CutBackdoor: A Circuit Cut Triggered Backdoor Attack on Variational Quantum Algorithms
Ahatesham Bhuiyan, Hoang Ngo, Cheng Chu, Qian Lou, Lei Jiang, My T. Thai, Mengxin Zheng
quant-ph, cs.CR
Submitted: 2026-07-20
Code: https://github.com/Qiskit/qiskit-addoncutting
License: http://creativecommons.org/licenses/by-nc-sa/4.0/
The gist: Variational Quantum Algorithms (VQAs) are a leading paradigm for near-term quantum computing, combining parameterized quantum circuits with classical optimization across quantum chemistry,
Terminology
Abstract
Variational Quantum Algorithms (VQAs) are a leading paradigm for near-term quantum computing, combining parameterized quantum circuits with classical optimization across quantum chemistry, combinatorial optimization, and quantum machine learning. Since real-world VQA deployments routinely require circuits that exceed available hardware capacity, quantum circuit cutting has become an indispensable execution strategy, and pre-trained parameters are increasingly distributed through public repositories, introducing supply-chain security risks that have received little attention. Prior quantum backdoor attacks either introduce detectable circuit modifications or depend on device-specific noise, and none consider circuit cutting as an attack surface. We present CutBackdoor, the first parameter-supply-chain backdoor that uses cut circuit execution from CutQC as the deployment-time trigger against VQAs. Under noisy finite-shot circuit-cut execution, poisoned parameters preserve full-circuit validation performance while substantially increasing cut-path reconstruction error, without any circuit modification. The trigger activates when a resource-limited victim responds to a qubit-capacity mismatch by invoking the cutting workflow, requiring no attacker presence at deployment. We provide a theoretical analysis and empirically validate it across varying shot budgets. Evaluation across multiple VQA benchmarks on IBM quantum backends demonstrates cut-path energy amplification of 1.3 times to 2.9 times over clean baselines on the VQE and VQD benchmarks while maintaining small stealthiness error on the full-circuit path. The cut-path gap persists across the evaluated backends and cut placements under matched compilation; Zero-Noise Extrapolation provides only partial mitigation, and the diagonal-cost QAOA benchmark delineates the attack's structural boundary
Sources
- Strategies for running the QAOA at hundreds of qubits
- PennyLane: Automatic differentiation of hybrid quantum-classical computations
- Performance of the Quantum Approximate Optimization Algorithm on the Maximum Cut Problem
- Randomized Reversible Gate-Based Obfuscation for Secured Compilation of Quantum Circuit
- A Quantum Approximate Optimization Algorithm
- BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain
- Quantum computing with Qiskit
- Decoherence Free Subspaces for Quantum Computation
- Towards Efficient Ansatz Architecture for Variational Quantum Algorithms
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