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Christof Paar

Publications and source records attributed to Christof Paar.

At least 19 recordsLinked to original sources

Designing a Hardware Reverse Engineering Course: Lessons from Eight Years in a Rapidly Evolving Tech Domain

Integrated Circuits (ICs) are omnipresent, yet their globalized manufacturing process remains vulnerable to supply chain threats. Hardware Reverse Engineering (HRE) is essential for detecting such threats and re-establishing trust; however domain experts remain scarce due to a lack of educational programs. To contribute educational insights in this critical and rapidly evolving technology domain, we present our HRE course focusing on digital circuit analysis and digital circuit extraction from ICs. The course targets junior-level undergraduates at a major European research university. The curriculum has been refined over nine iterations (2017-2025), with several alumni subsequently pursuing careers in the HRE field. By reflecting on the evolution of the course organization, content, and assignments, we derive key lessons learned. We further distill these insights into actionable design priorities for educators developing courses in rapidly evolving technological domains, emphasizing iterative growth and sustainable workload management for both students and instructors.

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PINsight: Systematic Threat Assessment of Cross-Domain Wi-Fi-based PIN Inference

Wi-Fi signals can be repurposed as radar-like sensors, exposing a side channel for inferring sensitive information. A particularly concerning example is PIN inference, where an attacker recovers typed digits by mapping Wi-Fi channel estimations back to individual keystrokes. While effective in a fixed setting, such attacks typically fail once physical conditions change, e.g., a new room, a different person, or a repositioned device. The state-of-the-art attack WiKI-Eve tackles this domain generalization problem with deep learning, reporting high PIN inference accuracy regardless of physical conditions - suggesting a significant real-world threat. However, the actual threat potential remains unclear: isolated success cases cannot substantiate general performance, and no systematic method exists to evaluate attacks under unseen conditions. We close this gap with PINsight, a methodology that separates the effects of changing physical conditions from those of PIN typing itself, enabling a rigorous threat assessment that attributes performance degradation to specific condition changes. PINsight leverages a robotic typing platform that produces highly repeatable keystrokes under systematically varied conditions, such as room and device placement. Using this setup, we record over one million typed digits across over one thousand controlled combinations of physical conditions, yielding the first benchmark for cross-domain generalization in Wi-Fi PIN inference, which we release publicly. On this benchmark, we revisit WiKI-Eve, address several reproducibility gaps in its evaluation, and construct a stronger variant as an attack baseline. We find that attacks generalize reliably across background changes but degrade substantially once devices are repositioned. We conclude that domain generalization is partially feasible, but prior results overstate the real-world threat.

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Hardware Trojans from Invisible Inversions: On the Trojanizability of Standard Cell Libraries

At S&P 2023, Puschner et al. made a valuable dataset for hardware Trojan detection research publicly available. It contains a complete set of Scanning Electron Microscope (SEM) images of four different digital Integrated Circuits (ICs) fabricated at progressively smaller semiconductor technology nodes. Puschner et al. reported preliminary evidence that feature sizes affect Trojan detection performance, but they were unable to disentangle effects caused by insertion strategies or by degrading image quality from those intrinsic to the underlying standard cell libraries. Distinguishing those causes, however, is crucial to understand whether improved tooling (e.g., higher resolution imaging equipment) can remove the observed technology bias, or whether susceptibility to stealthy hardware Trojans is indeed an inherent property of a cell library. In this work, we dive deep into the S&P 2023 dataset to answer these questions. We devise alternative metrics to those of Puschner et al., in order to assess and compare the potential susceptibility of standard cell libraries more meaningfully. We find clear differences between the evaluated process nodes. However, in all cases we identify cells that implement distinct logic functions yet are visually indistinguishable in backside SEM images. We exploit this property to construct stealthy, standard-cell-based hardware Trojans and present a concrete case study: a privilege-escalation backdoor in an Ibex RISCV core. Our results demonstrate that cell libraries can - and should - be evaluated for their potential "Trojanizability", and we recommend practical defenses.

