🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risk in terms of network calls, shell execution, and obfuscation. However, it comes from a new maintainer with limited history and no community engagement, raising concerns about its legitimacy.

New maintainer with limited history
No community engagement

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package is from a new maintainer with limited history and no community engagement, raising some suspicion.

🔬 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

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

Repository has zero stars and zero forks

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Only one version has ever been released — brand new package
Author "Aleksandr Dobkin" 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 a750-control

Create a Python-based desktop application named 'RoboPainter' that leverages the 'a750-control' package to enable users to paint digital art using a robotic arm. The application should provide an intuitive interface where users can select colors, brush sizes, and draw on a canvas, with the robotic arm translating these actions into physical movements to create real-world paintings.

Step-by-Step Instructions:
1. Setup the development environment by installing necessary libraries including 'a750-control'.
2. Design a simple GUI using Tkinter or PyQt that includes color pickers, sliders for adjusting brush size, and a canvas for drawing.
3. Integrate 'a750-control' to control the robotic arm movements based on user interactions on the GUI.
4. Implement functionality to translate mouse movements on the canvas into corresponding robotic arm movements, taking into account factors like speed and pressure of the brush.
5. Add features to save and load painting sessions, as well as export the final artwork as an image file.
6. Enhance the app by allowing users to choose from pre-defined shapes or patterns that the robotic arm can draw automatically.

Suggested Features:
- Real-time preview of the robotic arm's movement.
- Adjustable settings for the robotic arm's speed and precision.
- Support for different types of brushes and paints.
- Ability to connect multiple robotic arms for more complex drawings.
- Integration with online platforms to share artwork created with RoboPainter.

How 'a750-control' Package is Utilized:
- Use 'a750-control' to establish a connection between the computer and the robotic arm.
- Leverage the package's functions to send commands for the arm's movements, such as moving to specific coordinates, setting the speed, and controlling the gripper for different brush sizes.
- Monitor the status of the robotic arm through feedback provided by 'a750-control', ensuring smooth and accurate execution of the painting process.