Multi-tenancy schemes for quantum computing hardware are vulnerable to fault injection attacks through crosstalk effects. Research studies have experimentally demonstrated the change in output probabilities of victim circuits where the victim and the adversary share the same quantum hardware. To detect adversary circuits, this paper proposes compile time and simulation based protocols to scan quantum computer programs for malicious code patterns. In the compile time approach, with the help of databases of known malicious patterns, the number of gates and the repeating patterns in the code structures are tracked and validated for malicious intent. In the simulation based approach, Idle Tomography (IDT) using pyGSTi software framework is employed for crosstalk error rate extraction. Hamiltonian and Stochastic errors of relevant qubit pairs in accordance with the quantum hardware’s connectivity mapping are analyzed for the detection of unrecognized malicious adversary patterns. Both the protocols output metrics and error rates information that can be used as a "confidence ruler" over a concerned quantum hardware. These protocols safeguard honest quantum circuit parties from possible interference and resulting tampered computational outcomes brought about by adversary parties.
Multi-tenancy schemes for quantum computing hardware are vulnerable to fault injection attacks through crosstalk effects. Research studies have experimentally demonstrated the change in output probabilities of victim circuits where the victim and the adversary share the same quantum hardware. To detect adversary circuits, this paper proposes compile time and simulation based protocols to scan quantum computer programs for malicious code patterns. In the compile time approach, with the help of databases of known malicious patterns, the number of gates and the repeating patterns in the code structures are tracked and validated for malicious intent. In the simulation based approach, Idle Tomography (IDT) using pyGSTi software framework is employed for crosstalk error rate extraction. Hamiltonian and Stochastic errors of relevant qubit pairs in accordance with the quantum hardware’s connectivity mapping are analyzed for the detection of unrecognized malicious adversary patterns. Both the protocols output metrics and error rates information that can be used as a "confidence ruler" over a concerned quantum hardware. These protocols safeguard honest quantum circuit parties from possible interference and resulting tampered computational outcomes brought about by adversary parties.
Researchers are today exploring models for cloud-based usage of quantum computers where multi-tenancy can be used to share quantum computer hard-ware among multiple users. Multi-tenancy has a promise of allowing better utilization of the quantum computer hardware, but also opens up the quantum computer to new types of security attacks. As this and other recent research shows, it is possible to perform a fault injection attack using crosstalk on quantum computers when a victim and attacker circuits are instantiated as co-tenants on the same quantum computer. To ensure such attacks do not happen, this paper proposes that new techniques should be developed to help catch malicious circuits before they are loaded onto quantum computer hardware. Following ideas from classical computers, a compile-time technique can be designed to scan quantum computer programs for mali-cious or suspicious code patterns before they are compiled into quantum circuits that run on a quantum computer. This paper presents ongoing work which demonstrates how crosstalk can affect Grover's algorithm, and then presents suggestions of how quantum programs could be analyzed to catch circuits that generate large amounts of crosstalk with malicious intent.
Real-time computers of the Noisy Intermediate Scale Quantum (NISQ) era undergo the undesirable coupling among qubits known as crosstalk. The negative effects of crosstalk errors can lead to degradation in the performance of various quantum circuits. In this paper, we present four crosstalk models that negatively affect the outcome of Grover’s search algorithm, Simon’s algorithm and the performance of the quantum teleportation protocol. The crosstalk models presented in this work are used as malicious circuits running alongside the victim circuits of the said quantum algorithms and protocol. This is possible in the shared cloud quantum computing environment which is right now offered by some of the industries. This work demonstrates the formation of some of the possible patterns as parts of the malicious circuits and their repetitions to inject crosstalk errors in the victim circuits. The analysis of the affected outputs for each pattern along with the corresponding diagrammatic representation is also done in this article along with the discussion on the degraded results for the used victim circuits other than the state-of-the-art works for the available ones. Moreover, this work highlights the need for proper counter-measures in order to detect and eliminate the malicious patterns that can harm the performance of a quantum circuit.
