How the Web Audio API is used for browser fingerprinting

• fingerprintjs

  346 20,863 7.9 TypeScript

  Browser fingerprinting library. Accuracy of this version is 40-60%, accuracy of the commercial Fingerprint Identification is 99.5%. V4 of this library is BSL licensed.

  

For higher identification accuracy, we also developed the FingerprintJS Pro API, which uses machine learning to combine browser fingerprinting with additional identification techniques. You can try FingerprintJS Pro free for 10 days with no usage limits.

• WebKit

  150 7,416 10.0

  Home of the WebKit project, the browser engine used by Safari, Mail, App Store and many other applications on macOS, iOS and Linux.

  

Examples of Google contributions to the Webkit project include: creation of OfflineAudioContext, creation of OscillatorNode, creation of DynamicsCompressorNode.

• InfluxDB

  www.influxdata.com sponsored

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• chromium

  224 17,522 10.0

  The official GitHub mirror of the Chromium source

  

Blink: oscillator, dynamics compressor

• gecko-dev

  78 3,105 10.0

  Read-only Git mirror of the Mercurial gecko repositories at https://hg.mozilla.org. How to contribute: https://firefox-source-docs.mozilla.org/contributing/contribution_quickref.html

  

• brave-core

  174 2,291 10.0 HTML

  Core engine for the Brave browser for Android, Linux, macOS, Windows. For issues https://github.com/brave/brave-browser/issues

  

The farbling modifies the original Blink AudioBuffer by transforming the original audio values.

• list

  46 1,854 8.7 Go

  The Public Suffix List

  

Farbling is Brave’s term for slightly randomizing the output of semi-identifying browser features, in a way that’s difficult for websites to detect, but doesn’t break benign, user-serving websites. These “farbled” values are deterministically generated using a per-session, per-eTLD+1 seed so that a site will get the exact same value each time it tries to fingerprint within the same session, but that different sites will get different values, and the same site will get different values on the next session. This technique has its roots in prior privacy research, including the PriVaricator (Nikiforakis et al, WWW 2015) and FPRandom (Laperdrix et al, ESSoS 2017) projects.

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