AI Analysis
Final verdict: SAFE
The package does not perform any network calls or shell executions, which are common indicators of malicious behavior. While the metadata risk is slightly elevated due to incomplete maintainer information, there are no clear signs of malicious intent.
- No network calls detected
- No shell execution patterns
- Incomplete maintainer information
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires network functionality.
- Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
- Metadata: The maintainer's author information is incomplete and may indicate a less experienced or new developer, but there are no clear signs of malicious intent.
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: gmail.com>
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository Dnyarri/PyPNM appears legitimate
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 PyPNM
Create a simple yet powerful image processing mini-application using the Python package 'PyPNM'. This application will serve as a basic tool for handling PNM (PPM and PGM) images, enabling users to read, display, manipulate, and save these images. The app should support operations such as converting between PPM and PGM formats, adjusting brightness and contrast, and saving images in different bit depths (8-bit and 16-bit). Additionally, implement a feature that allows users to view the pixel data of an image directly. ### Steps to Build the Application: 1. **Setup**: Install the required packages, primarily 'PyPNM', and any additional libraries necessary for GUI creation (such as Tkinter). 2. **Reading Images**: Implement functionality to load PNM images from disk into memory using PyPNM. Ensure the application can handle both PPM and PGM formats. 3. **Displaying Images**: Create a basic GUI using Tkinter to display the loaded image on screen. Allow users to zoom in/out and pan across the image. 4. **Image Manipulation**: Add features to adjust the brightness and contrast of the image. Use PyPNM's capabilities to modify pixel values directly. 5. **Saving Images**: Provide options to save the modified image back to disk in either PPM or PGM format, allowing users to choose the bit depth (8-bit or 16-bit). 6. **Pixel Data Viewer**: Implement a feature within the GUI that displays the raw pixel data of the current image, highlighting how PyPNM stores and accesses pixel information. 7. **Format Conversion**: Include a function to convert images between PPM and PGM formats, demonstrating PyPNM's ability to handle different types of PNM files. 8. **Testing**: Test each feature thoroughly to ensure they work correctly with various PNM files, including those with different bit depths. 9. **Documentation**: Write clear documentation explaining how to use each feature of the application and how PyPNM contributes to its functionality. ### Suggested Features: - Support for real-time preview of changes when adjusting brightness and contrast. - Option to import/export images in other formats like PNG or JPEG using external libraries. - Advanced features like edge detection or noise reduction, utilizing PyPNM's image processing capabilities. - Integration with command-line interface for batch processing of multiple PNM files. By following these steps and implementing these features, you'll create a versatile tool that showcases the power of PyPNM for handling PNM images.