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Not hours. Not days. It takes thirty-nine seconds from initial access to data exfiltration.

That stat, pulled from Unit 42^® research, isn't hypothetical. It's what defenders are up against right now, while most organizations are still building security teams around manual detection and response workflows that were never designed to operate at machine speed.

Wendi Whitmore, Chief Security Intelligence Officer at Palo Alto Networks, put it plainly in a recent conversation on the Threat Vector podcast, recorded live at RSA this year:

If you're applying a manual detection and response capability, you are going to be beat by the attacker every day.

It's the kind of sentence that should make security budgets move faster.

The Threat Landscape Doesn't Wait for Organizational Consensus

Whitmore has spent nearly 25 years tracking nation-state actors, and she's unequivocal about what's changed. The adversaries today aren't just better funded and more sophisticated. They're faster, and increasingly AI-powered.

Consider what's converging right now:

Chinese nation-state groups like Volt Typhoon and Salt Typhoon have been operating with near-surgical patience inside critical infrastructure, leveraging existing administrative tools to avoid detection. Volt Typhoon is focused on military prepositioning in power grids, water systems and telecommunications. Salt Typhoon has been systematically collecting intelligence from those same networks. Neither group announces itself with novel malware. They disappear into environments using the tools already there.

Meanwhile, threat actors tied to Iran are operating with entirely different objectives: tactical disruption and destruction. And financially motivated cybercriminal groups are automating ransomware campaigns at a pace that has compressed attack timelines from weeks to minutes.

Every CISO is being asked to defend against all of them simultaneously, while also managing their organization's AI expansion, and doing it without adding headcount.

Speed Is the New Perimeter

When Whitmore references the 39-second exfiltration window, she's pointing at something structural, not just alarming. It reflects how completely the attacker's operational tempo has shifted.

The 72-minute data breach figure from Unit 42 Incident Response data is equally striking: From initial access to full data theft in the time it takes to sit through a decent movie. A 400-times year-over-year increase in exfiltration speed isn't a trend. It's a fundamental change in the physics of an attack.

"There is no way that we are going to defeat these adversaries if we are working at manual speed," Whitmore explained. The answer isn't just more analysts. It's fighting AI with AI, letting machines handle the volume and velocity, so humans can focus on the problems that actually require human judgment.

Two Sides of the Same AI Problem

Here's where the conversation gets more nuanced and more important.

Most of the AI-in-security conversation focuses on the offensive side: adversaries using generative AI to craft convincing phishing lures, accelerate reconnaissance and automate attack sequences. That's real, and it's accelerating.

But Whitmore raised the other half of the problem, one that gets far less attention: The attack surface that organizations are creating by deploying AI without securing it.

Innovation of AI doesn't so far outpace the security of AI.

This is the outcome she wants to see. Right now, that's not what's happening. Business pressure to deploy AI quickly is outrunning the security architecture required to protect it. Every new AI deployment touching production data, cloud APIs and enterprise systems expands the attack surface. Shadow AI, prompt injection, model poisoning: These are not future threat vectors. They're present tense.

The distinction Whitmore draws is useful: AI for cybersecurity (faster detection, automated response, reduced analyst burden) needs to advance in parallel with cybersecurity for AI (securing the models, prompts and data pipelines that organizations are building on). One without the other creates exactly the kind of asymmetry attackers will exploit.

Visibility Is Where It Starts

Whether the conversation is about defending against nation-state actors or securing AI deployments, Whitmore keeps returning to the same foundation of visibility.

Not complexity. Not more tools. Visibility is a single, unified view of what's happening across endpoints, networks, cloud and AI systems, that’s fast enough to matter when the window is measured in seconds, not days.

For SOC teams, that means being able to detect and contain a threat before a compromise of one system becomes an enterprise-wide event. For CISOs thinking about AI governance, it means understanding what's being deployed, what's being prompted, and where the data is going before an incident surfaces for them.

The organizations Whitmore sees succeeding aren't the ones with the largest security budgets. They're the ones with the clearest picture of their environment, and the architecture to act on it in real time.

The Win Looks Different Now

Perhaps the most important reframe in the conversation is that the objective is no longer to prevent every attack. That goal is not achievable against adversaries operating at AI speed with nation-state resources.

The win is resilience. Detecting fast and containing fast. Keeping one compromised endpoint from becoming an enterprise-wide breach.

That shift in framing, from prevention to rapid recovery, has significant implications for how security teams are built, how AI is integrated into workflows, and how CISOs make the case for investment to leadership that still thinks in terms of keeping attackers out.

The adversaries already know the perimeter is gone. The question is whether your defense strategy has caught up.

Want to Dig in More?

Listen to the full interview here.

The Unit 42 2026 Global Incident Response Report goes deep on the threat trends shaping how modern attacks unfold. If you want the data behind the headlines, start here. Download the Report →

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