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New York University Abu Dhabi, Center for Quantum and Topological Systems (CQTS), NYUAD Research Institute, NYUAD
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Quantum malware detectors, while accurate on clean data, are surprisingly vulnerable to sophisticated executable-aware adversarial attacks, with defenses like dynamic adversarial training showing promise.
LLM-generated quantum tests are executable but fail to reliably distinguish correct from faulty code, with the best models achieving only 71% and 34% test quality on separate benchmarks.