Regression Modeling
Pass
Audited by Gen Agent Trust Hub on Feb 17, 2026
Risk Level: SAFE
Full Analysis
- Standard ML Implementation (SAFE): The code follows standard practices for regression modeling using scikit-learn, numpy, and pandas. There is no evidence of malicious intent or hidden functionality.
- Data Privacy (SAFE): The script generates its own synthetic data for demonstration purposes. It does not attempt to read sensitive system files, environment variables, or user credentials.
- Network Security (SAFE): No network-related functions (e.g., requests, urllib, socket) are used. The skill does not communicate with external servers.
- Execution Safety (SAFE): The code does not use dangerous functions such as eval(), exec(), or subprocess.run(). All operations are confined to standard mathematical and plotting routines.
- Dependency Review (SAFE): All imported libraries (pandas, numpy, matplotlib, sklearn, seaborn, scipy, statsmodels) are industry-standard packages for data science.
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