Spaces:
Sleeping
Sleeping
Sofia Santos
commited on
Commit
·
885f71a
1
Parent(s):
6d79d16
feat: improves readibility
Browse files
README.md
CHANGED
|
@@ -14,45 +14,45 @@ short_description: AI-driven TDAgent to automate threat analysis with MCP tools
|
|
| 14 |
|
| 15 |
---
|
| 16 |
|
| 17 |
-
# TDAgentTools & TDAgent
|
| 18 |
|
| 19 |
-
|
| 20 |
|
| 21 |
## Team Introduction
|
| 22 |
|
| 23 |
We are an AI-focused team within a company, dedicated to empowering other teams by implementing AI solutions. Our expertise lies in automating processes to enhance productivity and tackle complex tasks that AI excels in. Our hackathon team members include:
|
| 24 |
|
| 25 |
-
- Pedro Completo Bento
|
| 26 |
-
- Josep Pon Farreny
|
| 27 |
-
- Sofia Jeronimo dos Santos
|
| 28 |
-
- Rodrigo Dominguez Sanz
|
| 29 |
-
- Miguel Rodin
|
| 30 |
|
| 31 |
## Project Overview
|
| 32 |
|
| 33 |
-
### Track 1: MCP Tool - TDAgentTools
|
| 34 |
|
| 35 |
-
TDAgentTools serves as an MCP server built using Gradio, offering a wide array of cybersecurity intelligence tools. These tools enable users to augment their LLMs' capabilities by integrating with various publicly available cybersecurity intel resources. Our TDAgentTools are accessible via the following link: [TDAgentTools Space](https://huggingface.co/spaces/Agents-MCP-Hackathon/TDAgentTools).
|
| 36 |
|
| 37 |
#### Available Tools:
|
| 38 |
-
1.
|
| 39 |
-
2.
|
| 40 |
-
3.
|
| 41 |
-
4.
|
| 42 |
-
5.
|
| 43 |
-
6.
|
| 44 |
-
7.
|
| 45 |
-
8.
|
| 46 |
-
9.
|
| 47 |
-
10.
|
| 48 |
-
11.
|
| 49 |
-
12.
|
| 50 |
|
| 51 |
-
> **Note:** TDAgentTools rely on publicly provided APIs and some of
|
| 52 |
|
| 53 |
-
### Track 3: Agentic Demo Showcase - TDAgent
|
| 54 |
|
| 55 |
-
TDAgent is an adaptive and interactive AI agent. This agent facilitates a dynamic AI experience, allowing users to switch the LLM used and adjust the system prompt to refine the agent’s behavior and objectives. It uses TDAgentTools to enrich threat data. Explore it here: [TDAgent Space](https://huggingface.co/spaces/Agents-MCP-Hackathon/TDAgent).
|
| 56 |
|
| 57 |
#### Key Features:
|
| 58 |
- **Intelligent API Interactions**: The agent autonomously interacts with APIs for data enrichment and analysis without explicit user guidance.
|
|
@@ -80,16 +80,14 @@ We aimed to:
|
|
| 80 |
|
| 81 |
Our projects successfully demonstrated rapid prototyping with Gradio and Hugging Face Spaces, achieving all intended objectives while providing an engaging and rewarding experience for our team. This PoC shows the potential for future expansions and refinements in the realm of cybersecurity AI support!
|
| 82 |
|
|
|
|
| 83 |
|
| 84 |
# TDA Agent
|
| 85 |
|
| 86 |
-
|
| 87 |
|
| 88 |
To start developing you need the following tools:
|
| 89 |
|
| 90 |
-
|
| 91 |
|
| 92 |
-
To start, sync all the dependencies with `uv sync --all-groups`.
|
| 93 |
-
Then, install the pre-commit hooks (`uv run pre-commit install`) to
|
| 94 |
-
ensure that future commits comply with the bare minimum to keep
|
| 95 |
-
code _readable_.
|
|
|
|
| 14 |
|
| 15 |
---
|
| 16 |
|
| 17 |
+
# Welcome to **TDAgentTools & TDAgent**
|
| 18 |
|
| 19 |
+
Our innovative proof of concept (PoC) crafted for the Agents-MCP Hackathon. Our initiatives focus on leveraging Agentic AI to enhance cybersecurity threat analysis, providing robust tools for data enrichment and strategic advice for incident handling.
