网络钓鱼（Phishing）作为一种利用社会工程学手段窃取敏感信息或植入恶意软件的网络犯罪形式，其历史几乎与互联网的商业化应用一样悠久。然而，进入2026年，随着人工智能生成内容（AIGC）技术的普及以及远程办公模式的常态化，钓鱼攻击的复杂度、规模化程度及成功率均呈现出指数级增长态势。传统的基于黑名单和特征码的防御机制，在面对高度定制化、动态化且极具心理诱导性的新型钓鱼攻击时，往往显得捉襟见肘。

Last year, US banks used real-time machine learning to flag over 90 percent of suspected fraud, yet almost half of chargeback disputes were still managed manual ...

Code and architecture often fail to convey meaning understandably. Not only humans but also AI models fail due to the consequences.