aidotse/LeakPro
Oct 2024 – Jun 2025
7 Months active
Languages Used
JavaScriptPythonJupyter NotebookShellYAML
Technical Skills
Backend DevelopmentCode RefactoringError HandlingSoftware DevelopmentTestingAPI Development
henrikfo
PROFILE
Henrikfo
Henrik Forsgren developed and enhanced privacy-preserving machine learning workflows in the aidotse/LeakPro repository, focusing on attack simulation, reporting, and reproducibility. Over seven months, he delivered features such as end-to-end DP-SGD training and auditing pipelines for datasets like CIFAR-10 and CelebA-HQ, integrating PyTorch and Opacus for differential privacy. Henrik refactored backend components to improve error handling, configuration management, and test coverage, while also expanding support for PDF report generation and synthetic data attacks. His work emphasized robust configuration-driven experimentation, reliable analytics, and maintainable code, demonstrating depth in Python development, data privacy, and machine learning engineering practices.
Overall Statistics
Feature vs Bugs
91%Features
Repository Contributions
43Total
Bugs
1
Commits
43
Features
10
Lines of code
10,279
Activity Months7
Your Network
11 people
Work History
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025 (2025-06) monthly performance summary for aidotse/LeakPro: Delivered enhancements to CIFAR DP-SGD privacy attack experiment configuration and training workflow, with refactoring to better manage DP-SGD parameters and virtual batch sizes. Simplified configuration loading by renaming train_config_dpsgd.yaml to a generic train_config.yaml, ensuring the system points to the intended configuration. Addressed configuration issues flagged by stakeholders and aligned changes with the attack suite requirements. Implemented two commits to complete these changes.
2 Commits • 1 Features
Jun 1, 2025June 2025 (2025-06) monthly performance summary for aidotse/LeakPro: Delivered enhancements to CIFAR DP-SGD privacy attack experiment configuration and training workflow, with refactoring to better manage DP-SGD parameters and virtual batch sizes. Simplified configuration loading by renaming train_config_dpsgd.yaml to a generic train_config.yaml, ensuring the system points to the intended configuration. Addressed configuration issues flagged by stakeholders and aligned changes with the attack suite requirements. Implemented two commits to complete these changes.
June 2025
April 2025
13 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for aidotse/LeakPro: Delivered end-to-end privacy-preserving training and auditing workflows using DP-SGD across CIFAR10 and CelebA-HQ, consolidated model integration, training handlers, notebook support, and standardized paths/configs, with PDF audit reporting to support privacy compliance. Implemented an end-to-end DP-SGD example suite, stabilized the workflow, and provided production-ready references for privacy audits. Also fixed a formatting bug in the Abstract input handler to align with code standards and improve maintainability. The work enhances privacy-by-design capabilities, improves reproducibility, and strengthens readiness for future privacy-focused deployments.
April 2025
13 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for aidotse/LeakPro: Delivered end-to-end privacy-preserving training and auditing workflows using DP-SGD across CIFAR10 and CelebA-HQ, consolidated model integration, training handlers, notebook support, and standardized paths/configs, with PDF audit reporting to support privacy compliance. Implemented an end-to-end DP-SGD example suite, stabilized the workflow, and provided production-ready references for privacy audits. Also fixed a formatting bug in the Abstract input handler to align with code standards and improve maintainability. The work enhances privacy-by-design capabilities, improves reproducibility, and strengthens readiness for future privacy-focused deployments.
March 2025
11 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for aidotse/LeakPro: delivered an end-to-end CIFAR-10 DP-SGD training workflow and enhanced MIA auditing for CIFAR-10, with robust privacy reporting and metadata tracking. Implemented with ResNet-18 and PrivacyEngine integration, configurable privacy parameters (epsilon, delta), and generation of training/privacy reports. Addressed key integration and metadata handling issues to ensure correct model/optimizer usage and return values. YAML/config restoration improvements support reproducible experiments and audit trails.
