Introducing the AI Security Fabric: Empowering Software Builders in the Era of AI

Today, we’re thrilled to introduce the AI Security Fabric, delivered through the Snyk AI Security Platform, and operationalized through a prescriptive path for AI security.

As software creation shifts to humans, models, and autonomous agents working together at machine speed, security must evolve just as fundamentally. The AI Security Fabric defines the new paradigm, and the Prescriptive Path shows how the Snyk AI Security Platform gets you there.

AI has changed how software is built

Software creation has entered a new era in which code is no longer written line by line by humans alone, but rather is continuously generated by models and increasingly autonomous agents operating together at machine speed. Though it has unlocked unprecedented productivity and innovation, this shift has fundamentally changed how risk enters our systems.

Modern applications are no longer composed solely of source code and open source dependencies. They now include AI-native components such as models, prompts, agent-native artifacts, MCP servers, and agent-driven workflows. These elements are created dynamically, often outside traditional pipelines, and rarely appear in existing asset inventories.

The result is a software supply chain that is broader, faster-moving, and far more difficult to track, creating blind spots that traditional security models were never designed to handle.

Velocity without trust breaks security

Speed alone doesn’t break security; untrusted speed does. Most security programs were designed for deterministic systems and human-paced workflows. Those conditions simply do not exist in an AI-driven SDLC, as new code, dependencies, and services continuously appear, often without clear ownership or visibility. Static signals alone are no longer sufficient to determine what actually matters.

As velocity increases without corresponding trust, confidence erodes. Security teams struggle to distinguish real risk from noise, developers stop trusting late, context-poor findings, and organizations are forced into an impossible tradeoff: slow down to regain control, or move fast and accept unmanaged risk.

This is how velocity turns into chaos. Closing this gap requires more than faster scanning or more alerts. It requires a security model that continuously orchestrates and delivers deterministic trust at AI speed - ensuring visibility, enforcing prevention, and prioritizing based on real-world impact. That trust is the prerequisite for everything that comes next.

Why AI security requires a fabric

When velocity outpaces trust, security breaks down not because tools are missing, but because it is no longer woven into the creative process. We saw this vividly last week with the viral rise of OpenClaw (formerly ClawdBot). In just days, thousands of developers granted full access to an autonomous agent that sits outside traditional IAM controls. 

Traditional security operates as a series of checkpoints: scan here, review there, fix later. But OpenClaw proves that the model is obsolete. It creates persistent non-human identities, executes commands autonomously, and is susceptible to prompt injection from simple emails - risks that traditional scanners simply cannot see.

The gap is widening: exploit timelines are predicted to accelerate by 50% by 2027 due to AI, giving defenders less time than ever to react.

AI compounds this fracture by introducing non-determinism at scale. With 77% of developers already using AI coding assistants and 48% of that generated code containing security vulnerabilities, risk is now entering systems continuously and autonomously.

What’s needed is not another point solution, nor more alerts downstream. What’s needed is a new autonomous defense paradigm–an AI Security Fabric. This invisible, intelligent layer adapts as systems change and operates at machine speed, weaving security directly into every stage of modern software creation. 

How Snyk delivers the AI Security Fabric

The AI Security Fabric defines how security must operate in the age of AI. The Snyk AI Security Platform is how that Fabric is delivered in practice today.

Snyk delivers the AI Security Fabric through three unified vectors, each addressing a critical phase of modern software creation as organizations move from AI adoption to AI-native systems. These vectors describe where Snyk applies security across modern software creation, not the order in which organizations adopt them.

1. AI-accelerated DevSecOps

You cannot secure the AI future with a broken DevSecOps past. As AI accelerates development, organizations must first fortify how software is built and secured today. Without strong fundamentals, AI amplifies existing blind spots, noise, and manual processes.

Snyk strengthens the foundation by delivering visibility and accuracy across the modern software supply chain, spanning first-party code, open source dependencies, containers, and infrastructure. This ensures teams know what exists, what’s at risk, and what must be addressed before vulnerabilities reach production. This foundation is what restores trust in the signal and creates a stable environment where AI-driven development can safely scale.

2. Securing AI-driven development

Developers are now using AI to write code faster than ever, enabling risk to increasingly enter the system at the moment code is generated. Snyk secures AI-driven development by embedding security directly into AI coding assistants through Snyk Studio. 

This enables Secure at Inception: real-time guardrails that guide both human and AI-generated code from the very first prompt. By shifting prevention to the earliest possible moment, Snyk allows teams to move at AI speed without introducing hidden risk, accelerating development while maintaining trust.

