Google Adds Web Bluetooth And 2FA Fingerprint Support To Chrome Beta 70 Web Browser


Google early this month celebrated Chrome 10th anniversary. Now the Alphabets company is introducing some useful features to Chrome 70 which is still in a beta form.




According to the Chromium blog, the Chrome Beta 70 hopes to make logging into websites a little by allowing Chrome users to use their Android fingerprint reader or Mac device Touch ID sensor as a form of two-factor authentication. This feature will save users time because there won't be need for users to enter password or other sensitive information.

Another feature is the Web Bluetooth. This feature will allow sites to securely communicate with nearby Bluetooth devices. This feature is been made available for Windows 10 users for the first time with the coming of Chrome 70, though the feature has been made available for Android, ChromeOS and macOS since Chrome 56. Earlier version Windows and Linux can still access it via this flag: chrome://flags/#enable-experimental-web-platform-features

Also Read: Hundreds of Millions of Android Devices are Exposed To This Vulnerability, And Google Won't Fix It!

To increase privacy, Chrome 70 will no longer include the Android and iOS builds number in the user-agent identification string visible to websites. This is necessary so as to prevent exploits targeting fingerprinting and other forms of abuses.


Google's decision to remove its build numbers from iOS and Android follows in the step of Apple's Safari to freeze the build number at 15E148.

Google removed the "Secure" tag from the URL bar in Chrome 69 when users visit a complaint site(HTTPS), however, Chrome 70 will  display a "Not Secure" warning and red icon when users visits a non-complaint site (HTTP) so as to warn users that the site isn't secure.

Chrome 70 Beta will exit full screen mode to ensure that users have proper context before making any decision on dialog boxes such as authentication or payment prompts.

Developers using the Chrome 70 Beta will be able to experiment with a Shape Detection API that can be used to identify faces, barcodes, and text in images through the web. This will help improve  features that rely on OCR (onscreen character recognition) so that you can easily turn a photo of a text document into a PDF, or simply make it easier to scan in a QR code without needing to pull out a second device.

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