Amid growing fears of AI-driven cybersecurity threats, warnings are being issued against exaggerated “vulnocalypse” scenarios. While large language models are increasingly able to identify software vulnerabilities at scale, this does not automatically lead to an uncontrollable catastrophe. The real issue lies in a growing imbalance.

Automated systems are finding flaws much faster than organizations can fix them, exposing long-standing security shortcomings. The solution lies in measured, practical action. This can mean faster patch cycles, reduced attack surfaces, greater resilience, and stronger security fundamentals. It is also likely that, over time, AI will benefit defenders just as much as attackers.