🤖 AI Analysis

Final verdict: SAFE

The package TINTOlib v1.2.2 is assessed as safe with a low risk score. It shows no signs of malicious intent or risky practices.

No network calls detected.
No shell execution detected.

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution detected, indicating no direct system command execution risk.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The maintainer has a new or inactive account and lacks a proper author name, which may indicate low activity or a less experienced developer.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: alumno.uned.es>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository oeg-upm/TINTOlib-Documentation appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with TINTOlib

Create a user-friendly desktop application using Python that converts tabular data from CSV files into visually appealing images. This application should allow users to select a CSV file, customize various aspects of the table image (such as font style, color, background, and cell padding), and then save the resulting image in common formats like PNG or JPEG.

The core functionality will rely on the 'TINTOlib' package, which efficiently handles the conversion of tabular data into images. Here’s a step-by-step guide on how to implement this:

1. **Setup**: Install necessary Python packages including TINTOlib, tkinter for GUI, and pandas for handling CSV files.
2. **User Interface Design**: Use tkinter to design a simple yet effective GUI allowing users to upload CSV files and preview the table before converting it into an image.
3. **Data Handling**: Implement a function to read CSV files using pandas and pass the data to TINTOlib for conversion.
4. **Customization Options**: Allow customization of the table appearance such as choosing fonts, colors, and adding headers/footers.
5. **Image Generation**: Utilize TINTOlib to convert the tabular data into an image based on user preferences.
6. **Save Image**: Provide options for users to save the generated image in different formats and resolutions.
7. **Testing & Feedback**: Ensure thorough testing across various types of CSV files and gather feedback for further improvements.

This application not only leverages the power of TINTOlib but also provides a practical solution for users who need to visualize tabular data in a more engaging format.