https://github.com/microsoft/VibeVoice.git
· scanned 2026-05-24 01:24 UTC (1 week, 5 days ago)
· 10 languages
216 findings (80 legacy + 136 scanner) 11/13 scanners ran 36th percentile · Python · small (2-20K LoC) Scanner says 92 (lower by 28)
Last scanned 1 week, 5 days ago · v2 · 148 findings from 2 sources. Findings combine the legacy security pipeline AND the multi-layer engine (atlas, wiring, flows, ranked) AND verified AI agent contributions.
| Component | Sub-score | Weight | Contribution |
|---|---|---|---|
structure_score |
75.0 | 0.15 | 11.25 |
security_score |
100.0 | 0.25 | 25.00 |
testing_score |
13.0 | 0.20 | 2.60 |
documentation_score |
95.0 | 0.15 | 14.25 |
practices_score |
40.0 | 0.15 | 6.00 |
code_quality |
45.0 | 0.10 | 4.50 |
| Overall | 1.00 | 63.6 |
Top 10 actions, ranked by impact × ease. Severity drives impact; tag-based fix-clarity drives ease.
demo/vibevoice_asr_gradio_demo.py:108demo/realtime_model_inference_from_file.py:218demo/vibevoice_asr_inference_from_file.py:68demo/web/app.py:114vibevoice/modular/modeling_vibevoice_asr.py:105vibevoice/modular/modeling_vibevoice_streaming.py:161vibevoice/modular/modeling_vibevoice.py:165finetuning-asr/inference_lora.py:68vllm_plugin/scripts/start_server.py:35Click "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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