https://github.com/Azure/azureml-assets
· scanned 2026-06-05 17:39 UTC (4 days, 22 hours ago)
· 10 languages
1659 raw signals (555 security + 1104 graph) 11/13 scanners ran 78th percentile · Python · large (100-500K LoC) System graph score 59 (higher by 26)
Last scanned 4 days, 22 hours ago · v2 · 449 actionable findings from 2 signal sources. 658 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.
| Component | Sub-score | Weight | Contribution |
|---|---|---|---|
structure_score |
40.0 | 0.15 | 6.00 |
security_score |
100.0 | 0.25 | 25.00 |
testing_score |
100.0 | 0.20 | 20.00 |
documentation_score |
100.0 | 0.15 | 15.00 |
practices_score |
79.0 | 0.15 | 11.85 |
code_quality |
68.0 | 0.10 | 6.80 |
| Overall | 1.00 | 84.6 |
Top 10 actions, ranked by impact × ease. Severity drives impact; tag-based fix-clarity drives ease.
assets/training/model_management/environments/foundation-model-serve/context/foundation/model/serve/api_server.py:355assets/training/model_management/environments/foundation-model-serve/context/foundation/model/serve/api_server.py:397assets/training/model_management/environments/foundation-model-serve/context/foundation/model/serve/api_server.py:431assets/model_monitoring/components/src/model_data_collector_preprocessor/run.py:331assets/model_monitoring/components/src/model_data_collector_preprocessor/spark_run.py:56assets/aml-benchmark/scripts/custom_inference_postprocessors/humaneval.py:280assets/training/model_management/src/azureml/model/mgmt/processors/pyfunc/virchow/virchow_mlflow_model_wrapper.py:45assets/training/finetune_acft_image/src/model_converters/medimage_embed_adapter_merge/medimageinsight_adapter_classification_mlflow_wrapper.py:130assets/training/finetune_acft_image/src/model_converters/medimage_embed_adapter_merge/medimageinsight_zero_shot_classification_mlflow_wrapper.py:191assets/training/finetune_acft_image/src/medimage_insight_adapter_finetune/training.py:298Click "Find this gap" on any action above to jump to it on the Findings tab. Adjust the chip bar to filter by impact (severity), layer, or source.
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