Xinyi Xie (Shanghai Fudan Microelectronics Group Co., Ltd.), Kun Jiang (Shanghai Fudan Microelectronics Group Co., Ltd.), Rui Dai (Shanghai Fudan Microelectronics Group Co., Ltd.), Jun Lu (Shanghai Fudan Microelectronics Group Co., Ltd.), Lihui Wang (Shanghai Fudan Microelectronics Group Co., Ltd.), Qing Li (State Key Laboratory of ASIC & System, Fudan University), Jun Yu (State Key Laboratory of ASIC & System, Fudan University)

Tesla Model 3 has equipped with Phone Keys and Key Cards in addition to traditional key fobs for better driving experiences. These new features allow a driver to enter and start the vehicle without using a mechanical key through a wireless authentication process between the vehicle and the key. Unlike the requirements of swiping against the car for Key Cards, the Tesla mobile app’s Phone Key feature can unlock a Model 3 while your smartphone is still in a pocket or bag.

In this paper, we performed a detailed security analysis aiming at Tesla keys, especially for Key Cards and Phone Keys. Starting with reverse engineering the mobile application and sniffing the communication data, we reestablished pairing and authentication protocols and analyzed their potential issues. Missing the certificate verification allows an unofficial Key Card to work as an official one. Using these third-party products may lead to serious security problems. Also, the weaknesses of the current protocol lead to a man-in-the-middle (MitM) attack through a Bluetooth channel. The MitM attack is an improved relay attack breaking the security of the authentication procedures for Phone Keys. We also developed an App named TESmLA installed on customized Android devices to complete the proof-of-concept. The attackers can break into Tesla Model 3 and drive it away without the awareness of the car owner. Our results bring into question the security of Passive Keyless Entry and Start (PKES) and Bluetooth implementations in security-critical applications. To mitigate the security problems, we discussed the corresponding countermeasures and feasible secure scheme in the future.

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Tian Dong (Shanghai Jiao Tong University), Shaofeng Li (Shanghai Jiao Tong University), Guoxing Chen (Shanghai Jiao Tong University), Minhui Xue (CSIRO's Data61), Haojin Zhu (Shanghai Jiao Tong University), Zhen Liu (Shanghai Jiao Tong University)

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Wei Zhou, Zhouqi Jiang (School of Cyber Science and Engineering, Huazhong University of Science and Technology), Le Guan (School of Computing, University of Georgia)

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Takami Sato (University of California, Irvine), Sri Hrushikesh Varma Bhupathiraju (University of Florida), Michael Clifford (Toyota InfoTech Labs), Takeshi Sugawara (The University of Electro-Communications), Qi Alfred Chen (University of California, Irvine), Sara Rampazzi (University of Florida)

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