AI Analysis
The package shows low risks in terms of network usage, shell execution, and code obfuscation. However, it raises concerns due to its newness and lack of maintainer history or a GitHub repository.
- Metadata risk score is high due to lack of maintainer history and GitHub repository.
- Package is newly published, increasing suspicion.
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 immediate signs of malicious shell command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk of code being hidden maliciously.
- Credentials: No credential harvesting patterns detected, suggesting no suspicious activity related to secret extraction.
- Metadata: The package is brand new with no maintainer history and lacks a GitHub repository, raising concerns about its legitimacy.
Package Quality Overall: Low (1.2/10)
No test suite detected
No test files or test-runner configuration detected
No documentation detected
No documentation URL, doc files, or meaningful description found
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: example.com>
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
3 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a Python-based desktop application called 'StellarGuide' that utilizes the 'alphaSco' package to provide users with detailed information about stars, focusing on the Alpha Sco (Rigol) star system as a primary example. The application should allow users to input specific star names and retrieve information such as distance from Earth, luminosity, spectral type, and any notable events or discoveries related to the star. Additionally, the app should feature a graphical representation of the star's position in the sky based on user location and time. Key Features: - User Input: Allow users to enter star names. - Information Retrieval: Display key details about the entered star using data provided by the 'alphaSco' package. - Visualization: Show the star's location in the night sky relative to the user's geographical location and current date/time. - Educational Content: Include short descriptions about the star's significance in astronomy. How to Utilize 'alphaSco': - Use the 'alphaSco' package to fetch accurate and up-to-date astronomical data regarding the selected star. - Integrate this data into your application to dynamically update information and visualizations based on user inputs.
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