Turning GPU into an FM Radio: A Practical Data Exfiltration Framework from Air-gapped Systems

In the field of cybersecurity, it has been widely believed that air-gapped devices, disconnected from the Internet, offer strong protection against data breaches. However, recent research has challenged this assumption by demonstrating the feasibility of exfiltrating data from air-gapped devices using covert channels, such as modulating thermal, acoustic, or electromagnetic (EM) emanations. Existing approaches, however, face key limitations, including low bit rates, line-of-sight requirements, and susceptibility to EM shielding, limiting their practical deployments. To this end, we propose MagWhisper, a novel and practical data exfiltration framework that exploits GPU magnetic leakages for a covert channel. The non-radiative magnetic signals can penetrate various materials, including metal, enabling MagWhisper’s non-line-of-sight and shielded operation. We design a high-frequency frequency-shift keying modulation scheme over GPU magnetic signals, thus establishing a high-rate and robust channel. We further adopt a GPU-agnostic design to enhance MagWhisper’s generalizability. A proof-of-concept system is implemented to demonstrate MagWhisper’s feasibility. Our evaluation on three heterogeneous GPUs shows that MagWhisper achieves high bit rates exceeding 133 bps with a bit error rate (BER) lower than 1.2%. Furthermore, real-world case studies confirm that MagWhisper remains effective in non-line-of-sight scenarios and can even bypass EM shielding within a Faraday cage.