STRIDE GPT: An AI-powered threat modeling tool

by ddos · Published · Updated

STRIDE GPT

STRIDE GPT is an AI-powered threat modeling tool that leverages OpenAI’s GPT models to generate threat models and attack trees for a given application based on the STRIDE methodology. Users provide application details, such as the application type, authentication methods, and whether the application is internet-facing or processes sensitive data. The GPT model then generates its output based on the provided information.

Features

  • Generates unique incident response scenarios based on chosen threat actor groups.
  • Allows you to specify your organization’s size and industry for a tailored scenario.
  • Displays a detailed list of techniques used by the selected threat actor group as per the MITRE ATT&CK framework.
  • 🆕 Create custom scenarios based on a selection of ATT&CK techniques.
  • 🆕 Capture user feedback on the quality of the generated scenarios.
  • Downloadable scenarios in Markdown format.
  • Integrated with LangSmith for powerful debugging, testing, and monitoring of model performance.

Installation

Option 1: Cloning the Repository

  1. Clone this repository:

    git clone https://github.com/mrwadams/stride-gpt.git

  2. Change to the cloned repository directory:

    cd stride-gpt

  3. Install the required Python packages:

    pip install -r requirements.txt

Option 2: Using Docker Container

  1. Pull the Docker image from Docker Hub:

    docker pull mrwadams/stridegpt:latest

Usage

Option 1: Running the Streamlit App Locally

  1. Run the Streamlit app:

    streamlit run main.py

  2. Open the app in your web browser using the provided URL.

  3. Follow the steps in the Streamlit interface to use STRIDE GPT.

Option 2: Using Docker Container

  1. Run the Docker container:

    docker run -p 8501:8501 mrwadams/stridegpt

    This command will start the container and map port 8501 (default for Streamlit apps) from the container to your host machine.

  2. Open a web browser and navigate to http://localhost:8501 to access the app running inside the container.

  3. Follow the steps in the Streamlit interface to use STRIDE GPT.

Copyright (C) 2024 mrwadams

Source: https://github.com/mrwadams/

Tags: AI-powered threat modeling