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https://github.com/claudiaslibrary/visualsec
A tool for visualizing and analyzing cybersecurity data as interactive graphs. Supports entity modeling, risk-based coloring, attack path analysis, and data import/export. Designed for OSINT and cybersecurity professionals.
https://github.com/claudiaslibrary/visualsec
cybersecurity ethical-hacking graph hacking hacking-tool matplotlib network osint penetration-testing python security security-tools
Last synced: about 1 month ago
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A tool for visualizing and analyzing cybersecurity data as interactive graphs. Supports entity modeling, risk-based coloring, attack path analysis, and data import/export. Designed for OSINT and cybersecurity professionals.
- Host: GitHub
- URL: https://github.com/claudiaslibrary/visualsec
- Owner: ClaudiasLibrary
- Created: 2024-12-28T10:55:39.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2024-12-28T11:03:49.000Z (about 1 month ago)
- Last Synced: 2024-12-28T11:27:25.908Z (about 1 month ago)
- Topics: cybersecurity, ethical-hacking, graph, hacking, hacking-tool, matplotlib, network, osint, penetration-testing, python, security, security-tools
- Language: Python
- Homepage:
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# visualSec
**visualSec** is a dynamic tool for visualizing and analyzing cybersecurity data as interactive graphs. Designed for OSINT practitioners, ethical hackers, and cybersecurity analysts, it simplifies the exploration of complex relationships between entities.
## Features
- **Graph Visualization**: Display entities (e.g., domains, IPs, emails) and relationships with customizable layouts.
- **Risk-Based Node Coloring**: Highlight nodes using colormaps like `Reds` based on attributes such as vulnerabilities or risks.
- **Data Import/Export**:
- Import entities and relationships from JSON.
- Export graphs to GEXF for use with other tools.
- **Analysis Tools**:
- Clustering: Group related nodes (e.g., domains by ASN).
- Pathfinding: Identify attack paths or entity dependencies.
- Heatmaps: Visualize critical vulnerabilities.
## Installation
1. Clone the repository:
```bash
git clone https://github.com/ClaudiasLibrary/visualSec.git
cd visualSec
```
2. Install the required dependencies:
```bash
pip install -r requirements.txt
```
## Usage
1. Import the `CyberSecurityVisualizer` class in your script:
```python
from visualizer import CyberSecurityVisualizer
```
2. Create a visualizer instance and add entities and relationships:
```python
visualizer = CyberSecurityVisualizer()
visualizer.add_entity("Domain: example.com", type="Domain")
visualizer.add_entity("IP: 192.168.1.1", type="IP")
visualizer.add_relationship("Domain: example.com", "IP: 192.168.1.1", relationship="Resolves to")
```
3. Visualize the graph:
```python
visualizer.visualize(layout='spring', title="Cybersecurity Graph")
```
4. Export the graph:
```python
visualizer.export_to_file("cybersecurity_graph.gexf")
```
## Example
Import and visualize data from JSON:
```python
import json
from visualizer import CyberSecurityVisualizer
visualizer = CyberSecurityVisualizer()
# Sample JSON data
sample_json = json.dumps({
"entities": [
{"name": "Domain: example.com", "attributes": {"type": "Domain"}},
{"name": "IP: 192.168.1.1", "attributes": {"type": "IP"}}
],
"relationships": [
{"source": "Domain: example.com", "target": "IP: 192.168.1.1", "attributes": {"relationship": "Resolves to"}}
]
})
# Import data and visualize
visualizer.import_from_json(sample_json)
visualizer.visualize(layout='spring', title="OSINT Graph")
```
## Contributing
Contributions are welcome! Please fork the repository and submit a pull request.
## License
This project is licensed under the MIT License. See the `LICENSE` file for details.