dnn-modeling
Pass
Audited by Gen Agent Trust Hub on Jun 29, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill implements standard machine learning practices for binary classification using a Multi-Layer Perceptron (MLP).
- [SAFE]: Data processing is performed using established libraries (Pandas, NumPy, Scikit-learn). The use of
df.query()for data filtering is a standard feature and is applied to data within the dataframe context. - [SAFE]: The code includes a 'SafetyGate' module that performs integrity checks on the data (e.g., checking for temporal leakage, label drift, and sample size) which is a security and quality best practice.
- [SAFE]: No suspicious network operations or unauthorized file system access patterns were identified. External dependencies are restricted to well-known machine learning and data science packages.
- [SAFE]: Static analysis flags regarding
eval()are false positives related to the standard PyTorchmodel.eval()method, which sets the neural network to evaluation mode.
Audit Metadata