"title": item.get("title"),
A recent article published by the BBC explored how generative AI tools could be “hacked” within minutes by introducing newly published online content. In the example presented, a blog post claiming expertise in a highly niche category was later echoed in responses from systems such as OpenAI’s ChatGPT and Google’s AI outputs when prompted with […]
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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.
687 OPR_R - PROTUN TST_DES_SIMPLE PTOVRR UNL ; validate descriptor，详情可参考51吃瓜