AI Didn’t Just Disrupt the Scanner. It Disrupted the Entire Security Vendor Ecosystem.

Blog February 22, 2026

Chief Security and Trust Officer, ArmorCode

When Anthropic launched Claude Code Security on Friday, most of the conversation focused on what it means for enterprise security programs. That’s the right conversation to have. But there’s a bigger one underneath it that I haven’t seen anyone address directly.

This isn’t just a better scanner. It’s a foundation model company moving into a product category. And that changes the structural logic of the entire security vendor ecosystem in ways that will play out over the next 18-24 months whether security leaders are paying attention or not.

I’ve spent my career on the buying side of that ecosystem, running programs at organizations like Kroger and AT&T where vendor decisions at scale have real consequences. What I’m seeing right now looks less like a functional disruption and more like the beginning of how and where security gets consolidated. The last time the security industry went through something like this, it took years for practitioners to understand what had actually happened. I don’t think we have that kind of time now.

What actually happened on Friday

The financial markets read the Anthropic announcement as an “AI will produce secure systems” and a security scanner story and sold off scanner-adjacent stocks accordingly. That reaction was correct but incomplete.

The depth of what’s happening is this: the same companies building the foundational AI infrastructure that powers development workflows, code generation, and developer tooling are now also building the security analysis layer. Those are no longer separate markets with separate vendors. They are becoming a single integrated surface, and the integration is happening from the bottom up, at the infrastructure level, in tools developers are already using every day.

According to Anthropic, Claude Code Security doesn’t scan for known patterns. It reads and reasons about code the way a human security researcher would, understanding how components interact, tracing data flows across files, identifying complex multi-component vulnerability patterns that rule-based tools miss. Using Claude Opus 4.6, their team found over 500 previously undetected vulnerabilities in production open-source codebases. Bugs that had survived years of expert review.

That capability, embedded directly into the development environment, at marginal cost to the developer, changes the value equation for every standalone tool that has been delivering detection as its primary value proposition.

We are moving past a ‘find-the-problem’ mentality toward an integrated approach that prioritizes prevention and immediate resolution of issues as they arise. This fundamental shift—from siloed, reactive scanning to integrated, proactive, and continuous security within the development pipeline—creates a compelling, non-negotiable need for a unified risk management platform.

As security is “shifted left” and decentralized, the organization loses the ability to holistically assess and prioritize true risk. A centralized platform is essential to:

Aggregate Disparate Data: Collect findings and context from all the new, integrated security tools (SAST, DAST, SCA, etc.) across the entire development and operational lifecycle.
Establish True Risk Context: Apply business context, asset criticality, exploitability, and compliance requirements to the raw findings to calculate a unified, prioritized, and actionable risk score.
Ensure Governance and Accountability: Provide a single source of truth for security posture, compliance, and remediation tracking, ensuring that the “secure by design” principles translate into measurable risk reduction across the entire organization.

Without this platform, the transition to proactive security simply replaces one set of siloed tools with another, leaving the organization unable to manage and communicate its actual security risk effectively.

The ecosystem restructuring nobody is modeling

It reminds me of the structural shift that occurred a few years ago, moving from Intrusion Detection to Intrusion Prevention, where tooling centered on detection quickly had to integrate with proactive preventive controls. That same fundamental upheaval is now echoing across the application security and scanning market.

Here’s what I’ve observed running large security programs: the security vendor ecosystem has always been fragmented by design. Each category emerged to solve a specific problem that existing tools couldn’t handle. A classic example would be data protection. Static analysis for code vulnerabilities. Dynamic analysis for runtime behavior. Software composition analysis for open source dependencies. Container scanning for infrastructure. Cloud security posture for configuration drift. Each one added a new data stream, a new console, a new team responsibility, a new vendor relationship. And soon enough a typical enterprise is running 50 – 100 different security tools yet we have not solved the security posture problem.

That fragmentation made sense when each category required specialized expertise to build. It makes less sense when a foundation model can reason across all of those surfaces with the same underlying capability. The question isn’t whether AI will eventually cover each of these categories. It’s how fast, and what that means for the standalone vendors who built their businesses around one of them.

