Topic: Am I Unique lets you learn how identifiable you are on the Internet

[Software Santa]

Am I Unique lets you learn how identifiable you are on the Internet.

Learn how identifiable you are on the Internet
Help us investigate the diversity of web browsers


By clicking on this button, only anonymous data will be collected and a cookie will be stored in your browser for four months. You can find more details in the Privacy Policy.

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What is browser fingerprinting?

Device fingerprinting or browser fingerprinting is the systematic collection of information about a remote device, for identification purposes. Client-side scripting languages allow the development of procedures to collect very rich fingerprints: browser and operating system type and version, screen resolution, architecture type, lists of fonts, plugins, microphone, camera, etc.


On this site, we collect:

    the User agent header
    the Accept header
    the Connection header
    the Encoding header
    the Language header
    the list of plugins
    the platform
    the cookies preferences (allowed or not)
    the Do Not Track preferences (yes, no or not communicated)
    the timezone
    the screen resolution and its color depth
    the use of local storage
    the use of session storage
    a picture rendered with the HTML Canvas element
    a picture rendered with WebGL
    the presence of AdBlock
    the list of fonts



How is the fingerprint collected?

Browser fingerprints are also called “cookieless monsters” because it is not necessary to install any form of cookie to collect a fingerprint. This means that the act of fingerprinting a specific browser is stateless and transparent for the user. Any third-party interested in fingerprinting can exploit a set of different techniques to get a rich fingerprint:

    The user agent and the accept headers are automatically sent to websites when a connection is initiated.

    JavaScript gives access to many browser-populated features like the plugins installed on the user’s device.

    If the Flash plugin is installed, its rich programming interface (API) provides access to many system-specific attributes: exact version of the operating system, list of fonts, screen resolution, timezone.

    Through the display of an HTML5 Canvas element, it is possible to collect small differences in the hardware or in the software configurations, thanks to slight differences in the image rendering between devices. The smallest pixel difference can be detected. This is called canvas fingerprinting .

On this site, we use:

    Plugin Detect for plugins detection in some versions of Internet Explorer.
    three.js for the rendering of a WebGL scene.

How are the fingerprints exploited?
Like all tracking technology, it is a double-edge sword.

Fingerprints can be used in a constructive way to combat fraud or credential hijacking, by checking that a user who logs into a specific site is likely the legitimate user.

Fingerprints can also be used in more questionable way, in order to track users across web sites and collect information about their habits and their tastes without the users knowing about it.

Fingerprints can even be used in a destructive way: if attackers know which software modules (specific browser version, plugins, etc.) are installed on a specific device, they can deliver exploits that are tailored for these specific modules or combination of modules.
Who maintains this web site?
This web site is created and maintained by a team of researchers, who investigates the software monocultures and software diversity on the web. The research team is financially supported by the DIVERSIFY European project and by a grant from the INSA-Rennes school. The site is hosted at the INRIA Rennes Bretagne-Atlantique research center and the IRISA lab.

What is the purpose of this web site?
Inform users about their position within the web ecosystem
With this web site, we aim at providing users with some basic information about their configuration and how trackable it is. We also want to exploit the data we collect to advise users about how they can be more similar to others and thus be less trackable.

Investigate the diversity of fingerprints
The research question we investigate is: how can we automatically reconfigure a users platform to fuzz the device fingerprint in a realistic manner? The degree of realism is important to prevent users of our solution to be detected as such. The collection of a large base of real fingerprints will allow us to tune our solution towards platforms that are as different as possible yet not distinguishable as "strange" configurations.

https://amiunique.org