This does not mean confusables.txt is wrong. It means confusables.txt is a visual-similarity claim that has never been empirically validated at scale. Many entries map characters to the same abstract target under NFKC decomposition (mathematical bold A to A, for instance), and the mapping is semantically correct even if the glyphs look nothing alike. But if you treat every confusables.txt entry as equally dangerous for UI security, you are generating massive false positive rates for 96.5% of the dataset.
Rather than a hardcoded font list, confusable-vision auto-discovers every system font that contains Latin a-z:
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Despite the increase, the number of successful claims has been small. As of mid-November last year, 249 people had received payouts for harm caused by Covid vaccinations.