Hot Pixels: Frequency, Power, and Temperature Attacks on GPUs and ARM SoCs

TL;DR

This paper reveals that modern SoCs and GPUs are vulnerable to hybrid side-channel attacks exploiting power, temperature, and frequency sensors, enabling data leakage and fingerprinting even with countermeasures active.

Contribution

It introduces new hybrid side-channel attack techniques on Arm SoCs and GPUs using internal sensor data, demonstrating real-world exploits like pixel stealing and website fingerprinting.

Findings

Sensor data correlates with executed instructions and processed data

JavaScript-based attacks can bypass side-channel countermeasures

Attacks enable website fingerprinting without elevated privileges

Abstract

The drive to create thinner, lighter, and more energy efficient devices has resulted in modern SoCs being forced to balance a delicate tradeoff between power consumption, heat dissipation, and execution speed (i.e., frequency). While beneficial, these DVFS mechanisms have also resulted in software-visible hybrid side-channels, which use software to probe analog properties of computing devices. Such hybrid attacks are an emerging threat that can bypass countermeasures for traditional microarchitectural side-channel attacks. Given the rise in popularity of both Arm SoCs and GPUs, in this paper we investigate the susceptibility of these devices to information leakage via power, temperature and frequency, as measured via internal sensors. We demonstrate that the sensor data observed correlates with both instructions executed and data processed, allowing us to mount software-visible hybrid side-channel attacks on these devices. To demonstrate the real-world impact of this issue, we present JavaScript-based pixel stealing and history sniffing attacks on Chrome and Safari, with all side channel countermeasures enabled. Finally, we also show website fingerprinting attacks, without any elevated privileges.