Qinhong Jiang (Zhejiang University), Yanze Ren (Zhejiang University), Yan Long (University of Michigan), Chen Yan (Zhejiang University), Yumai Sun (University of Michigan), Xiaoyu Ji (Zhejiang University), Kevin Fu (Northeastern University), Wenyuan Xu (Zhejiang University)

Keyboards are the primary peripheral input devices for various critical computer application scenarios. This paper performs a security analysis of the keyboard sensing mechanisms and uncovers a new class of vulnerabilities that can be exploited to induce phantom keys---fake keystrokes injected into keyboards' analog circuits in a contactless way using electromagnetic interference (EMI). Besides normal keystrokes, such phantom keys also include keystrokes that cannot be achieved by human operators, such as rapidly injecting over 10,000 keys per minute and injecting hidden keys that do not exist on the physical keyboard. The underlying principles of phantom key injection consist in inducing false voltages on keyboard sensing GPIO pins through EMI coupled onto matrix circuits. We investigate the voltage and timing requirements of injection signals both theoretically and empirically to establish the theory of phantom key injection. To validate the threat of keyboard sensing vulnerabilities, we design GhostType that can cause denial-of-service of the keyboard and inject random keystrokes as well as certain targeted keystrokes of the adversary's choice. We have validated GhostType on 48 of 50 off-the-shelf keyboards/keypads from 20 brands including both membrane/mechanical structures and USB/Bluetooth protocols. Some example consequences of GhostType include completely blocking keyboard operations, crashing and turning off downstream computers, and deleting files on computers. Finally, we glean lessons from our investigations and propose countermeasures including EMI shielding, phantom key detection, and keystroke scanning signal improvement.

View More Papers

LibAFL QEMU: A Library for Fuzzing-oriented Emulation

Romain Malmain (EURECOM), Andrea Fioraldi (EURECOM), Aurelien Francillon (EURECOM)

Read More

Work-in-Progress: A Large-Scale Long-term Analysis of Online Fraud across...

Yi Han, Shujiang Wu, Mengmeng Li, Zixi Wang, and Pengfei Sun (F5)

Read More

Security Attacks to the Name Management Protocol in Vehicular...

Sharika Kumar (The Ohio State University), Imtiaz Karim, Elisa Bertino (Purdue University), Anish Arora (Ohio State University)

Read More

WIP: Modeling and Detecting Falsified Vehicle Trajectories Under Data...

Jun Ying, Yiheng Feng (Purdue University), Qi Alfred Chen (University of California, Irvine), Z. Morley Mao (University of Michigan and Google)

Read More