The noisy intermediate-scale quantum (NISQ) computers suffer from unwanted coupling across qubits referred to as crosstalk. Existing literature largely ignores the crosstalk effects which can introduce significant error in circuit optimization. In this work, we present a crosstalk modeling analysis framework for near-term quantum computers after extracting the error-rates experimentally. Our analysis reveals that crosstalk can be of the same order of gate error which is considered a dominant error in NISQ devices. We also propose adversarial fault injection using crosstalk in a multiprogramming environment where the victim and the adversary share the same quantum hardware. Our simulation and experimental results from IBM quantum computers demonstrated that the adversary can inject fault and launch a Denial-of-Service attack. Finally, we propose system- and device-level countermeasures.
Hardware crosstalk in multi-tenant superconducting quantum computers constitutes a significant security threat, enabling adversaries to inject targeted errors across tenant boundaries. We present the first end-to-end framework for mapping physical pulse-level attacks to interpretable logical error channels, integrating density-matrix simulation, quantum process tomography (QPT), and a novel isometry-based circuit extraction method. Our pipeline reconstructs the complete induced error channel and fits an effective logical circuit model, revealing a fundamentally asymmetric attack mechanism: one adversarial qubit acts as a driver to set the induced logical rotation, while a second, the catalyst, refines the attack’s coherence. Demonstrated on a linear three-qubit system, our approach shows that such attacks can significantly disrupt diverse quantum protocols, sometimes reducing accuracy to random guessing, while remaining effective and stealthy even under realistic hardware parameter variations. We further propose a protocol-level detection strategy based on observable attack signatures, showing that stealthy attacks can be exposed through targeted monitoring and providing a foundation for future defense-in-depth in quantum cloud platforms.
Hardware crosstalk in multi-tenant superconducting quantum computers poses a severe security threat, allowing adversaries to induce targeted errors across tenant boundaries by injecting carefully engineered pulses. We present a simulation-based study of active crosstalk attacks at the pulse level, analyzing how adversarial control of pulse timing, shape, amplitude, and coupling can disrupt a victim's computation. Our framework models the time-dependent dynamics of a three-qubit system in the rotating frame, capturing both always-on couplings and injected drive pulses. We examine two attack strategies: attacker-first (pulse before victim operation) and victim-first (pulse after), and systematically identify the pulse and coupling configurations that cause the largest logical errors. Protocol-level experiments on quantum coin flip and XOR classification circuits show that some protocols are highly vulnerable to these attacks, while others remain robust. Based on these findings, we discuss practical methods for detection and mitigation to improve security in quantum cloud platforms.
Quantum computing (QC) is an emerging paradigm with the potential to transform numerous application domains by addressing classically intractable problems. However, its growing presence in cyberspace has introduced new security and privacy challenges. Similar to classical computing systems, the QC stack including software and hardware relies extensively on third parties, many of which are emerging and trust-seeking or less-trusted. This stack often contains sensitive intellectual property (IP) that demands protection. Unique features of quantum systems can enable classical-style attacks: for instance, crosstalk in multitenant settings can facilitate fault-injection attacks, while malicious calibration services can misreport error rates or miscalibrate qubits to induce denial-of-service (DoS) conditions. Given the high cost and limited availability of likely trustworthy quantum hardware, users may be enticed to explore emerging and trust-seeking but cheaper and readily available quantum hardware, which can enable the stealth of IP and tampering of quantum programs and/or computation outcomes. Similarly, emerging compilation services may compromise circuit confidentiality or insert Trojans. Despite the strategic significance of QC and its potential to process sensitive information, its security and privacy concerns remain underexplored. This article presents a comprehensive overview of QC fundamentals, key vulnerabilities, recent attack vectors, and corresponding defenses, and concludes with directions for future research to strengthen the quantum security community.