Adversarial Fragility and Language Vulnerability in Clinical AI: A Systematic Audit of Diagnostic Collapse Under Imperceptible Perturbations and Cross-Lingual Drift in Low-Resource Healthcare Settings

In three linesSystematic audit of two critical vulnerabilities in clinical AI: adversarial fragility and cross-lingual drift. On CheXNet (DenseNet121), accuracy collapses from 89.3% to 62.0% under imperceptible FGM perturbation (epsilon=0.021). Llama3.1:8b and NatLAS show major degradation on Nigerian Pidgin and Yoruba (80%→65%, 85%→55%). Standard defenses fail.

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