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Nikesh Arora says models arriving in two to three months will be more capable than public ones, so bugs not found today will be found soon. He warns defenders will lose the luxury of weeks to assess whether a vulnerability is real, because AI also accelerates exploit writing.

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The primary cyber threat from AI is not new attack vectors, but the speed at which models can discover existing vulnerabilities. The only effective defense is to use AI to find, prioritize, and patch these flaws faster than adversaries can exploit them.

Powerful AI tools have fundamentally altered cyber defense by shrinking the time it takes to exploit a software flaw. What once took skilled hackers days, weeks, or months can now be weaponized in hours or days, making traditional defense and patching strategies obsolete.

The AI vulnerability race has begun, and the timeline is alarmingly short. Advanced AI models can already identify security flaws seven times faster than human teams. Cybersecurity firms estimate that organizations have only three to five months before attackers gain widespread access to similar AI-powered exploit capabilities.

As AI models become adept at finding software vulnerabilities, there's a limited time for companies to use these tools defensively. This brief "catch-up" period exists before these powerful capabilities become widely available to malicious actors, creating an urgent, time-boxed need for proactive patching of legacy systems.

Frontier AI models are dramatically reducing the time it takes for a newly discovered software vulnerability to be turned into a functional exploit. This acceleration means traditional, onerous patching cycles are no longer viable. Organizations must find new ways to patch systems almost immediately, as exploits can appear within hours of a vulnerability's announcement.

Previously, finding exploits in a new device's code could take a year of manual analysis. Now, AI can be fed a technical dump (firmware, logic, hardware specs) and identify vulnerabilities in hours, accelerating the exploit development cycle.

Advanced AI models capable of finding complex code vulnerabilities are expected to be publicly available within months. This puts enterprises in an urgent race to find and patch their own security holes before malicious actors use the very same tools to exploit them.

The average time for an enterprise to patch a zero-day vulnerability is 55 days. AI agents can now find and build an attack for that same vulnerability in a fraction of a second, fundamentally changing the speed and scale of cyber defense required.

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.

AI models like Mythos aren't just finding vulnerabilities; they are creating working exploits almost instantly. This forces security and engineering teams to abandon manual patching in favor of automated, machine-speed defense pipelines.