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SoK: From Silicon to Netlist and Beyond $-$ Two Decades of Hardware Reverse Engineering Research

Hardware serves as the root of trust in modern computing systems, making Hardware Reverse Engineering (HRE) essential for security assurance$-$from design verification and supply-chain integrity to vulnerability discovery. We scope HRE to netlist recovery and its subsequent analysis, spanning the three subdomains of Integrated Circuit (IC), Field-Programmable Gate Array (FPGA), and netlist reverse engineering. These subdomains differ in their methodologies, but share core processes and are shaped by common requirements and legal constraints of the same stakeholders. Despite an increasing number of publications, the field lacks a systematic understanding of how these obstacles have stunted the research ecosystem. To address this gap, we present the first large-scale Systematization of Knowledge (SoK) of the HRE workflow, analyzing 187 peer-reviewed publications. Across all three subdomains, we identify eleven concrete technical challenges$-$from a widening gap between academic research and modern semiconductor technology nodes to overly idealized assumptions in netlist analysis$-$and propose actionable directions for each. A retrospective evaluation of all 30 published artifacts reveals that key results could be reproduced for only seven, a mere 4 % of all 187 papers in our corpus, confirming a systemic reproducibility crisis. We trace both the technical and reproducibility challenges to three structural barriers that recur across all subdomains: scarce reusable artifacts, missing benchmarks, and unresolved legal constraints on data sharing and collaboration. Based on these findings, we derive stakeholder-specific recommendations for academia, industry, and government to transition HRE from isolated research silos toward a collaborative discipline capable of assuring increasingly complex, global hardware supply chains.

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SAMSEM -- A Generic and Scalable Approach for IC Metal Line Segmentation

In light of globalized hardware supply chains, the assurance of hardware components has gained significant interest, particularly in cryptographic applications and high-stakes scenarios. Identifying metal lines on scanning electron microscope (SEM) images of integrated circuits (ICs) is one essential step in verifying the absence of malicious circuitry in chips manufactured in untrusted environments. Due to varying manufacturing processes and technologies, such verification usually requires tuning parameters and algorithms for each target IC. Often, a machine learning model trained on images of one IC fails to accurately detect metal lines on other ICs. To address this challenge, we create SAMSEM by adapting Meta's Segment Anything Model 2 (SAM2) to the domain of IC metal line segmentation. Specifically, we develop a multi-scale segmentation approach that can handle SEM images of varying sizes, resolutions, and magnifications. Furthermore, we deploy a topology-based loss alongside pixel-based losses to focus our segmentation on electrical connectivity rather than pixel-level accuracy. Based on a hyperparameter optimization, we then fine-tune the SAM2 model to obtain a model that generalizes across different technology nodes, manufacturing materials, sample preparation methods, and SEM imaging technologies. To this end, we leverage an unprecedented dataset of SEM images obtained from 48 metal layers across 14 different ICs. When fine-tuned on seven ICs, SAMSEM achieves an error rate as low as 0.72% when evaluated on other images from the same ICs. For the remaining seven unseen ICs, it still achieves error rates as low as 5.53%. Finally, when fine-tuned on all 14 ICs, we observe an error rate of 0.62%. Hence, SAMSEM proves to be a reliable tool that significantly advances the frontier in metal line segmentation, a key challenge in post-manufacturing IC verification.

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Talking to the Airgap: Exploiting Radio-Less Embedded Devices as Radio Receivers

Physical isolation from external networks - an airgap - aims to minimize exposure to remote attacks. Yet capable adversaries still achieve code execution on air-gapped systems, and prior work has shown that they can then wirelessly exfiltrate data via unintended emissions. In this work, we demonstrate the reverse direction: malicious code on an embedded device enables wireless infiltration of air-gapped systems, granting attackers command-and-control over compromised targets. Leveraging physical effects previously studied in the context of electromagnetic interference (EMI), we show that parasitic radio frequency (RF) sensitivity in printed circuit board (PCB) traces and on-chip analog-to-digital converters (ADCs) turns commodity embedded devices into inadvertent radio receivers. Unlike prior infiltration techniques, our approach requires no dedicated sensors (e.g., microphones, LEDs, or temperature sensors) and works in non-line-of-sight scenarios. In our evaluation, an ordinary microcontroller evaluation board reliably recovers communication signals from tens of meters at data rates of up to 100 kbps. Applying a systematic methodology to discover such device-intrinsic RF sensitivity, we evaluate twelve commercial embedded devices and two custom prototypes, finding that all exhibit reception capabilities in the 300-1000 MHz range. Our findings challenge the assumption that embedded devices without radios lack an inbound radio paths and call for air-gap threat models that account for both emission-based leakage and unintended reception.

