aidotse/LeakPro
Oct 2024 – Mar 2026
11 Months active
Languages Used
JavaScriptPythonJupyter NotebookShellYAML
Technical Skills
Backend DevelopmentCode RefactoringError HandlingSoftware DevelopmentTestingAPI Development
henrikfo
PROFILE
Henrikfo
Henrik Forsgren developed and maintained core privacy auditing and attack simulation workflows for the aidotse/LeakPro repository, focusing on robust backend engineering and data integrity. Over 11 months, he delivered features such as end-to-end DP-SGD training pipelines, multi-attack reporting, and reproducible analytics for datasets like CIFAR-10 and CelebA-HQ. His work emphasized code refactoring, configuration management, and comprehensive testing, using Python, PyTorch, and NumPy to ensure reliability and maintainability. Henrik addressed edge cases in PDF generation, improved onboarding with CI/CD scaffolding, and enhanced data processing, resulting in a stable, extensible platform for privacy research and security assessments.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
67Total
Bugs
5
Commits
67
Features
20
Lines of code
743,754
Activity Months11
Your Network
12 peopleWork History
March 2026
9 Commits • 2 Features
Mar 1, 2026March 2026 (aidotse/LeakPro): Delivered key auditing and data handling enhancements, stabilized the codebase, and advanced testing practices. Key outcomes include SeqMIA auditing configs with ResNet18 compatibility, improved SinglingOutEvaluator for converting numerical columns to categorical data with thresholds and validated tests, and hardened multivariate singling-out queries with improved NaN handling and deterministic tests. Also completed merge conflict resolution to restore a stable development baseline. These changes deliver stronger security auditing, better data quality, and more reliable deployments.
9 Commits • 2 Features
Mar 1, 2026March 2026 (aidotse/LeakPro): Delivered key auditing and data handling enhancements, stabilized the codebase, and advanced testing practices. Key outcomes include SeqMIA auditing configs with ResNet18 compatibility, improved SinglingOutEvaluator for converting numerical columns to categorical data with thresholds and validated tests, and hardened multivariate singling-out queries with improved NaN handling and deterministic tests. Also completed merge conflict resolution to restore a stable development baseline. These changes deliver stronger security auditing, better data quality, and more reliable deployments.
March 2026
February 2026
5 Commits • 4 Features
Feb 1, 2026February 2026 (2026-02) — Delivered foundational contributor onboarding improvements and strengthened data integrity and model configuration workflows for LeakPro. Key contributions to the repo include: - Contributor Onboarding and Repository Scaffolding: Implemented issue and pull request templates, a test workflow, and a .gitignore to streamline onboarding and improve repository structure. - Model Configuration JSON Dump Formatting Consistency: Refactored JSON dumping to ensure consistent formatting of model configuration data for reliable downstream processing. - Data Integrity Warnings for Excessive NaN Values: Added a warning mechanism to alert users when excessive NaN values are detected, enhancing data quality checks. - SinglingOutEvaluator: Numeric-to-Categorical Conversion Enhancements: Added logging for auto-num2col, adjusted the conversion threshold, and introduced a toggle to disable this behavior for better control. - SinglingOutEvaluator: Test Fixes for Narrow Numeric-to-Categorical Behavior: Fixed failing tests related to numeric-to-categorical conversion and expanded test coverage.
February 2026
5 Commits • 4 Features
Feb 1, 2026February 2026 (2026-02) — Delivered foundational contributor onboarding improvements and strengthened data integrity and model configuration workflows for LeakPro. Key contributions to the repo include: - Contributor Onboarding and Repository Scaffolding: Implemented issue and pull request templates, a test workflow, and a .gitignore to streamline onboarding and improve repository structure. - Model Configuration JSON Dump Formatting Consistency: Refactored JSON dumping to ensure consistent formatting of model configuration data for reliable downstream processing. - Data Integrity Warnings for Excessive NaN Values: Added a warning mechanism to alert users when excessive NaN values are detected, enhancing data quality checks. - SinglingOutEvaluator: Numeric-to-Categorical Conversion Enhancements: Added logging for auto-num2col, adjusted the conversion threshold, and introduced a toggle to disable this behavior for better control. - SinglingOutEvaluator: Test Fixes for Narrow Numeric-to-Categorical Behavior: Fixed failing tests related to numeric-to-categorical conversion and expanded test coverage.
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for aidotse/LeakPro: Focused on code hygiene and reliability improvements in the test evaluation path. Delivered a feature-level cleanup that removes a duplicate line responsible for retrieving the naive rate from evaluation results, streamlining the test function and improving code clarity. Implemented via commit 3e4ca0486e56d04f449513dc876a2bebfc3c6d66 with message 'Removed duplicate lines'.
1 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for aidotse/LeakPro: Focused on code hygiene and reliability improvements in the test evaluation path. Delivered a feature-level cleanup that removes a duplicate line responsible for retrieving the naive rate from evaluation results, streamlining the test function and improving code clarity. Implemented via commit 3e4ca0486e56d04f449513dc876a2bebfc3c6d66 with message 'Removed duplicate lines'.
December 2025
November 2025
9 Commits • 3 Features
Nov 1, 2025Month 2025-11: Delivered major enhancements to aidotse/LeakPro, including robust data processing, enhanced shuffling and sorting, and more flexible linkability evaluation. Fixed a critical indentation bug in nearest_neighbors. Expanded test coverage for shuffled_argsorted, boosting reliability under duplicates and randomness. These changes improve synthetic data generation quality, reliability of linkability assessments, and overall system stability across data generation pipelines.
November 2025
9 Commits • 3 Features
Nov 1, 2025Month 2025-11: Delivered major enhancements to aidotse/LeakPro, including robust data processing, enhanced shuffling and sorting, and more flexible linkability evaluation. Fixed a critical indentation bug in nearest_neighbors. Expanded test coverage for shuffled_argsorted, boosting reliability under duplicates and randomness. These changes improve synthetic data generation quality, reliability of linkability assessments, and overall system stability across data generation pipelines.
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
Correctness85.6%
Maintainability84.6%
Architecture82.6%
Performance78.0%
AI Usage22.4%
Skills & Technologies
Programming Languages
JavaScriptJupyter NotebookPythonShellYAML
Technical Skills
API DevelopmentAttack SimulationBackend DevelopmentCI/CDCode FormattingCode ImprovementCode OptimizationCode RefactoringConfiguration ManagementData AnalysisData CleaningData HandlingData PreparationData PrivacyData Science
Repositories Contributed To
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