Project Summary
Security and Privacy Risk Simulator for Machine Learning
AIJack is an open source tool that helps you identify and protect against security and privacy attacks on machine learning algorithms. It includes defense techniques like Differential Privacy and Homomorphic Encryption, as well as APIs for distributed learning methods like Federated Learning and Split Learning. AIJack currently supports over 30 state-of-the-art methods.
In a Nutshell, AIJack...
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took an estimated 12 years of effort (COCOMO model)
starting with its first commit in January, 2021
ending with its most recent commit about 1 month ago
Quick Reference
Apache License 2.0
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These details are provided for information only. No information here is legal advice and should not be used as such.
Project Security
Vulnerabilities per Version ( last 10 releases )
There are no reported vulnerabilities
Project Vulnerability Report
Security Confidence Index
Vulnerability Exposure Index
30 Day SummaryJun 2 2026 — Jul 2 2026
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12 Month SummaryJul 2 2025 — Jul 2 2026
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