The Zero Trust Hub

For years, cybersecurity has relied on a comforting rhythm. We check security controls on a schedule: once a quarter, once a month, maybe once a week. If everything looks fine, we move on.

That rhythm no longer matches reality.

One of the clearest signals came recently from the U.S. Department of Defense. The Pentagon announced it is shifting away from periodic security audits and toward real-time cyber risk management.  

Instead of reviewing controls after the fact, the focus is now on continuous monitoring, automation, and live visibility into risk.

The fact is that cloud platforms, AI systems, and connected infrastructure don’t pause between audits. Threats don’t wait for the next review cycle. Trust decays the moment conditions change.

That gap between how fast systems move and how slowly trust is evaluated is exactly why Zero Trust exists.

Why periodic security no longer works

Traditional security reviews offer a snapshot in time. They tell us whether controls looked acceptable when someone checked.  

In slower, static environments, that approach was often good enough.

Today’s environments are dynamic by design. Workloads spin up and down automatically. Data moves across clouds and regions constantly. AI systems pull information from sources that change every minute.  

A control that was valid yesterday may be risky today.

Zero Trust security starts from this reality. It assumes that change is constant. Because conditions change continuously, trust must be verified continuously.  

You can't grant trust for a week and expect it to hold.

This is why Zero Trust is not a checklist or a compliance milestone. Rather, it’s an operating model built for environments that never stop moving.

AI breaks traditional trust assumptions

AI has made the trust problem more complicated, not easier.

A recent incident involving Salesforce illustrates this shift. Attackers didn’t steal data through a traditional breach. Instead, they manipulated the data feeding an AI system using a technique called prompt injection.  

By poisoning the inputs, they caused the AI engine to expose sensitive information.

This matters because the attacker influenced AI behavior instead of using traditional methods like defeating a firewall or exploiting a known vulnerability.

AI systems respond to patterns, not intent. They don’t understand context the way humans do.  

When attackers learn how to manipulate inputs, trust breaks in subtle ways that perimeter-based defenses were never designed to detect.

Static controls struggle here because the attack targets behavior, not a known vector.

Zero Trust is becoming behavioral security

Zero Trust was built for this kind of variable behavior.

At its core, Zero Trust treats trust as conditional and temporary. Every interaction is evaluated based on current context instead of past approval.  

That principle applies directly to AI-driven systems, where behavior matters more than configuration.

In a Zero Trust model, the key question is not: “Was this system approved last quarter?” Instead, it’s: “Does this interaction make sense right now, given what we know?”

That shift is critical. As systems learn and adapt, security must focus on outcomes and behavior rather than static rules. This is pushing the industry toward behavioral security, where controls assess patterns and actions in real time.

There is no final configuration that guarantees safety forever.

The case for Zero Trust in a constantly changing world

The pace of change is accelerating. AI systems are becoming more autonomous. Data flows are becoming more complex. Attackers are increasingly targeting trust itself rather than individual systems.

Zero Trust acknowledges that trust must be continuously earned in environments that never stop changing.

Organizations that cling to periodic security checks will continue to fall behind. Those that adopt Zero Trust principles will be better positioned to limit risk, adapt faster, and stay resilient.

Trust is no longer static, and security can't be either.