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HAL -- An Open-Source Framework for Gate-Level Netlist Analysis

HAL is an open-source framework for gate-level netlist analysis, an integral step in hardware reverse engineering. It provides analysts with an interactive GUI, an extensible plugin system, and APIs in both C++ and Python for rapid prototyping and automation. In addition, HAL ships with plugins for word-level modularization, cryptographic analysis, simulation, and graph-based exploration. Since its release in 2019, HAL has become widely adopted in academia, industry, government, and teaching. It underpins at least 23 academic publications, is taught in hands-on trainings, conference tutorials, and university classes, and has collected over 680 stars and 86 forks on GitHub. By enabling accessible and reproducible hardware reverse engineering research, HAL has significantly advanced the field and the understanding of real-world capabilities and threats.

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The Battle of Metasurfaces: Understanding Security in Smart Radio Environments

Metasurfaces, or Reconfigurable Intelligent Surfaces (RISs), have emerged as a transformative technology for next-generation wireless systems, enabling digitally controlled manipulation of electromagnetic wave propagation. By turning the traditionally passive radio environment into a smart, programmable medium, metasurfaces promise advances in communication and sensing. However, metasurfaces also present a new security frontier: both attackers and defenders can exploit them to alter wireless propagation for their own advantage. While prior security research has primarily explored unilateral metasurface applications - empowering either attackers or defenders - this work investigates symmetric scenarios, where both sides possess comparable metasurface capabilities. Using both theoretical modeling and real-world experiments, we analyze how competing metasurfaces interact for diverse objectives, including signal power and sensing perception. Thereby, we present the first systematic study of context-agnostic metasurface-to-metasurface interactions and their implications for wireless security. Our results reveal that the outcome of metasurface "battles" depends on an interplay of timing, placement, algorithmic strategy, and hardware scale. Across multiple case studies in Wi-Fi environments, including wireless jamming, channel obfuscation for sensing and communication, and sensing spoofing, we demonstrate that opposing metasurfaces can substantially or fully negate each other's effects. By undermining previously proposed security and privacy schemes, our findings open new opportunities for designing resilient and high-assurance physical-layer systems in smart radio environments.

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Anti-Tamper Radio meets Reconfigurable Intelligent Surface for System-Level Tamper Detection

Many computing systems need to be protected against physical attacks using active tamper detection based on sensors. One technical solution is to employ an ATR (Anti-Tamper Radio) approach, analyzing the radio wave propagation effects within a protected device to detect unauthorized physical alterations. However, ATR systems face key challenges in terms of susceptibility to signal manipulation attacks, limited reliability due to environmental noise, and regulatory constraints from wide bandwidth usage. In this work, we propose and experimentally evaluate an ATR system complemented by an RIS to dynamically reconfigure the wireless propagation environment. We show that this approach can enhance resistance against signal manipulation attacks, reduce bandwidth requirements from several~GHz down to as low as 20 MHz, and improve robustness to environmental disturbances such as internal fan movements. Our work demonstrates that RIS integration can strengthen the ATR performance to enhance security, sensitivity, and robustness, recognizing the potential of smart radio environments for ATR-based tamper detection

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"Make the Voodoo Box Go Bleep Bloop:" Exploring End Users' Understanding and Information Needs Regarding Microchips

Microchips are fundamental components of modern electronic devices, yet they remain opaque to the users who rely on them daily. This opacity, compounded by the complexity of global supply chains and the concealment of proprietary information, raises significant security, trust, and accountability issues. We investigate end users' understanding of microchips, exploring their perceptions of the societal implications and information needs regarding these essential technologies. Through an online survey with 250 participants, we found that while our participants were aware of some microchip applications, they lacked awareness of the broader security, societal, and economic implications. While our participants unanimously desired more information on microchips, their specific information needs were shaped by various factors such as the microchip's application environment and one's affinity for technology interaction. Our findings underscore the necessity for improving end users' awareness and understanding of microchips, and we provide possible directions to pursue this end.

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Key Exchange in the Quantum Era: Evaluating a Hybrid System of Public-Key Cryptography and Physical-Layer Security

Today's information society relies on cryptography to achieve security goals such as confidentiality, integrity, authentication, and non-repudiation for digital communications. Here, public-key cryptosystems play a pivotal role to share encryption keys and create digital signatures. However, quantum computers threaten the security of traditional public-key cryptosystems as they can tame computational problems underlying the schemes, i.e., discrete logarithm and integer factorization. The prospective arrival of capable-enough quantum computers already threatens today's secret communication in terms of their long-term secrecy when stored to be later decrypted. Therefore, researchers strive to develop and deploy alternative schemes. In this work, evaluate a key exchange protocol based on combining public-key schemes with physical-layer security, anticipating the prospect of quantum attacks. If powerful quantum attackers cannot immediately obtain private keys, legitimate parties have a window of short-term secrecy to perform a physical-layer jamming key exchange (JKE) to establish a long-term shared secret. Thereby, the protocol constraints the computation time available to the attacker to break the employed public-key cryptography. In this paper, we outline the protocol, discuss its security, and point out challenges to be resolved.

