AI levels the playing field for cyber attackers globally. It provides them with perfect English for social engineering, expert-level coding abilities for finding vulnerabilities, and effectively 'unlimited manpower' through automation. This combination leads to a significant increase in the volume and sophistication of attacks.

AI will find vulnerabilities at an unprecedented rate. The real crisis will be the organizational inability to patch them, especially in critical infrastructure with long update cycles and unsupported software where original developers are long gone. The problem shifts from finding flaws to fixing them at scale.

AI tools aren't just lowering the bar for novice hackers; they are making experts more effective, enabling attacks at a greater scale across all stages of the "cyber kill chain." AI is a universal force multiplier for offense, making even powerful reverse engineers shockingly more effective.

AI enables attackers to launch scalable, rapid attacks, overwhelming defenders who are left to manually monitor, validate, and patch vulnerabilities. This dramatically shifts the balance of power, creating a significant strategic disadvantage for cybersecurity teams in a way not seen before.

AI has armed cyber attackers with a new weapon: swarms of coding agents. Unlike human attackers, these agents can exhaustively and rapidly review an entire codebase to find vulnerabilities, dramatically increasing the speed and scale of cyber threats. This necessitates a boom in AI-powered defensive tools.

Anthropic's AI found thousands of vulnerabilities in supposedly well-vetted open-source code. Because this code is widely copied and embedded in countless enterprise systems, these flaws represent a massive, previously unknown attack surface across global digital infrastructure.

The old security adage was to be better than your neighbor. AI attackers, however, will be numerous and automated, meaning companies can't just be slightly more secure than peers; they need robust defenses against a swarm of simultaneous threats.

AI models are better at finding bad code than writing good code. This capability will rapidly uncover vulnerabilities in open-source, custom, and vendor software that would have otherwise taken 10 years to find. This creates an urgent, large-scale need for patching across all industries.

The traditional cybersecurity model of humans finding and patching vulnerabilities cannot keep pace with AI that discovers thousands of exploits in hours. This fundamental mismatch in speed and scale will require a complete overhaul of how software security is managed.