The LLM Security Chatbot is designed to assist in understanding and researching cybersecurity research. Mostly a POC. Built using Mistral 7B v1 and integrated into a user-friendly interface using Streamlit, this chatbot leverages natural language processing to provide in-depth analysis and potential mitigation strategies for a wide range of security concerns.
- Interactive Chat Interface: Engage in conversational queries and receive detailed responses.
- Code Snippet Support: Get examples and explanations with formatted code (still a work in progress) snippets for technical understanding.
- Conversation History: Review past queries and responses directly within the application.
- Exportable Conversations: Easily export the conversation history for documentation or further analysis.
To get started with the LLM Security Chatbot, follow these steps:
Ensure you have Python 3.9+ installed on your system. You will also need the streamlit and llama_cpp packages.
- Clone the repository:
git clone https://github.com/jwalker/llm_security_chatbot.git
- Navigate to the project directory:
cd llm_security_chatbot/ - Install the required Python packages:
uv pip install -r requirements.txt
Launch the chatbot by running the Streamlit application:
streamlit run app.pyVisit http://localhost:8501 in your web browser to start interacting with the chatbot.
Enter your cybersecurity-related queries in the text area and hit 'Submit' to receive a response. The chat interface allows for natural language questions and provides detailed explanations, including code examples when relevant.
Contributions are welcome! If you have suggestions for improvements or want to contribute to the development of the LLM Security Chatbot, please feel free to fork the repository and submit a pull request.
If you have any questions or feedback, please reach out via email: [email protected]