GPUs are vulnerable to side-channel attacks

Computer scientists at the University of California at Riverside have found that GPUs are vulnerable to side-channel attacks, the same kinds of exploits that have impacted Intel and AMD CPUs.

Two professors and two students, one a computer science doctoral student and a post-doctoral researcher, reverse-engineered a Nvidia GPU to demonstrate three attacks on both graphics and computational stacks, as well as across them. The researchers believe these are the first reported side-channel attacks on GPUs.

A side-channel attack is one where the attacker uses how a technology operates, in this case a GPU, rather than a bug or flaw in the code. It takes advantage of how the processor is designed and exploits it in ways the designers hadn’t thought of.

In this case, it exploits the user counters in the GPU, which are used for performance tracking and are available in user mode, so anyone has access to them.

3 types of GPU attacks

All three attacks require the victim to download a malicious program to spy on the victim’s computer.

The first attack tracks user activity on the web, since GPUs are used to render graphics in browsers. A malicious app uses OpenGL to create a spy program to infer the behavior of the browser as it uses the GPU. The spy program can reliably obtain all allocation events of each website visited to see what the user has been doing on the web and possibly extract login credentials.