|
| 20 |
|
| 21 |
## Team Introduction
|
| 22 |
|
| 23 |
We are an AI-focused team within a company, dedicated to empowering other teams by implementing AI solutions. Our expertise lies in automating processes to enhance productivity and tackle complex tasks that AI excels in. Our hackathon team members include:
|
| 24 |
|
| 25 |
+
- **Pedro Completo Bento**
|
| 26 |
+
- **Josep Pon Farreny**
|
| 27 |
+
- **Sofia Jeronimo dos Santos**
|
| 28 |
+
- **Rodrigo Dominguez Sanz**
|
| 29 |
+
- **Miguel Rodin**
|
| 30 |
|
| 31 |
## Project Overview
|
| 32 |
|
| 33 |
+
### Track 1: MCP Tool - **TDAgentTools**
|
| 34 |
|
| 35 |
+
**TDAgentTools** serves as an MCP server built using Gradio, offering a wide array of cybersecurity intelligence tools. These tools enable users to augment their LLMs' capabilities by integrating with various publicly available cybersecurity intel resources. Our **TDAgentTools** are accessible via the following link: [TDAgentTools Space](https://huggingface.co/spaces/Agents-MCP-Hackathon/TDAgentTools).
|
| 36 |
|
| 37 |
#### Available Tools:
|
| 38 |
+
1. ***TDAgentTools_get_url_http_content***: Retrieve URL content through an HTTP GET request.
|
| 39 |
+
2. ***TDAgentTools_query_abuseipdb***: Query AbuseIPDB to check if an IP is reported for abusive behavior.
|
| 40 |
+
3. ***TDAgentTools_query_rdap***: Gather information about internet resources such as domain names and IP addresses.
|
| 41 |
+
4. ***TDAgentTools_get_virus_total_url_info***: Fetch URL information using VirusTotal URL Scanner.
|
| 42 |
+
5. ***TDAgentTools_get_geolocation***: Obtain location details from an IP address.
|
| 43 |
+
6. ***TDAgentTools_enumerate_dns***: Access DNS configuration details for a given domain.
|
| 44 |
+
7. ***TDAgentTools_scrap_subdomains_for_domain***: Retrieve subdomains related to a domain.
|
| 45 |
+
8. ***TDAgentTools_retrieve_ioc_from_threatfox***: Get potential IoC information from ThreatFox.
|
| 46 |
+
9. ***TDAgentTools_get_stix_object_of_attack_id***: Access a STIX object using an ATT&CK ID.
|
| 47 |
+
10. ***TDAgentTools_lookup_user***: Seek user details from the Company User Lookup System.
|
| 48 |
+
11. ***TDAgentTools_lookup_cloud_account***: Investigate cloud account information.
|
| 49 |
+
12. ***TDAgentTools_send_email***: Simulate emailing from cert@company.com.
|
| 50 |
|
| 51 |
+
> **Note:** TDAgentTools rely on publicly provided APIs, and some of these require API keys. If any of these API keys are revoked, certain tools may not function as intended.
|
| 52 |
|
| 53 |
+
### Track 3: Agentic Demo Showcase - **TDAgent**
|
| 54 |
|
| 55 |
+
**TDAgent** is an adaptive and interactive AI agent. This agent facilitates a dynamic AI experience, allowing users to switch the LLM used and adjust the system prompt to refine the agent’s behavior and objectives. It uses **TDAgentTools** to enrich threat data. Explore it here: [TDAgent Space](https://huggingface.co/spaces/Agents-MCP-Hackathon/TDAgent).
|
| 56 |
|
| 57 |
#### Key Features:
|
| 58 |
- **Intelligent API Interactions**: The agent autonomously interacts with APIs for data enrichment and analysis without explicit user guidance.
|
|
|
|
| 80 |
|
| 81 |
Our projects successfully demonstrated rapid prototyping with Gradio and Hugging Face Spaces, achieving all intended objectives while providing an engaging and rewarding experience for our team. This PoC shows the potential for future expansions and refinements in the realm of cybersecurity AI support!
|
| 82 |
|
| 83 |
+
---
|
| 84 |
|
| 85 |
# TDA Agent
|
| 86 |
|
| 87 |
+
## Development setup
|
| 88 |
|
| 89 |
To start developing you need the following tools:
|
| 90 |
|
| 91 |
+
- [uv](https://docs.astral.sh/uv/)
|
| 92 |
|
| 93 |
+
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_.
|
|
|
|
|
|
|
|
|