| --- |
| title: Security Triage Fleet |
| emoji: 💻 |
| colorFrom: gray |
| colorTo: gray |
| sdk: docker |
| app_port: 8080 |
| pinned: false |
| license: agpl-3.0 |
| short_description: 'A multi-agent cybersecurity system using A2A protocol, OCSF ' |
| --- |
| |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |
|
|
| # Security Triage Fleet |
|
|
| Welcome to the **Security Triage Fleet** project! This repository contains a multi-agent SOC (Security Operations Center) dashboard powered by the Google Agent Development Kit (ADK) and Gemini. |
|
|
| The project orchestrates multiple specialized AI agents (Red Team, Blue Team, Green Team) to triage, analyze, and remediate security threats. It features a FastAPI backend and a web-based dashboard for interactive simulation and Human-In-The-Loop (HITL) approval. |
|
|
| --- |
|
|
| ## 🚀 Setup Instructions |
|
|
| You can run this project either using **Docker** (recommended) or **Locally via Python**. |
|
|
| ### Prerequisites |
| Before you begin, you will need: |
| 1. A **Google API Key** for Gemini models. |
| 2. **Docker** installed (if using the Docker method). |
| 3. **Python 3.11+** installed (if using the local method). |
|
|
| --- |
|
|
| ### Option 1: Running with Docker (Recommended) |
|
|
| Running with Docker ensures you have the exact environment needed without modifying your local system. |
|
|
| **1. Build the Docker image:** |
| Open your terminal in the project root directory and run: |
| ```bash |
| docker build -t security-triage-fleet . |
| ``` |
|
|
| **2. Run the container:** |
| Start the container and pass your Google API Key as an environment variable: |
| ```bash |
| docker run -p 8080:8080 -e GOOGLE_API_KEY="your_api_key_here" security-triage-fleet |
| ``` |
|
|
| **3. Access the Dashboard:** |
| Open your web browser and navigate to: |
| [http://localhost:8080](http://localhost:8080) |
|
|
| --- |
|
|
| ### Option 2: Running Locally with Python |
|
|
| If you prefer to run the project directly on your machine, follow these steps: |
|
|
| **1. Create a virtual environment:** |
| ```bash |
| python -m venv agent-env |
| ``` |
|
|
| **2. Activate the virtual environment:** |
| - **Windows:** |
| ```powershell |
| agent-env\Scripts\activate |
| ``` |
| - **macOS / Linux:** |
| ```bash |
| source agent-env/bin/activate |
| ``` |
|
|
| **3. Install dependencies:** |
| ```bash |
| pip install -r requirements.txt |
| ``` |
|
|
| **4. Configure Environment Variables:** |
| Create a `.env` file in the root directory of the project and add your API key: |
| ```env |
| GOOGLE_API_KEY=your_google_api_key_here |
| ``` |
| *(Note: The server will automatically map this to `GEMINI_API_KEY` if required by underlying libraries).* |
|
|
| **5. Start the Server:** |
| Run the FastAPI server using `uvicorn`: |
| ```bash |
| uvicorn server:app --host 0.0.0.0 --port 8000 |
| ``` |
| *(Alternatively, you can run `python server.py` which will also start the server on port 8000).* |
|
|
| **6. Access the Dashboard:** |
| Open your web browser and navigate to: |
| [http://localhost:8000](http://localhost:8000) |
|
|
| --- |
|
|
| ## 🛠️ Technology Stack |
| * **Agent Framework:** Google ADK (Agent Development Kit), Google GenAI SDK |
| * **Backend:** FastAPI, Uvicorn, Pydantic |
| * **Frontend:** Vanilla HTML/JS/CSS Dashboard |
| * **Containerization:** Docker (Python 3.11-slim) |
|
|