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Patching FPGAs: The Security Implications of Bitstream Modifications

Field Programmable Gate Arrays (FPGAs) are known for their reprogrammability that allows for post-manufacture circuitry changes. Nowadays, they are integral to a variety of systems including high-security applications such as aerospace and military systems. However, this reprogrammability also introduces significant security challenges, as bitstream manipulation can directly alter hardware circuits. Malicious manipulations may lead to leakage of secret data and the implementation of hardware Trojans. In this paper, we present a comprehensive framework for manipulating bitstreams with minimal reverse engineering, thereby exposing the potential risks associated with inadequate bitstream protection. Our methodology does not require a complete understanding of proprietary bitstream formats or a fully reverse-engineered target design. Instead, it enables precise modifications by inserting pre-synthesized circuits into existing bitstreams. This novel approach is demonstrated through a semi-automated framework consisting of five steps: (1) partial bitstream reverse engineering, (2) designing the modification, (3) placing and (4) routing the modification into the existing circuit, and (5) merging of the modification with the original bitstream. We validate our framework through four practical case studies on the OpenTitan design synthesized for Xilinx 7-Series FPGAs. While current protections such as bitstream authentication and encryption often fall short, our work highlights and discusses the urgency of developing effective countermeasures. We recommend using FPGAs as trust anchors only when bitstream manipulation attacks can be reliably excluded.

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An Evidence-Based Curriculum Initiative for Hardware Reverse Engineering Education

The increasing importance of supply chain security for digital devices -- from consumer electronics to critical infrastructure -- has created a high demand for skilled cybersecurity experts. These experts use Hardware Reverse Engineering (HRE) as a crucial technique to ensure trust in digital semiconductors. Recently, the US and EU have provided substantial funding to educate this cybersecurity-ready semiconductor workforce, but success depends on the widespread availability of academic training programs. In this paper, we investigate the current state of education in hardware security and HRE to identify efficient approaches for establishing effective HRE training programs. Through a systematic literature review, we uncover 13 relevant courses, including eight with accompanying academic publications. We identify common topics, threat models, key pedagogical features, and course evaluation methods. We find that most hardware security courses do not prioritize HRE, making HRE training scarce. While the predominant course structure of lectures paired with hands-on projects appears to be largely effective, we observe a lack of standardized evaluation methods and limited reliability of student self-assessment surveys. Our results suggest several possible improvements to HRE education and offer recommendations for developing new training courses. We advocate for the integration of HRE education into curriculum guidelines to meet the growing societal and industry demand for HRE experts.

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I see an IC: A Mixed-Methods Approach to Study Human Problem-Solving Processes in Hardware Reverse Engineering

Trust in digital systems depends on secure hardware, often assured through Hardware Reverse Engineering (HRE). This work develops methods for investigating human problem-solving processes in HRE, an underexplored yet critical aspect. Since reverse engineers rely heavily on visual information, eye tracking holds promise for studying their cognitive processes. To gain further insights, we additionally employ verbal thought protocols during and immediately after HRE tasks: Concurrent and Retrospective Think Aloud. We evaluate the combination of eye tracking and Think Aloud with 41 participants in an HRE simulation. Eye tracking accurately identifies fixations on individual circuit elements and highlights critical components. Based on two use cases, we demonstrate that eye tracking and Think Aloud can complement each other to improve data quality. Our methodological insights can inform future studies in HRE, a specific setting of human-computer interaction, and in other problem-solving settings involving misleading or missing information.

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Spatial-Domain Wireless Jamming with Reconfigurable Intelligent Surfaces

Wireless communication infrastructure is a cornerstone of modern digital society, yet it remains vulnerable to the persistent threat of wireless jamming. Attackers can easily create radio interference to overshadow legitimate signals, leading to denial of service. The broadcast nature of radio signal propagation makes such attacks possible in the first place, but at the same time poses a challenge for the attacker: The jamming signal does not only reach the victim device but also other neighboring devices, preventing precise attack targeting. In this work, we solve this challenge by leveraging the emerging RIS technology, for the first time, for precise delivery of jamming signals. In particular, we propose a novel approach that allows for environment-adaptive spatial control of wireless jamming signals, granting a new degree of freedom to perform jamming attacks. We explore this novel method with extensive experimentation and demonstrate that our approach can disable the wireless communication of one or multiple victim devices while leaving neighboring devices unaffected. Notably, our method extends to challenging scenarios where wireless devices are very close to each other: We demonstrate complete denial-of-service of a Wi-Fi device while a second device located at a distance as close as 5 mm remains unaffected, sustaining wireless communication at a data rate of 25 Mbit/s. Lastly, we conclude by proposing potential countermeasures to thwart RIS-based spatial domain wireless jamming attacks.

