AI Analysis
Final verdict: SAFE
The package exhibits low risks across all critical areas with no signs of malicious intent or activity. However, the metadata suggests a potentially new or inactive maintainer, raising minor concerns.
- Low risk scores in network, shell, obfuscation, and credential checks.
- Metadata indicates a new or inactive maintainer.
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
- Shell: No shell execution detected, indicating the package does not execute external commands.
- Obfuscation: No obfuscation patterns detected, suggesting low risk of malicious activity.
- Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
- Metadata: The maintainer has a short or missing author name and appears to be new or inactive, which raises some concerns but does not strongly indicate 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: leeds.ac.uk>
Suspicious Page Links
score 2.0
Found 1 suspicious link(s) on the package page
Non-HTTPS external link: http://www.stoner.leeds.ac.uk/people/gb
Git Repository History
Repository gb119/Stoner-PythonCode 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 Stoner
Create a Python-based mini-application named 'CondensedMatterExplorer' which leverages the Stoner library to analyze and visualize data from experimental condensed matter physics experiments. This application should allow users to upload their own datasets or use predefined sample datasets included within the application. The core functionalities of 'CondensedMatterExplorer' include but are not limited to: 1. Data Importation: Users should be able to import various types of experimental data files such as CSV, TXT, or HDF5. 2. Data Visualization: Implement plotting functions using Stoner's capabilities to display key parameters like temperature vs. resistance, magnetic field vs. magnetization, etc., in both 2D and 3D plots. 3. Analysis Tools: Incorporate analytical tools provided by Stoner such as fitting routines for common physical models like Ohmic, Curie-Weiss, etc., and statistical analysis methods. 4. Interactive Interface: Develop a simple yet intuitive graphical user interface (GUI) using libraries like PyQt or Tkinter to facilitate easy interaction with the application. 5. Documentation and Help: Ensure there is comprehensive documentation available both within the GUI and as external files (PDFs or HTML) explaining each feature, its usage, and underlying physics principles. 6. Customization Options: Allow users to customize plot styles, save results in different formats (PNG, PDF), and export analysis reports. Your task is to outline the development process from setting up the environment, importing necessary packages including Stoner, through to testing the final product. Emphasize on utilizing Stoner’s unique features for data handling and analysis specific to condensed matter physics experiments.