A lightweight Kotlin library for stateless device identification and fingerprinting on Android.
FingerprintJS Android is a free, MIT-licensed library for identifying and fingerprinting Android devices. It generates stable, stateless device identifiers from platform signals, solving the problem of reliably tracking devices across app sessions without storing persistent data. The library provides two identification methods: a random device ID for general use and a composite fingerprint for security-focused scenarios.
Android developers building applications that require device identification for personalization, fraud detection, analytics, or security purposes, particularly those needing a lightweight, crash-free solution.
Developers choose FingerprintJS Android for its simplicity, reliability (100% crash-free), and dual identification approach that balances ease of use with security. Unlike alternatives, it offers stateless identifiers that persist through app reinstallations while being fully written in Kotlin with minimal dependencies.
Free library for identifying and fingerprinting Android devices. MIT license, no restrictions on usage in production.
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Device identifiers remain consistent after app reinstall or data clearance, as explicitly stated in the README for reliable tracking without persistent storage.
Offers both deviceId for general use and fingerprint for security, allowing developers to choose based on their needs, with clear guidance in the documentation.
Built to be 100% crash-free in production, ensuring stable operation in critical environments like fraud detection or analytics.
Methods run on worker threads with caching, as noted in the README, optimizing performance without blocking the main thread.
Version 2 introduced deprecated APIs from v1, requiring migration effort and potential code refactoring, as admitted in the migration guide.
Only supports Android API 21 and higher, excluding older devices, which restricts its use in legacy or broad-market applications.
Device fingerprinting collects multiple platform signals, which can be invasive and may not align with privacy-focused app designs or regulations like GDPR.