Drone Security and the Mysterious Case of DJI's DroneID
Nico Schiller, Merlin Chlosta, Moritz Schloegel, Nils Bars, Thorsten Eisenhofer, Tobias Scharnowski, Felix Domke, Lea Schönherr, Thorsten Holz
摘要
Consumer drones enable high-class aerial video photography, promise to reform the logistics industry, and are already used for humanitarian rescue operations and during armed conflicts. Contrasting their widespread adoption and high popularity, the low entry barrier for air mobility---a traditionally heavily regulated sector---poses many risks to safety, security, and privacy. Malicious parties could, for example, (mis-)use drones for surveillance, transportation of illegal goods, or cause economic damage by intruding the closed airspace above airports. To prevent harm, drone manufacturers employ several countermeasures to enforce safe and secure use of drones, e.g., they impose software limits regarding speed and altitude, or use geofencing to implement no-fly zones around airports or prisons. Complementing traditional countermeasures, drones from the market leader DJI implement a tracking protocol called DroneID, which is designed to transmit the position of both the drone and its operator to authorized entities such as law enforcement or operators of critical infrastructures.
In this paper, we analyze security and privacy claims for drones, focusing on the leading manufacturer DJI with a market share of 94%. We first systemize the drone attack surface and investigate an attacker capable of eavesdropping on the drone's over-the-air data traffic. Based on reverse engineering of DJI firmware, we design and implement a decoder for DJI's proprietary tracking protocol DroneID, using only cheap COTS hardware. We show that the transmitted data is not encrypted, but accessible to anyone, compromising the drone operator's privacy. Second, we conduct a comprehensive analysis of drone security: Using a combination of reverse engineering, a novel fuzzing approach tailored to DJI's communication protocol, and hardware analysis, we uncover several critical flaws in drone firmware that allow attackers to gain elevated privileges on two different DJI drones and their remote control. Such root access paves the way to disable or bypass countermeasures and abuse drones. In total, we found 16 vulnerabilities, ranging from denial of service to arbitrary code execution. 14 of these bugs can be triggered remotely via the operator's smartphone, allowing us to crash the drone mid-flight.
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引用它的顶会 Paper6
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- FlyTrap: Physical Distance-Pulling Attack Towards Camera-based Autonomous Target Tracking SystemsShaoyuan Xie, Mohamad Habib Fakih, Junchi Lu, Fayzah Alshammari 等NDSS 2026 · 被引用 5 次
- RouthSearch: Inferring PID Parameter Specification for Flight Control Program by Coordinate SearchSiao Wang, Zhen Dong, Hui Li, Liwei Shen 等ISSTA 2025 · 被引用 1 次
- RSFuzz: A Robustness-Guided Swarm Fuzzing Framework Based on Behavioral ConstraintsRuoyu Zhou, Zhiwei Zhang, Haocheng Han, Xiaodong Zhang 等ASE 2025
- AidFuzzer: Adaptive Interrupt-Driven Firmware Fuzzing via Run-Time State RecognitionJianqiang Wang, Qinying Wang, Tobias Scharnowski, Li Shi 等USENIX Security 2025
它引用的顶会 Paper16
- Coverage-based Greybox Fuzzing as Markov ChainMarcel Böhme, Van-Thuan Pham, Abhik RoychoudhuryCCS 2016 · 被引用 1,026 次
- Driller: Augmenting Fuzzing Through Selective Symbolic ExecutionNick Stephens, John Grosen, Christopher Salls, Andrew Dutcher 等NDSS 2016 · 被引用 1,021 次
- Directed Greybox FuzzingMarcel Böhme, Van-Thuan Pham, Manh-Dung Nguyen, Abhik RoychoudhuryCCS 2017 · 被引用 836 次
- Angora: Efficient Fuzzing by Principled SearchPeng Chen, Hao ChenS&P 2018 · 被引用 616 次
- QSYM : A Practical Concolic Execution Engine Tailored for Hybrid FuzzingInsu Yun, Sangho Lee, Meng Xu, Yeongjin Jang 等USENIX Security 2018 · 被引用 537 次
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