3. Securing AI-native applications

Applications themselves are evolving. Modern systems are becoming non-deterministic and agentic, driven by autonomous components that observe, decide, and act. Traditional security tools, designed for static code and predictable workflows, cannot defend these environments alone.

This is where Evo by Snyk extends the Fabric, securing AI-native applications and agents. Evo is the world’s first agentic security orchestrator, designed to secure AI-native applications and agents in runtime. By observing behavior, making decisions, and taking action autonomously, Evo closes the loop between code security and runtime defense, extending the AI Security Fabric into the frontier of AI-native systems.

Together, these three vectors form a unified platform that delivers the AI Security Fabric, from foundational DevSecOps, through AI-driven development, to the emerging world of autonomous applications.

But while the platform provides the engine, organizations still need a clear way to apply it, mature their practices, and scale securely over time. That’s why we’ve defined the Prescriptive Path to operationalizing AI security.

The Prescriptive Path to operationalizing AI security

The AI Security Fabric defines how security must operate in the age of AI. The Snyk AI Security Platform delivers the capabilities required to make that possible. The Prescriptive Path defines how organizations apply those capabilities over time.

AI security adoption is not a single-step process. As AI reshapes how software is built, risk enters systems earlier, faster, and in more places. Organizations mature progressively, not by turning on features, but by achieving outcomes that restore trust, reduce real risk, and sustain governance as automation increases.

The Prescriptive Path is an opinionated operating model that helps organizations sequence their focus and efforts as they operationalize AI security. It does not map to specific products or platform domains. Instead, it utilizes all of the Snyk AI Security Platform, guiding when and how different capabilities are applied to achieve meaningful security outcomes.

The Path is organized into three acts, each representing a set of outcomes organizations must achieve to move forward with confidence. Together, they provide a clear, practical path for operationalizing AI security, helping organizations move from reactive controls to architected trust as AI adoption accelerates.

Phase 1: Stabilize - establish trust and control

The first priority is stability. As AI accelerates development, organizations must eliminate blind spots and restore trust in their security signal. This means understanding what exists across the software supply chain, ensuring accurate detection, and enforcing guardrails to prevent unchecked new risks from entering.

In this act, security becomes predictable and trustworthy. Teams gain confidence that risk is visible, prevention is enforced, and development can move faster without amplifying chaos.

Phase 2: Optimize - focus effort and accelerate fixes

Once stability is established, the challenge shifts. At AI speed, organizations cannot afford to treat all risk equally. Security must focus its efforts where they matter most, quickly and confidently fixing issues where developers work.

In this act, security moves from detection to measurable risk reduction. Noise is reduced, prioritization reflects real-world impact, and remediation accelerates without increasing friction for development teams.

Phase 3: Scale - govern, prove, and orchestrate

Optimization alone is not enough. Act 3 is about scaling security outcomes with confidence–ensuring governance, measurement, and automation reinforce each other as AI-driven development expands across teams, applications, and agents.

Governance is not the destination; it is the control plane that enables scale. Measurable standards, auditable decisions, and clear proof of impact are what allow security programs to expand without slowing innovation.

As security scales, organizations move beyond manual and assisted workflows into orchestrated, autonomous defense. Orchestration is where security becomes adaptive and reaches the required machine-speed to observe, decide, and act across AI-native and agentic systems without reintroducing friction or risk.

Building trust at AI speed

AI is rewriting how software is created by humans, models, and autonomous agents working together at unprecedented speed. That shift is irreversible. The question is no longer whether organizations will adopt AI, but whether they will do so with trust. Security can’t remain reactive in this world. It must be woven into creation itself, operating continuously, enforcing guardrails early, and adapting as systems evolve.

That is the promise of the AI Security Fabric. The Snyk AI Security Platform delivers it in practice, and the Prescriptive Path shows how organizations can operationalize it, step by step, as AI adoption accelerates.

By fortifying DevSecOps foundations, securing AI-driven development at inception, and preparing for the rise of AI-native applications, organizations can move beyond managing risk to architecting trust. 

This is how teams stop having to choose between speed and security. This is how AI innovation scales responsibly. And this is how the future of software is built - securely, by design.

Take the next step

Whether you’re just beginning to secure AI-driven development or preparing for AI-native systems, the next step is turning strategy into action.

• Sign up for Snyk’s launch event on February 11 to learn more about how the Snyk AI Security Platform delivers the AI Security Fabric - and how the Prescriptive Path helps organizations operationalize AI security with confidence.

• Take the Prescriptive Path to explore the practical framework for operationalizing AI security - from foundation to frontier.