# Password-Stealing without Hacking: Wi-Fi Enabled Practical Keystroke Eavesdropping

arXiv: https://arxiv.org/abs/2309.03492 · HTML: https://mlsanity.com/paper/2309.03492/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Sep 2023.

## Built on by (most cited first, 4 of 4)

- [Multi-Pair Temporal Sentence Grounding via Multi-Thread Knowledge Transfer Network](https://mlsanity.com/paper/2412.15678/) (2024)
- [Towards Battery-Free Wireless Sensing via Radio-Frequency Energy Harvesting](https://mlsanity.com/paper/2409.00086/) (2024)
- [Cross-Domain Multi-Person Human Activity Recognition via Near-Field Wi-Fi Sensing](https://mlsanity.com/paper/2510.17816/) (2025)
- [Stochastic Modeling of Human-Machine Authentication Channels under Partial Information Leakage](https://mlsanity.com/paper/2605.02102/) (2026)

## Abstract (arXiv)

The contact-free sensing nature of Wi-Fi has been leveraged to achieve privacy breaches, yet existing attacks relying on Wi-Fi CSI (channel state information) demand hacking Wi-Fi hardware to obtain desired CSIs. Since such hacking has proven prohibitively hard due to compact hardware, its feasibility in keeping up with fast-developing Wi-Fi technology becomes very questionable. To this end, we propose WiKI-Eve to eavesdrop keystrokes on smartphones without the need for hacking. WiKI-Eve exploits a new feature, BFI (beamforming feedback information), offered by latest Wi-Fi hardware: since BFI is transmitted from a smartphone to an AP in clear-text, it can be overheard (hence eavesdropped) by any other Wi-Fi devices switching to monitor mode. As existing keystroke inference methods offer very limited generalizability, WiKI-Eve further innovates in an adversarial learning scheme to enable its inference generalizable towards unseen scenarios. We implement WiKI-Eve and conduct extensive evaluation on it; the results demonstrate that WiKI-Eve achieves 88.9% inference accuracy for individual keystrokes and up to 65.8% top-10 accuracy for stealing passwords of mobile applications (e.g., WeChat).