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| title: TDAgent | |
| emoji: 💬 | |
| colorFrom: yellow | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 5.31.0 | |
| app_file: app.py | |
| pinned: false | |
| license: apache-2.0 | |
| tags: | |
| - agent-demo-track | |
| short_description: AI-driven TDAgent to automate threat analysis with MCP tools | |
| # Hackathon Participation: Cybersecurity AI Agents | |
| This project is our contribution to Tracks 1 and 3 of the [Agents-MCP-Hackathon](https://huggingface.co/Agents-MCP-Hackathon), focused on applying AI technologies in the cybersecurity domain. Our aim is to develop solutions that improve the operational efficiency in cybersecurity through automation and data-driven insights. | |
| ## Team Overview | |
| Our team is part of the AI division in our company's cybersecurity department. We focus on implementing AI-based solutions to assist cybersecurity operations. Our team members include: | |
| - **Pedro Completo Bento** | |
| - **Josep Pon Farreny** | |
| - **Sofia Jeronimo dos Santos** | |
| - **Rodrigo Dominguez Sanz** | |
| - **Miguel Rodin** | |
| ## Project Goals | |
| We are exploring the application of AI agents to aid cybersecurity analysts in threat data enrichment and threat analysis. Our main goals are: | |
| 1. To experiment with agentic technologies like Gradio and MCP. | |
| 2. To explore how AI can improve data enrichment capabilities in threat analysis. | |
| 3. To develop autonomous agents capable of API interaction, data enrichment, and threat evaluation. | |
| ## Track 1: MCP Tool / Server | |
| In Track 1, we developed **TDAgentTools**, a Gradio-powered MCP server offering a set of public cybersecurity intelligence tools. This tool is designed to assist cybersecurity professionals in their threat analysis and response tasks. | |
| Access TDAgentTools here: [TDAgentTools Space](https://huggingface.co/spaces/Agents-MCP-Hackathon/TDAgentTools) | |
| ## Track 3: Agentic Demo Showcase | |
| For Track 3, we created **TDAgent**, an AI agent with a chat interface that connects to MCPs, defaulting to TDAgent MCP. The agent utilizes **TDAgentTools** or other MCP servers to gather additional threat intelligence, providing enriched data for more comprehensive threat evaluations. | |
| ## Usage and Purpose | |
| - **TDAgentTools**: Provides cybersecurity professionals with essential analysis tools via a user-friendly interface. | |
| - **TDAgent**: Facilitates interactive AI-supported threat analysis, enhancing efficiency, by leveraging data from MCP servers for improved insights. | |
| Our work aims to reduce the manual effort involved in threat analysis, allowing cybersecurity teams to focus on strategic activities by utilizing AI for operational tasks. | |
| ## Conclusion | |
| This project seeks to demonstrate the practical applications of AI agents in cybersecurity, providing tools and frameworks to improve security operations. | |
| # TDA Agent | |
| # Development setup | |
| To start developing you need the following tools: | |
| * [uv](https://docs.astral.sh/uv/) | |
| To start, sync all the dependencies with `uv sync --all-groups`. | |
| Then, install the pre-commit hooks (`uv run pre-commit install`) to | |
| ensure that future commits comply with the bare minimum to keep | |
| code _readable_. | |
| ## Old content | |
| An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index). | |