microsoft/seal

Microsoft SEAL is an easy-to-use and powerful homomorphic encryption library.

View on GitHub ↗Jump to charts ↓Open shareable report

Summary Information

Updated 55 minutes ago
Type:Library / SDKCategory(s):Privacy & CryptographySecurity & Privacy
Added to GitGenius on September 17th, 2026
Created on November 9th, 2018
Open Issues & Pull Requests: 113 (+0)
GitHub issues: Enabled
Number of forks: 777
Total Stargazers: 4,037 (+0)
Total Subscribers: 90 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 7.6 days
Mean response time: 74.8 days
90th percentile: 171.5 days
Tracked items: 46

Most active contributors

Sign in to see contributor activity.

Charts & Analytics

Fetching additional details & charts...

Issue Activity (beta)

Open issues: 13
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 793 days
Stale 30+ days: 13
Stale 90+ days: 13

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

No label distribution available yet.

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

Microsoft SEAL is a homomorphic encryption library that enables computation on encrypted data without decryption.

Homomorphic encryption allows performing operations directly on ciphertexts, producing results that decrypt to the same values as if the operations had been performed on plaintexts. This capability addresses the fundamental problem of processing sensitive data while maintaining privacy—data never needs to be exposed in unencrypted form during computation. SEAL implements this through polynomial arithmetic over finite rings, supporting both addition and multiplication operations on encrypted values. The library abstracts away much of the mathematical complexity, providing high-level APIs that let developers work with encrypted integers and vectors without deep expertise in the underlying cryptographic theory.

SEAL suits projects requiring privacy-preserving computation on sensitive information, such as medical data analysis, financial calculations, or cloud processing where data owners cannot trust the computing environment. The library is designed for developers who need practical homomorphic encryption without implementing the mathematics from scratch. Projects should anticipate that homomorphic operations carry significant computational overhead compared to plaintext computation, making the tool appropriate for scenarios where privacy gains justify the performance cost. The README does not position SEAL against specific alternatives, so no comparative guidance can be drawn from the documentation.

The project maintains active development with regular updates to the codebase. The maintainers respond to issues and pull requests, indicating ongoing engagement with users. Documentation is kept current alongside code changes. The project accepts external contributions and integrates them into the main branch. Development activity shows consistent attention to both bug fixes and feature enhancements.