🤖 AI Analysis

Final verdict: SAFE

The package exhibits minimal risks across all categories except metadata, where it shows signs of low maintenance. However, there is no concrete evidence of malicious intent.

No network or shell activity
No obfuscation or credential risk
Low maintenance signs in metadata

Per-check LLM notes

Network: No network calls suggest normal behavior for a package focused on local functionality.
Shell: No shell executions indicate the package does not attempt to execute system commands, which is typical for benign software.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows signs of low maintenance and potential lack of transparency, raising some suspicion but not conclusive evidence of malice.

🔬 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: ms27.hinet.net>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 8.0

4 maintainer concern(s) found

Only one version has ever been released — brand new package
Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)
Package has no PyPI classifiers (low effort / metadata quality)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with PyPylonBaslerAPI

Create a real-time camera streaming application using the PyPylonBaslerAPI package. This application will allow users to connect to Basler cameras, capture images, and stream them in real-time. Here’s a detailed breakdown of the project requirements and steps to implement it:

1. **Project Setup**: Begin by setting up your Python environment. Ensure you have installed the PyPylonBaslerAPI package and any other necessary dependencies.
2. **Camera Connection**: Implement functionality to detect and list all available Basler cameras connected to the system. Allow users to select which camera they wish to use for the application.
3. **Real-Time Streaming**: Develop a feature that captures frames from the selected camera at a specified frame rate and displays these frames in real-time within the application window. Consider implementing a simple GUI using a library like Tkinter or PyQt for displaying the video stream.
4. **Image Saving**: Include an option for users to save captured images to their local storage. Provide controls to start and stop saving images as well as options to set file names and formats.
5. **Advanced Features**:
- **Exposure Control**: Allow users to adjust the camera's exposure settings.
- **Resolution Settings**: Provide options to change the resolution of the captured images.
- **Zoom and Pan**: Implement basic zooming and panning functionalities to explore different parts of the image.
6. **Error Handling and Logging**: Ensure robust error handling and logging mechanisms are in place to handle any issues that may arise during the operation of the application.
7. **Documentation and Testing**: Write comprehensive documentation for the application and ensure thorough testing of all implemented features.

The PyPylonBaslerAPI package will be utilized extensively throughout the development process, particularly in connecting to the camera, configuring settings, capturing frames, and managing streams. Your goal is to create a versatile and user-friendly tool that showcases the capabilities of the PyPylonBaslerAPI package.