AI Analysis
The package has a low risk score due to the lack of network and shell risks, but it is newly released with an inactive maintainer, raising concerns about its legitimacy and potential for future malicious updates.
- Newly released package with no activity history
- Inactive maintainer
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external communication.
- Shell: No shell execution patterns detected, indicating the package likely does not execute system commands.
- Metadata: The package is newly released with no activity history and the maintainer seems to be inactive or new, raising some suspicion but not conclusive evidence of malice.
Package Quality Overall: Low (2.0/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (1912 chars)
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: gmail.com
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
2 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor "Dr Taher Abunama" 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 mini-application that simulates the operation of a wastewater treatment plant using the 'asm2dbsm2' Python package. This application will allow users to input various parameters related to the wastewater characteristics and plant conditions, such as influent flow rate, organic loading, and operational settings. Based on these inputs, the application will utilize the 'asm2dbsm2' package to simulate the biological processes within the plant, including nitrification, denitrification, and phosphorus removal. The output will include key performance indicators such as effluent quality metrics and process efficiency. Additionally, the application should feature a user-friendly interface for data input and visualization of results. Consider implementing features like real-time simulation adjustments based on user feedback, historical data analysis, and predictive maintenance suggestions. Use the 'asm2dbsm2' package to extend the core functionalities by incorporating advanced modeling techniques and extended module support.
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