Everything you need to know about websites have new way to spy.
[ad_1]While each file system is sandboxed, meaning it’s isolated from other websites and from the device system itself, the JavaScript can measure the I/O interactions. Then, by running those interactions through a pretrained convolutional neural network—a system that uses deep learning to analyze text, audio, and images—the attacker can deduce various apps and websites open on the device.
“The attacker continuously measures SSD contention by performing random reads from a large OPFS file,” the researchers explained. “SSD contention caused by user activity causes measurable latency differences for these read operations. By training a convolutional neural network (CNN) on these traces, the attacker can fingerprint user activity on the host system by classifying new traces using the trained model.”
The technique has its limitations. First, the OPFS file must be extremely large—likely a gigabyte or more. That requirement means that attacks at scale would inevitably be detected by many users. Additionally, the OPFS file must be stored on the same SSD the visitor is using. This isn’t usually a problem for tracking open websites, since the OPFS file is stored in the browser’s default location. In the event apps are using a separate SSD drive for apps, those apps couldn’t be detected by FROST.
One of the best ways to prevent FROST attacks is to close tabs as soon as they’re no longer needed. More savvy users can monitor the creation and size of OPFS files allocated by unknown websites. The researchers proposed ways for browser makers to shut down the side channel. One such method is to limit the maximum size such files that are allowed. There are no indications FROST attacks have been performed in the wild.
The researchers performed the full Frost attack on an M2 Mac. On Linux, they showed that the underlying primitive (measuring SSD access latency traces from JavaScript) works, but didn’t run the full attack.
“However, since the performance of the primitive is similar between macOS and Linux, we expect similar performance for the full classification,” Hannes Weissteiner, one of the co-authors, wrote in an email. “In principle, it would be possible to train a model on any system activity that reliably generates SSD accesses.”
The researchers did not test Windows.
The paper linked above provides many more technical details. The research is scheduled to be presented at the DIMVA conference in July.
[ad_2]
Source link
More on websites have new way to spy
Stay tuned for updates on websites have new way to spy as the story develops. Related: Beyond Siri: Here are the practical AI features coming to your iPhone in iOS 27.
Websites have new way to spy: Key Details Explained
Websites have a new way to spy on visitors: analyzing their SSD activity — let’s break down what actually matters here. This one stands out because it touches the things buyers care about most: performance, features, and value for money. If you’re comparing options right now, it’s worth keeping on your shortlist.
Looking at the bigger picture, this fits into a wider trend where brands compete harder with every release cycle. Expect more details to surface as things develop, including confirmed specifications and pricing from official sources.
Should You Keep Following This?
If you follow mobile tech closely, the answer is yes. Developments like this could influence your next purchase decision, so it’s worth tracking. Bookmark this page — we’ll keep the coverage fresh as the story evolves.
Frequently Asked Questions
A technique where a website measures SSD I/O contention through JavaScript reads from a large OPFS file, then runs the traces through a trained convolutional neural network to fingerprint apps and websites open on the device.
The OPFS file must be extremely large, likely a gigabyte or more, making large-scale attacks detectable, and it must sit on the same SSD the visitor is using.
Close tabs as soon as they are no longer needed, and monitor the creation and size of OPFS files allocated by unknown websites.
No. There are no indications of real-world attacks. Researchers demonstrated the full attack on an M2 Mac and showed the underlying primitive works on Linux.
