Joshua Bass

Discusses the evolution of AI-driven phishing campaigns targeting Gmail users, explaining how attackers use AI to create highly convincing and personalized scams, and the need for advanced defenses.

Explores the limitations of traditional email and web defenses against generative AI-crafted scams and advocates for AI-native security platforms built around large language models for proactive threat detection and intent-based analysis.

Provides a comprehensive guide on integrating Large Language Model (LLM) phishing defense into Microsoft 365 environments, addressing the gaps in native M365 security against advanced AI-driven attacks.

Examines the dual-use nature of generative AI, highlighting its potential for both innovation and malicious exploitation in creating deepfakes and manipulating digital content, and the need for robust safeguards.

Outlines the evolving landscape of AI-driven phishing, including zero-day threats, hyper-personalized spear phishing, and deepfake-assisted social engineering, and discusses how enterprises can defend against these tactics.

Emphasizes the critical role of human elements in cybersecurity, outlining solutions like employee training, incident reporting systems, and leadership-driven security culture to complement technological defenses against phishing.