Page 111 - Cyber Defense eMagazine September 2025

But an evolved firewall by itself isn’t enough, and you can’t secure what you can’t see—that’s where most
organizations are still exposed.

Cloud-Native Broke the Perimeter. You’re Still Relying on It

Cloud-native architecture dismantled the perimeter model. Applications are no longer isolated behind
digital moats. Workloads run in containers, scale dynamically, and often communicate in mesh networks
you didn’t hand-configure.

Yet security strategies still default to perimeter defense. Teams drop traditional firewalls at the edge of
their VPC and call it a day, and the problem is that threats don’t need to come in from outside anymore—
for 83% of organizations, they’re already inside. Misconfigured services, excessive permissions, and
exposed secrets give attackers all they need. These vulnerabilities often live in the code and
configurations your developers ship every day.

A modern firewall must be able to monitor east-west traffic, enforce policies at the workload level, and
adapt to the highly dynamic nature of cloud-native environments. That requires two things: deep visibility
into what’s running and how it behaves and intelligence to act on that data in real time.

AI in Firewalls Isn’t a Feature; It’s the Only Way This Works.

There’s a reason AI is everywhere in security marketing—but in this case, it’s justified. AI isn’t just
automating rule writing. It’s the only realistic way to keep pace with the scale and speed of modern
workloads.

An AI-driven firewall in a cloud-native world needs to do three things well:

1. Baseline behavior dynamically: It must understand how your workloads behave under normal
conditions, not based on static signatures but by learning patterns over time. This feature is crucial
when microservices scale horizontally, and traffic patterns shift constantly.
2. Enforce policies autonomously: Your infrastructure is elastic, and security policies must be,
too. AI-driven systems can adjust rules in real time, applying least-privilege principles to traffic
flows without waiting for human input.
3. Detect anomalies fast: AI enables real-time threat detection by analyzing huge volumes of
telemetry data, spotting outliers, and taking action before an attacker can move laterally.

This point is where AI stops being hype and starts being practical. In a cloud-native environment, static
rules and manual policy updates are slow and active liabilities. Just as AI enhances core firewall
functionality, AI-driven web application firewalls (WAFs) can learn application-specific traffic patterns and
detect anomalies that indicate complex web attacks, such as zero-day exploits or API abuse.

Cyber Defense eMagazine – September 2025 Edition 111
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