The categories most immediately at risk are the ones delivering value primarily through detection of known patterns: static analysis, secrets detection, basic software composition analysis. These are the tools furthest toward the left of the development pipeline and most directly in the path of what Claude Code Security does today.

The categories with more runway are the ones further right: dynamic analysis of running applications, cloud security posture management, API security testing. These require runtime context, live environment access, and operational integration that pure code analysis can’t replicate yet. But the same contextual reasoning capability that reads a codebase today will read network traffic, runtime behavior, and cloud configuration tomorrow. The timeline is different. The direction is the same.

The platform giants have a structural advantage that is easy to underestimate

The security industry has been through vendor consolidation cycles before. What’s different this time is where the consolidation pressure is coming from.

Previous consolidation waves were driven by large security platforms acquiring point solutions and bundling them. The pressure came from within the security industry, from vendors competing for budget and shelf space. Buyers understood the dynamic and could navigate it.

The current pressure is coming from outside the security industry entirely. The companies building AI coding assistants, development platforms, and foundation models are not primarily security companies. Security is an adjacent capability they are adding to tools developers are already dependent on. That makes the competitive dynamic fundamentally different for incumbent security vendors, because they are not competing against another security company with a comparable go-to-market. They are competing against infrastructure that developers will use regardless of whether it includes security features.

When detection capability is embedded in the tool your developers use every day, the standalone detection tool faces a question it has never had to answer before: what do you offer that the infrastructure doesn’t already provide? For many vendors in the current ecosystem, the honest answer to that question is getting harder to give.

What survives and what doesn’t

Not everything in the current security vendor landscape is equally exposed to this shift. The way I think about it from a solutioning perspective: tools whose primary value is detection are structurally more exposed. Tools whose value includes remediation, healing, workflow, integration, organizational context, and governance are structurally more durable.

Detection is becoming inherent. The same way basic logging evolved from a premium feature into a commodity layer that every platform provides, core scanning capabilities are moving toward infrastructural ubiquity. They will remain necessary. They will no longer be sufficient as a business.

What doesn’t commoditize is the layer above detection: the ability to take findings from every source across a heterogeneous environment, normalize them against a common data model, apply real asset criticality and business context to prioritization, route them through organizational workflows, track remediation to closure, and produce the audit evidence that compliance frameworks require. That layer requires deep integration across dozens of tools, organizational context that no single scanner possesses, and a vendor-neutral position that platform vendors are structurally unable to hold.

The critical word there is vendor-neutral. A governance layer built by a platform vendor optimizes for that vendor’s ecosystem. It has an inherent incentive to surface findings from its own tools, route remediation through its own workflows, and make switching costs as high as possible. For enterprises running 50-100 security tools across heterogeneous environments, that’s not a governance layer. That’s a lock-in mechanism dressed up as one.

The independent governance layer, the one that sits above all scanners including Claude Code Security, that aggregates without bias and governs without a preferred vendor outcome, becomes more strategically important as the detection layer commoditizes beneath it. Not less.

In fact a governance framework that incorporates AI related to exposures is even more important and is a future proofed solution to handle all things risk.

What this means for how you build your security program

If I were advising a CISO on how to position their program for the next 24 months given this shift, the guidance would be straightforward.

Stop evaluating standalone detection tools as strategic investments. Ask what the total cost of ownership looks like when the detection capability is eventually available at infrastructure cost from the platform your developers are already on. Buy for coverage gaps and integration quality, not for detection sophistication as a differentiator.

Invest heavily in the governance layer. This is the part of your security program that will compound in value as detection commoditizes. Your ability to aggregate findings from any source, apply consistent prioritization, manage remediation workflows at scale, and produce audit evidence that satisfies regulators: these capabilities become your program’s durable competitive advantage as the vendor landscape restructures around you.

Maintain vendor neutrality in your governance architecture. The worst position to be in 24 months from now is locked into a governance platform that tilts toward a single vendor’s detection ecosystem, because the detection ecosystem is the part of the stack that is most in motion. Your governance layer needs to absorb whatever the detection layer becomes, not be optimized for what it is today.

The security industry is restructuring. The vendors who understand that are repositioning now. The ones who don’t are hoping the wave doesn’t reach them. In my experience, the wave always reaches them. The only question is whether you’ve built the right architecture before it does.