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Oct 21, 2026
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Our team often receives questions from customers looking for advice on how to defend against attacks in the AI era.
It's easy to see why. The FUD is relentless. Rogue agents, autonomous attacks and a threat landscape supposedly rewritten from scratch fill the headlines, and most of it comes from people with something to sell.
Here's what we tell our customers. AI is having a real impact, but mostly on the speed, volume and scale of attacks you already know. It lowers the barrier for attackers to find and exploiting vulnerabilities, and this makes traditional approaches to vulnerability management unviable.
What AI has done is force a reset. We've seen similar before. In the early 2000s, vulnerabilities went from an afterthought to a strategic priority. A few years later, cloud adoption changed what an attack surface even was. AI is the next watershed, and it has exposed the slow processes and tooling that were already holding security teams back, before AI put a turbocharger on the threat.
The good news is that, once you cut through the hype, the problem is solvable. The same advances that help attackers are available to defenders too.
Our new report, AI vs. the Patch Window: What Has Changed, and What Hasn't, sets out what's changed, what hasn't, and where the real attention needs to go.
Download your free copy of AI vs. the Patch Window
The Patch Window Has Collapsed
Vulnerability management has long assumed a gap between disclosure and exploitation, and that gap gave defenders time to patch. Mandiant now estimates the mean time to exploit at negative seven days, meaning exploitation often begins before a patch exists. Verizon's 2026 DBIR found that vulnerability exploitation now starts 31% of breaches. That is the first time it has overtaken stolen credentials in the report's 19-year history.
Our own research shows what this looks like in practice. When we found and responsibly disclosed wp2shell, an unauthenticated RCE chain in WordPress Core, public exploits appeared within hours of the patch. Mass exploitation followed in under two days.
Three Pressures, One Blind Spot
The report breaks down what AI is changing in vulnerability management:
- Discovery: AI finds flaws that have sat in production code for years. Our researchers found an RCE vulnerability in WordPress Core affecting millions of website with the help of AI in 10 hours for roughly $25 of compute. Attackers have the same capability, and as in the case of the cPanel vulnerabilities covered in the report, sometimes get there first.
- Weaponization: AI can compare patched and unpatched code and produce a working exploit in hours.
- Triage overload: Noise is rising, but genuine severe vulnerabilities are rising too, with around 1,500 high and critical CVEs published by major vendors in June 2026, more than 3.5 times the previous monthly record.
All three land on a gap that was already there. The average organization sees only about 62% of its external attack surface. And while 91% of CISOs say threat intelligence is valuable, only 26% say it drives their decisions.
What Should Security Teams Do?
The fundamentals haven't changed: move faster, act with confidence, and act earlier. The report turns that into five practical shifts that form a continuous loop:
- Make attack surface visibility continuous and comprehensive.
- Validate by exploitability, not severity.
- Know the attacker reality.
- Send high-confidence findings straight to remediation.
- Verify the exposure is closed, then keep checking.
You can't out-patch a window that has already closed. What you can do is find and fix exposures before attackers reach them, and that is the premise of preemptive cybersecurity.
Get the Full Report
Inside, you'll find the data, case studies and practical guidance behind each point.
