GHIDRA_INSTALL_DIR=/absolute/path/to/ghidra_12.0.3_PUBLIC -
On Unix/Linux/macOS:
cd OGhidraMCP $GHIDRA_INSTALL_DIR/support/gradle/gradlew buildExtension --info -
On Windows:
cd OGhidraMCP "%GHIDRA_INSTALL_DIR%\support\gradle\gradlew.bat" buildExtension --info
-
-
Locate the built extension:
- The extension zip file is created in
OGhidraMCP/dist/ - The filename will be something like
ghidra_12.0.3_PUBLIC_YYYYMMDD_OGhidraMCP.zip
- The extension zip file is created in
Installing the GhidraMCP Extension
Once you've successfully built the extension:
-
Install in Ghidra:
- Open Ghidra -> File -> Install Extensions
- Click Add Extension (green plus icon)
- Browse to your
OGhidraMCP/dist/directory - Select the newly built extension zip file (e.g.,
ghidra_12.0.3_PUBLIC_YYYYMMDD_OGhidraMCP.zip) - Restart Ghidra
-
Enable the plugin:
- Open a Ghidra project
- File → Configure → Enable Developer
- Enable the
OGhidraMCPplugin - The server will start on
http://localhost:8080/methods
YOU NEED TO HAVE CODE BROWSER OPEN
Pull AI Models
# For Ollama (local models)
ollama pull gemma3:27b # Good balance (20GB RAM)
ollama pull nomic-embed-text # Embedding model for RAG
# Alternative models
ollama pull gpt-oss:120b # High quality (80GB RAM)
ollama pull devstral-2:123b # High quality (80GB RAM)
ollama pull devstral-2:123b-cloud # Cloud Model
Launch OGhidra
# GUI Mode (recommended)
uv run main.py --ui
# Interactive CLI
uv run main.py --interactive
# In interactive CLI, test connection
health
If you launched GUI mode, use:
curl http://localhost:8080/methods
Configuration
Edit .env to configure your AI provider:
Option 1: Local Models (Ollama)
LLM_PROVIDER=ollama
OLLAMA_BASE_URL=http://localhost:11434/
OLLAMA_MODEL=gemma3:27b
OLLAMA_EMBEDDING_MODEL=nomic-embed-text
Option 2: External APIs
LLM_PROVIDER=external
EXTERNAL_PROVIDER=google
EXTERNAL_API_KEY=your-api-key-here
EXTERNAL_MODEL=gemini-3.1-flash-lite-preview
EXTERNAL_EMBEDDING_MODEL=gemini-embedding-001
Option 3: Custom OpenAI-Compatible API
LLM_PROVIDER=custom_api
CUSTOM_API_URL=https://api.example.com/v1/chat/completions
CUSTOM_API_KEY=your-api-key-here
CUSTOM_API_MODEL=your-model-name
CUSTOM_API_EMBEDDING_MODEL=your-embedding-model
Context Management Settings
Adjust based on your model's context window:
# Context budget in tokens (adjust to your model's limit)
CONTEXT_BUDGET=100000 # 100K tokens for mid-size models
# 200K+ for frontier models
# Execution settings
MAX_EXECUTION_STEPS=5 # Steps per planning cycle
MAX_AGENTIC_CYCLES=3 # How many plan-execute-review loops
AGENTIC_LOOP_ENABLED=true # Enable adaptive replanning
Key Features
1. Smart Tool Buttons (GUI)
One-click access to common reverse engineering tasks:
| Tool | Description |
|---|---|
| Analyze Current Function | Deep dive into selected function's behavior |
| Rename Current Function | AI suggests meaningful names based on analysis |
| Rename All Functions | Bulk rename with Smart/Full/Rename-Only options |
| Analyze Imports | Identify libraries and external dependencies |
| Analyze Strings | Find URLs, credentials, configuration data |
| Generate Report | Comprehensive security assessment |
