Hackers can use the graphics processing unit to spy on web activity, steal passwords, and break into cloud-based applications

"In the second attack, the authors extracted user passwords. Each time the user types a character, the whole password textbox is uploaded to GPU as a texture to be rendered. Monitoring the interval time of consecutive memory allocation events leaked the number of password characters and inter-keystroke timing, well-established techniques for learning passwords."

"The third attack targets a computational application in the cloud. The attacker launches a malicious computational workload on the GPU which operates alongside the victim’s application. Depending on neural network parameters, the intensity and pattern of contention on the cache, memory and functional units differ over time, creating measurable leakage. The attacker uses machine learning-based classification on performance counter traces to extract the victim’s secret neural network structure, such as number of neurons in a specific layer of a deep neural network."

"In the future the group plans to test the feasibility of GPU side channel attacks on Android phones."

http://www.cs.ucr.edu/~zhiyunq/pub/ccs18_gpu_side_channel.pdf