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JustSTART: How to Find an RSA Authentication Bypass on Xilinx UltraScale(+) with Fuzzing

Fuzzing is a well-established technique in the software domain to uncover bugs and vulnerabilities. Yet, applications of fuzzing for security vulnerabilities in hardware systems are scarce, as principal reasons are requirements for design information access (HDL source code). Moreover, observation of internal hardware state during runtime is typically an ineffective information source, as its documentation is often not publicly available. In addition, such observation during runtime is also inefficient due to bandwidth-limited analysis interfaces (JTAG, and minimal introspection of internal modules). In this work, we investigate fuzzing for 7-Series and UltraScale(+) FPGA configuration engines, the control plane governing the (secure) bitstream configuration within the FPGA. Our goal is to examine the effectiveness of fuzzing to analyze and document the opaque inner workings of FPGA configuration engines, with a primary emphasis on identifying security vulnerabilities. Using only the publicly available chip and dispersed documentation, we first design and implement ConFuzz, an advanced FPGA configuration engine fuzzing and rapid prototyping framework. Based on our detailed understanding of the bitstream file format, we then systematically define 3 novel key fuzzing strategies for Xilinx configuration engines. Moreover, our strategies are executed through mutational structure-aware fuzzers and incorporate various novel custom-tailored, FPGA-specific optimizations. Our evaluation reveals previously undocumented behavior within the configuration engine, including critical findings such as system crashes leading to unresponsive states of the FPGA. In addition, our investigations not only lead to the rediscovery of the starbleed attack but also uncover JustSTART (CVE-2023-20570), capable of circumventing RSA authentication for Xilinx UltraScale(+). Note that we also discuss countermeasures.

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Stealing Maggie's Secrets -- On the Challenges of IP Theft Through FPGA Reverse Engineering

Intellectual Property (IP) theft is a cause of major financial and reputational damage, reportedly in the range of hundreds of billions of dollars annually in the U.S. alone. Field Programmable Gate Arrays (FPGAs) are particularly exposed to IP theft, because their configuration file contains the IP in a proprietary format that can be mapped to a gate-level netlist with moderate effort. Despite this threat, the scientific understanding of this issue lacks behind reality, thereby preventing an in-depth assessment of IP theft from FPGAs in academia. We address this discrepancy through a real-world case study on a Lattice iCE40 FPGA found inside iPhone 7. Apple refers to this FPGA as Maggie. By reverse engineering the proprietary signal-processing algorithm implemented on Maggie, we generate novel insights into the actual efforts required to commit FPGA IP theft and the challenges an attacker faces on the way. Informed by our case study, we then introduce generalized netlist reverse engineering techniques that drastically reduce the required manual effort and are applicable across a diverse spectrum of FPGA implementations and architectures. We evaluate these techniques on six benchmarks that are representative of different FPGA applications and have been synthesized for Xilinx and Lattice FPGAs, as well as in an end-to-end white-box case study. Finally, we provide a comprehensive open-source tool suite of netlist reverse engineering techniques to foster future research, enable the community to perform realistic threat assessments, and facilitate the evaluation of novel countermeasures.

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REVERSIM: An Open-Source Environment for the Controlled Study of Human Aspects in Hardware Reverse Engineering

Hardware Reverse Engineering (HRE) is a technique for analyzing integrated circuits. Experts employ HRE for security-critical tasks, like detecting Trojans or intellectual property violations, relying not only on their experience and customized tools but also on their cognitive abilities. In this work, we introduce ReverSim, a software environment that models key HRE subprocesses and integrates standardized cognitive tests. ReverSim enables quantitative studies with easier-to-recruit non-experts to uncover cognitive factors relevant to HRE. We empirically evaluated ReverSim in three studies. Semi-structured interviews with 14 HRE professionals confirmed its comparability to real-world HRE processes. Two online user studies with 170 novices and intermediates revealed effective differentiation of participant performance across a spectrum of difficulties, and correlations between participants' cognitive processing speed and task performance. ReverSim is available as open-source software, providing a robust platform for controlled experiments to assess cognitive processes in HRE, potentially opening new avenues for hardware protection.

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