Modern software is assembled, not written from scratch. Applications are built from thousands of components, libraries, containers, packages, and models, collectively known as artifacts. To manage this sprawl, organizations rely on artifact repositories and registries: centralized systems that store, version, and distribute dependencies to developers, CI pipelines, and runtime environments. As teams adopt more languages, frameworks, and platforms, these repositories have expanded to support many formats and ecosystems at once, giving rise to what are often called universal artifact repositories, designed to act as a single system of record rather than a patchwork of language-specific tools.
Over the past few years, universal artifact repositories have evolved into sophisticated platforms. Many now offer integrated vulnerability scanning, license analysis, dependency governance, static analysis, infrastructure-as-code checks, and even AI-assisted remediation workflows.
These capabilities are valuable. They help teams understand what risks exist inside their artifact ecosystems and prioritize remediation across increasingly large dependency graphs. However, they also share a common architectural assumption: that artifact access is already centralized and consistently routed through the repository platform.
In modern CI/CD environments, that assumption rarely holds.
The Reality: Dependency access is more distributed than storage
Even in organizations with mature artifact management practices, dependency traffic is highly fragmented:
- CI runners often pull directly from public registries for speed or simplicity
- Ephemeral build agents come and go across regions and clouds
- New language ecosystems appear faster than platform controls can be enforced
- Developer tooling and automation bypass central repositories in early or experimental workflows
As a result, security controls that operate inside repository platforms may offer strong coverage in principle, but uneven enforcement in practice. The risk is not that the tools are ineffective. It is that they are not always on the path where execution actually happens.
Detection and remediation vs. inline control
Modern software supply-chain attacks rarely target application code directly. Instead, they exploit the implicit trust placed in third-party dependencies, compromising packages upstream, poisoning build inputs, or substituting malicious artifacts that are pulled automatically during CI/CD. Incidents such as dependency hijacking, typosquatting, and compromised package maintainers have shown how a single malicious artifact can propagate rapidly across fleets before it is detected.
To address this growing risk, repository-centric security platforms have evolved to provide deep visibility into the artifacts organizations consume. They focus on understanding what is in the supply chain and where risk exists within it.
Repository-centric security platforms excel at analysis:
- Identifying known vulnerabilities
- Enriching artifacts with metadata and risk context
- Prioritizing issues based on exploitability or business impact
- Guiding remediation once issues are discovered
What they typically do not control is the moment of execution.
Recent, publicly reported supply-chain incidents have demonstrated that compromise often occurs at the point where a dependency is fetched and immediately executed during a build or deployment. In one such case in 2025, attackers injected malicious code into dozens of widely used npm packages, collectively accounting for billions of weekly downloads, allowing malware to run during installation or CI workflows before traditional scanning could intervene.
The question becomes not just whether an artifact is risky in the abstract, but whether a specific request should be allowed at the moment it is made. Is the artifact expected, coming from the correct source, and being accessed under known conditions? And what happens if the upstream service is unavailable or compromised at the time the dependency is fetched?
Those questions require an inline control surface.
Virtual registries as an architectural complement
Virtual Registries do not replace artifact repositories or their security tooling. They augment them by introducing a consistent control plane at the point of artifact access.
By acting as a single logical entry point for dependency pulls, Virtual Registries enable inline enforcement before artifacts reach build environments, while applying consistent policy across registries, clouds, and toolchains. They introduce web-style resilience patterns such as caching and controlled failover, reducing dependency on live upstream services and limiting the blast radius of outages. At the same time, they provide unified observability into what artifacts are actually consumed in practice, not just what is stored.
In this model, repository platforms continue to perform deep analysis, scanning, and governance. Virtual Registries ensure those controls are applied everywhere dependencies flow, not just where repositories happen to be deployed.
From artifact analysis to dependency control
As software delivery becomes more distributed, security cannot stop at storage boundaries.
Just as web architectures evolved from backend-only security to include gateways, proxies, and edge controls, CI/CD architectures are evolving toward dependency access control as a first-class platform concern. The goal is not to replace existing repositories or security tools, but to ensure their policies and protections apply consistently wherever artifacts are actually consumed.
This is the architectural role Virtual Registries are designed to play. In practice, platforms like Varnish Orca sit in front of existing repositories and registries, acting as an inline control plane for artifact access. They enforce policy at request time, apply caching and resilience patterns, and provide visibility into real dependency usage without requiring changes to developer workflows or CI tooling.
The result is not more tooling, but a more coherent system, one where artifact security, availability, and governance extend beyond storage and into the delivery path itself, enforced where it matters most, at the point of use.
