Add end-to-end Streamlit privacy auditor UI (MVP)#386
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Introduces leakpro/ui/ — a wizard-style Streamlit dashboard that guides
users through the full LeakPro audit journey in a browser:
Stage 0 – Overview: landing page with pipeline diagram and resume support
Stage 1 – Configure: YAML editors, attack checklist, DP-SGD toggle (ε/δ sliders)
Stage 2 – Train: target model training with live progress; supports both
standard and DP-SGD (Opacus) modes using existing handlers
Stage 3 – Audit: runs MIA attacks with live log streaming per attack
Stage 4 – Explore Results: four interactive tabs
• Summary — risk cards, traffic-light indicator, plain-English verdict,
DP-SGD privacy impact panel
• ROC Analysis — interactive Plotly ROC curves (log-log, all attacks overlaid)
• Signal Histograms — member vs non-member distributions + threshold slider
• Sensitive Records — top-N riskiest training images (CIFAR grid) or
tabular rows + CSV export for all data types
Reuses CifarInputHandler, CifarInputHandlerDPsgd, LeakPro, and MIAResult
from existing code. No changes to attack pipeline."
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taking care of in PR #393 |
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Streamlit Privacy Auditor UI — MVP + UX Improvements
Summary
leakpro/ui/) for running MIA privacy audits without touching any codeWhat's included
New UI (
leakpro/ui/)A 4-stage wizard launched via
streamlit run leakpro/ui/dashboard.py:Bug fix — logit cache indexing
prepare_data()previously assigned random population-space indices to train/test splits.RMIA and BASE attacks assume
logits_cache[i]corresponds to population pointi,causing
IndexError: index N is out of boundsat audit time.Fix: the population is now shuffled once and sequential 0-based indices are assigned
(
train = [0…n-1],test = [n…n+m-1]), so position always equals population index.The population pickle is always regenerated to stay consistent.
UX improvements
Test plan
ssh -L 8501:localhost:8501 user@host) required to access from a remote machine