Affiliation: imec-COSIC, KU Leuven Kasteelpark Arenberg 10, B-3001 Leuven-Heverlee
Dismantling DST80-based Immobiliser Systems 📺
Car manufacturers deploy vehicle immobiliser systems in order to prevent car theft. However, in many cases the underlying cryptographic primitives used to authenticate a transponder are proprietary in nature and thus not open to public scrutiny. In this paper we publish the proprietary Texas Instruments DST80 cipher used in immobilisers of several manufacturers. Additionally, we expose serious flaws in immobiliser systems of major car manufacturers such as Toyota, Kia, Hyundai and Tesla. Specifically, by voltage glitching the firmware protection mechanisms of the microcontroller, we extracted the firmware from several immobiliser ECUs and reverse engineered the key diversification schemes employed within. We discovered that Kia and Hyundai immobiliser keys have only three bytes of entropy and that Toyota only relies on publicly readable information such as the transponder serial number and three constants to generate cryptographic keys. Furthermore, we present several practical attacks which can lead to recovering the full 80-bit cryptographic key in a matter of seconds or permanently disabling the transponder. Finally, even without key management or configuration issues, we demonstrate how an attacker can recover the cryptographic key using a profiled side-channel attack. We target the key loading procedure and investigate the practical applicability in the context of portability. Our work once again highlights the issues automotive vendors face in implementing cryptography securely.
Revisiting a Methodology for Efficient CNN Architectures in Profiling Attacks 📺
This work provides a critical review of the paper by Zaid et al. titled “Methodology for Efficient CNN Architectures in Profiling attacks”, which was published in TCHES Volume 2020, Issue 1. This work studies the design of CNN networks to perform side-channel analysis of multiple implementations of the AES for embedded devices. Based on the authors’ code and public data sets, we were able to cross-check their results and perform a thorough analysis. We correct multiple misconceptions by carefully inspecting different elements of the model architectures proposed by Zaid et al. First, by providing a better understanding on the internal workings of these models, we can trivially reduce their number of parameters on average by 52%, while maintaining a similar performance. Second, we demonstrate that the convolutional filter’s size is not strictly related to the amount of misalignment in the traces. Third, we show that increasing the filter size and the number of convolutions actually improves the performance of a network. Our work demonstrates once again that reproducibility and review are important pillars of academic research. Therefore, we provide the reader with an online Python notebook which allows to reproduce some of our experiments1 and additional example code is made available on Github.2
Fast, Furious and Insecure: Passive Keyless Entry and Start Systems in Modern Supercars 📺
The security of immobiliser and Remote Keyless Entry systems has been extensively studied over many years. Passive Keyless Entry and Start systems, which are currently deployed in luxury vehicles, have not received much attention besides relay attacks. In this work we fully reverse engineer a Passive Keyless Entry and Start system and perform a thorough analysis of its security.Our research reveals several security weaknesses. Specifically, we document the use of an inadequate proprietary cipher using 40-bit keys, the lack of mutual authentication in the challenge-response protocol, no firmware readout protection features enabled and the absence of security partitioning.In order to validate our findings, we implement a full proof of concept attack allowing us to clone a Tesla Model S key fob in a matter of seconds with low cost commercial off the shelf equipment. Our findings most likely apply to other manufacturers of luxury vehicles including McLaren, Karma and Triumph motorcycles as they all use the same system developed by Pektron.