All posts by Alastair R. Beresford

Calibration Fingerprint Attacks for Smartphones

When you visit a website, your web browser provides a range of information to the website, including the name and version of your browser, screen size, fonts installed, and so on. Website authors can use this information to provide an improved user experience. Unfortunately this same information can also be used to track you. In particular, this information can be used to generate a distinctive signature, or device fingerprint, to identify you.

A device fingerprint allows websites to detect your return visits or track you as you browse from one website to the next across the Internet. Such techniques can be used to protect against identity theft or credit card fraud, but also allow advertisers to monitor your activities and build a user profile of the websites you visit (and therefore a view into your personal interests). Browser vendors have long worried about the potential privacy invasion from device fingerprinting and have included measures to prevent such tracking. For example, on iOS, the Mobile Safari browser uses Intelligent Tracking Prevention to restrict the use of cookies, prevent access to unique device settings, and eliminate cross-domain tracking.

We have developed a new type of fingerprinting attack, the calibration fingerprinting attack. Our attack uses data gathered from the accelerometer, gyroscope and magnetometer sensors found in smartphones to construct a globally unique fingerprint. Our attack can be launched by any website you visit or any app you use on a vulnerable device without requiring any explicit confirmation or consent from you. The attack takes less than one second to generate a fingerprint which never changes, even after a factory reset. This attack therefore provides an effective means to track you as you browse across the web and move between apps on your phone.

One-minute video providing a demo and describing how the attack works

Our approach works by carefully analysing the data from sensors which are accessible without any special permissions on both websites and apps. Our analysis infers the per-device factory calibration data which manufacturers embed into the firmware of the smartphone to compensate for systematic manufacturing errors. This calibration data can then be used as the fingerprint.

In general, it is difficult to create a unique fingerprint on iOS devices due to strict sandboxing and device homogeneity. However, we demonstrated that our approach can produce globally unique fingerprints for iOS devices from an installed app: around 67 bits of entropy for the iPhone 6S. Calibration fingerprints generated by a website are less unique (around 42 bits of entropy for the iPhone 6S), but they are orthogonal to existing fingerprinting techniques and together they are likely to form a globally unique fingerprint for iOS devices. Apple adopted our proposed mitigations in iOS 12.2 for apps (CVE-2019-8541). Apple recently removed all access to motion sensors from Mobile Safari by default.

We presented this work on 21st May at IEEE Symposium on Security and Privacy 2019. For more details, please visit the SensorID website and read our paper:

Jiexin Zhang, Alastair R. Beresford and Ian Sheret, SensorID: Sensor Calibration Fingerprinting for Smartphones, Proceedings of the 40th IEEE Symposium on Security and Privacy (S&P), 2019.

87% of Android devices insecure because manufacturers fail to provide security updates

We are presenting a paper at SPSM next week that shows that, on average over the last four years, 87% of Android devices are vulnerable to attack by malicious apps. This is because manufacturers have not provided regular security updates. Some manufacturers are much better than others however, and our study shows that devices built by LG and Motorola, as well as those devices shipped under the Google Nexus brand are much better than most. Users, corporate buyers and regulators can find further details on manufacturer performance at AndroidVulnerabilities.org

We used data collected by our Device Analyzer app, which is available from the Google Play Store. The app collects data from volunteers around the globe and we have used data from over 20,000 devices in our study. As always, we are keen to recruit more contributors! We combined Device Analyzer data with information we collected on critical vulnerabilities affecting Android. We used this to develop the FUM score which can be used to compare the security provided by different manufacturers. Each manufacturer is given a score out of 10 based on: f, the proportion of devices free from known critical vulnerabilities; u, the proportion of devices updated to the most recent version; and m, the mean number of vulnerabilities the manufacturer has not fixed on any device.

The problem with the lack of updates to Android devices is well known and recently Google and Samsung have committed to shipping security updates every month. Our hope is that by quantifying the problem we can help people when choosing a device and that this in turn will provide an incentive for other manufacturers and operators to deliver updates.

Google has done a good job at mitigating many of the risks, and we recommend users only install apps from Google’s Play Store since it performs additional safety checks on apps. Unfortunately Google can only do so much, and recent Android security problems have shown that this is not enough to protect users. Devices require updates from manufacturers, and the majority of devices aren’t getting them.

For further information, contact Daniel Thomas and Alastair Beresford via contact@androidvulnerabilities.org

Tor on Android

Andrew Rice and I ran a ten week internship programme for Cambridge undergraduates this summer. One of the project students, Connell Gauld, was tasked with the job of producing a version of Tor for the Android mobile phone platform which could be used on a standard handset.

Connell did a great job and on Friday we released TorProxy, a pure Java implementation of Tor based on OnionCoffee, and Shadow, a Web browser which uses TorProxy to permit anonymous browsing from your Android phone. Both applications are available on the Android Marketplace; remember to install TorProxy if you want to use Shadow.

The source code for both applications is released under GPL v2 and is available from our SVN repository on the project home page. There are also instructions on how to use TorProxy to send and receive data via Tor from your own Android application.