AI Analysis
Final verdict: SAFE
The package has minimal risks associated with network usage, shell execution, and code obfuscation. However, the maintainer's inactivity and lack of community engagement slightly elevate the metadata risk.
- Low risk for network and shell activities
- Inactive maintainer and low community engagement
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires internet access for functionality.
- Shell: No shell execution patterns detected, indicating no direct system command execution from the package.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer seems new or inactive, and the repository lacks community engagement.
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 2.0
1 maintainer concern(s) found
Author "Pengxuan Zhu" 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 Jarvis-HEP-Portal
Create a mini-application named 'HEP Data Explorer' using the Python package 'Jarvis-HEP-Portal'. This application will serve as a user-friendly interface for researchers and physicists to interact with high-energy physics data stored in various formats within the Jarvis ecosystem. Your task is to design and implement a feature-rich application that showcases the capabilities of 'Jarvis-HEP-Portal', including but not limited to data retrieval, transformation, and visualization. Step-by-step guide: 1. Set up your development environment with Python and install the 'Jarvis-HEP-Portal' package along with any necessary dependencies. 2. Design a simple yet effective user interface where users can input details such as dataset names or identifiers relevant to high-energy physics experiments. 3. Implement a backend system using 'Jarvis-HEP-Portal' to fetch data from registered sources based on user inputs. Ensure that the application supports multiple data formats and can dynamically adapt to new data sources added to the Jarvis ecosystem. 4. Integrate data transformation functionalities into the application. Users should be able to request specific transformations on the fetched data, such as normalization, scaling, or conversion to different units, all facilitated by the 'Jarvis-HEP-Portal' package. 5. Develop visualization tools within the application to display the transformed data in meaningful ways. Consider implementing both static visualizations like graphs and tables, as well as interactive ones like sliders or dropdown menus for parameter adjustments. 6. Incorporate error handling and logging mechanisms to ensure robustness and maintainability of the application. Logs should capture important events such as successful data retrievals, failed requests, and transformation errors. 7. Finally, document your code thoroughly and provide clear instructions for setting up and running the 'HEP Data Explorer' application. Suggested Features: - Support for real-time data updates from Jarvis-HEP-Portal. - Integration with external libraries for advanced statistical analysis. - User authentication and role-based access control to restrict certain operations. - Export functionality allowing users to save their data and visualizations in common file formats. - Detailed documentation and tutorials for end-users and developers.