隨著生成式人工智慧的發展，駭客正利用深偽技術和高度客製化的網路釣魚活動來發動攻擊，例如北韓駭客組織假冒高階主管進行視訊通話。這項技術不僅降低了攻擊成本，還能透過操縱信任和緊迫感等人類情緒，使社交工程攻擊變得更加容易且具說服力。

人工智慧同時也將整個詐騙供應鏈產業化，促使結合電子郵件、簡訊和語音通話的多面向攻擊日益增加，甚至能創造出完全虛構的合成身分。即時視訊通話已不再是驗證身分的絕對保證，而大量逼真的偽造內容更可能導致人們對企業真實通訊的信任瓦解。

為應對這些威脅，企業開始部署由人工智慧驅動的進階活體檢測系統，透過分析生物訊號和背景數據來辨識真偽。此外，組織必須實施零信任架構，為敏感操作建立預先設定的通關密語，加強員工培訓，並制定主動防禦控制措施，以減輕無可避免的攻擊所造成的損害。

With the advancement of generative AI, hackers are utilizing deepfake technology and highly customized phishing campaigns to launch attacks, such as a North Korean hacking group impersonating executives on video calls. This technology not only lowers the cost of attacks but also makes social engineering more accessible and convincing by manipulating human emotions like trust and urgency.

Artificial intelligence is also industrializing the entire fraud supply chain, driving an increase in multi-vector attacks that combine emails, text messages, and voice calls, and even creating entirely fictitious synthetic identities. Live video calls are no longer an absolute guarantee of identity verification, and the sheer volume of highly realistic fake content risks eroding public trust in genuine corporate communications.

To combat these threats, companies are deploying advanced, AI-driven liveness detection systems that analyze biological signals and contextual data to verify authenticity. Additionally, organizations must implement zero-trust frameworks, establish pre-agreed passphrases for sensitive operations, enhance employee training, and develop proactive defense controls to mitigate the damage caused by inevitable attacks.