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.

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.

Palo Alto Networks' CEO explains that AI tools are discovering software vulnerabilities at an unprecedented rate. This will cause a short-term deluge of patches, but it's effectively cleaning up years of bad code and will ultimately strengthen the entire ecosystem.

The rise of AI-powered attacks means vulnerabilities are exploited in minutes. Palo Alto Networks responded by developing a capability to deliver and deploy patches to all customers in just four hours, a massive reduction from the industry average of 55 days, fundamentally changing incident response time.

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.

Meera Rajival says AI models like Mythos are finding vulnerabilities in old code, and companies such as Bank of America have too much software to patch quickly. She says Palo Alto added virtual patching at the edge while remediation proceeds, calling security hygiene more important than ever.

Nikesh Arora says Palo Alto's scan found 22 million vulnerable places, narrowing to roughly nine or ten million. The hosts focus on long-tail local government and small business sites, which are less likely than big platforms to patch quickly. Those forgotten systems are where sensitive data can sit exposed.

While AI models excel at identifying security vulnerabilities, the next major innovation lies in automatic remediation. The "holy grail" for cybersecurity startups is developing AI systems that can instantly patch and fix identified threats, moving beyond simple detection to proactive, zero-day defense.

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.