AI Analysis
Final verdict: SUSPICIOUS
The package SUGC v0.1.1 has low individual risk factors but raises concerns due to the maintainer's metadata, including a new or inactive account and lack of a proper author name.
- Metadata risk due to new/inactive maintainer account
- Lack of proper maintainer identification
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package's functionality requires external communications.
- Shell: No shell execution patterns detected, indicating the package does not attempt to execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
- Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or sensitive information being stolen.
- Metadata: The maintainer has a new or inactive account and lacks a proper author name, which raises some suspicion but does not conclusively indicate 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: alumni.imperial.ac.uk>
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository OscarHickman/SUGC 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 SUGC
Create a mini-application called 'GalacticExplorer' that leverages the 'SUGC' package to analyze galaxy clustering data. This application should allow users to upload their own galaxy data in a supported format (e.g., CSV, FITS), visualize the spatial distribution of galaxies, and compute the two-point correlation function using the unbiased methods provided by SUGC. Additionally, GalacticExplorer should offer an interactive interface where users can adjust parameters such as binning strategies and smoothing techniques to refine their analysis. The application should output both visual plots and numerical results, enabling users to save their findings for further research. Use Python's Flask framework to build the web-based interface, ensuring that the backend computation is handled efficiently by integrating SUGC's Rust components for performance optimization. Document your code thoroughly and include comments explaining how each part of SUGC is utilized within the application.