11 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for aidotse/LeakPro: delivered an end-to-end CIFAR-10 DP-SGD training workflow and enhanced MIA auditing for CIFAR-10, with robust privacy reporting and metadata tracking. Implemented with ResNet-18 and PrivacyEngine integration, configurable privacy parameters (epsilon, delta), and generation of training/privacy reports. Addressed key integration and metadata handling issues to ensure correct model/optimizer usage and return values. YAML/config restoration improvements support reproducible experiments and audit trails.
March 2025
January 2025
4 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary focusing on PDF report generation reliability for aidotse/LeakPro. Delivered two features with enhanced test coverage and edge-case handling to improve output fidelity and reduce production risks. No major bugs fixed this month; primary improvements were in test harness and robustness.
January 2025
4 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary focusing on PDF report generation reliability for aidotse/LeakPro. Delivered two features with enhanced test coverage and edge-case handling to improve output fidelity and reduce production risks. No major bugs fixed this month; primary improvements were in test harness and robustness.
December 2024
7 Commits • 2 Features
Dec 1, 2024December 2024: Delivered major LeakPro enhancements and strengthened testing/CI, enabling broader evaluation coverage and greater stability. Key outcomes include multi-attack support (MIA and GIA) with CIFAR dataset handling, a refactored report pipeline to support multiple attack result types, CIFAR dataset integration and model preparation modules, and a comprehensive test/CI refresh to improve reliability. Cleanup of GIA assets and notebook alignment reduce technical debt and improve maintainability. These changes boost business value by enabling robust security assessments with faster feedback loops and lower regression risk.
7 Commits • 2 Features
Dec 1, 2024December 2024: Delivered major LeakPro enhancements and strengthened testing/CI, enabling broader evaluation coverage and greater stability. Key outcomes include multi-attack support (MIA and GIA) with CIFAR dataset handling, a refactored report pipeline to support multiple attack result types, CIFAR dataset integration and model preparation modules, and a comprehensive test/CI refresh to improve reliability. Cleanup of GIA assets and notebook alignment reduce technical debt and improve maintainability. These changes boost business value by enabling robust security assessments with faster feedback loops and lower regression risk.
December 2024
November 2024
4 Commits • 1 Features
Nov 1, 2024Month: 2024-11 — The LeakPro project (aidotse/LeakPro) delivered a major upgrade to reporting and results handling for attack analyses (MIA/GIA) with an emphasis on robustness, reproducibility, and demonstrability. The work strengthens data organization, analytics reliability, and onboarding for stakeholders.
November 2024
4 Commits • 1 Features
Nov 1, 2024Month: 2024-11 — The LeakPro project (aidotse/LeakPro) delivered a major upgrade to reporting and results handling for attack analyses (MIA/GIA) with an emphasis on robustness, reproducibility, and demonstrability. The work strengthens data organization, analytics reliability, and onboarding for stakeholders.
October 2024
2 Commits • 1 Features
Oct 1, 2024Month: 2024-10 — Focused on strengthening reliability and maintainability of the leak reporting workflow in aidotse/LeakPro. Delivered robust ReportHandler improvements and expanded test coverage to ensure stable report generation and easier debugging. Refactor work included improved error handling for result types and missing classes/methods, added type hints, and cleaned up tests for ReportHandler and MIAResult. Resulted in higher reliability, reduced debugging time, and a clearer path for future enhancements.
2 Commits • 1 Features
Oct 1, 2024Month: 2024-10 — Focused on strengthening reliability and maintainability of the leak reporting workflow in aidotse/LeakPro. Delivered robust ReportHandler improvements and expanded test coverage to ensure stable report generation and easier debugging. Refactor work included improved error handling for result types and missing classes/methods, added type hints, and cleaned up tests for ReportHandler and MIAResult. Resulted in higher reliability, reduced debugging time, and a clearer path for future enhancements.
October 2024
Activity
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Quality Metrics
Correctness83.2%
Maintainability83.6%
Architecture80.8%
Performance73.2%
AI Usage21.4%
Skills & Technologies
Programming Languages
JavaScriptJupyter NotebookPythonShellYAML
Technical Skills
API DevelopmentAttack SimulationBackend DevelopmentCode FormattingCode ImprovementCode OptimizationCode RefactoringConfiguration ManagementData AnalysisData CleaningData HandlingData PreparationData PrivacyData ScienceData Visualization
Repositories Contributed To
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