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
Permitted
Commercial Use
Modify
Distribute
Place Warranty
Sub-License
Private Use
Use Patent Claims
Forbidden
Hold Liable
Use Trademarks
Required
Include Copyright
State Changes
Include License
Include Notice
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
Did You Know...
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use of OSS increased in 65% of companies in 2016
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you can subscribe to e-mail newsletters to receive update from the Open Hub blog
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55% of companies leverage OSS for production infrastructure
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30 Day SummaryApr 20 2025 — May 20 2025
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