I wrote this last month Artificial intelligence has made code creation easier than ever— and it's just as easy to create insecure code. The pace of development has exploded. So are security vulnerabilities. Today, we write, generate, and deploy software faster than most organizations can secure it.
The result is what I called a growing heap security debt— problems put aside in the name of progress, adding compound interest every sprint. The old way of managing security simply can't keep up.
Over the years, companies have tried to solve this problem by combining more tools. One for static analysis, one for dependencies, one for APIs, one for containers. Each with their own dashboards, reports and risk assessments. Together they created more noise than insight.
Now the tide is turning. Platforms like Checkmarx One are gaining popularity as enterprises realize that piecemeal tools don't scale. This may be the beginning of the end of AppSec silos.
From chaos to clarity
Every security tool was built with good intentions: to find problems before attackers do. The problem is that when hundreds of requests come in from disconnected systems, no one has the context to separate what's urgent from what's unimportant.
I have seen this phenomenon in various industries. Developers ignore alerts they don't understand. Security teams chase duplicates. Management assumes that “protection” equals protection. Meanwhile, the real risks continue to grow beneath the surface.
Unified AppSec platforms solve this problem by combining code, dependencies, infrastructure, and APIs into a single ecosystem. Instead of treating each layer like an island, they correlate everything and thus begin to reveal what's really important.
Artificial intelligence makes a difference
AI is not a magic wand, but it is the first real breakthrough in how AppSec data is used. Traditional scanners are great at pointing out defects, rather than assessing which ones are significant. AI fixes this by adding context.
Machine learning models can understand whether a vulnerability is hidden in unused code, exposed to the public Internet, or linked to sensitive data. They can track utilization opportunities across modules and prioritize based on impact. In other words, they transform information into intelligence.
This transition – from detection to decision-making – is what makes these new systems so powerful. Developers get actionable results instead of alarm fatigue. Security teams can finally focus on mitigating risk rather than triaging reports.
The inflection point of the enterprise
Checkmarx recently announced that Checkmarx One platform surpassed $150 million ARR in less than three years. A milestone is more than just a press release. This is a reflection of what is happening across the enterprise landscape. Companies that once relied on a dozen niche tools are consolidating around unified AI-powered platforms that integrate directly with CI/CD pipelines and IDEs.
You can't protect what you can't see, and fragmented visibility is the Achilles' heel of modern software security. Organizations that do this well don't do more scanning – they do smarter scanning, guided by context and automation.
Collateral debt and the AI coding boom
When AI began writing code at scale, it not only accelerated development, but accelerated the accumulation of security debt. Every line of code generated may inherit faulty patterns, untested logic, or insecure dependencies. Humans can't manually check this volume, and disconnected tools can't see the bigger picture.
That's why unity matters.
A single platform can track lineage from AI-generated fragments to deployed microservices, identify vulnerabilities early, and provide real-time guidance to developers. Security should be a feedback loop, not an obstacle.
Safety that takes a backseat
The best protection doesn't scream. It just works.
That's where we're going – built-in security, not bolt-on security. Unified AppSec platforms will eventually become as invisible as continuous integration: always working, always learning, always improving.
When this happens, we will finally have a model that scales with the pace of development rather than being left behind. An AI-powered context will enable us to secure what we create as quickly as we create it.
The most important thing
The AI coding boom has exposed how fragile our approach to security has been. This forced us to reckon with the limitations of human supervision and the inefficiency of growing tools.
Ending AppSec silos means rethinking how you build trust in software from the first line of code all the way to final deployment. We've spent decades building tools that detect problems. The next decade will belong to systems that understand them.
