AWS Databases on Vercel now available in additional AWS Regions

Amazon Aurora PostgreSQL, Amazon Aurora DSQL, and Amazon DynamoDB serverless databases are now available on Vercel Marketplace and v0 by Vercel in additional AWS Regions, offering you more flexibility to build applications with Vercel and AWS databases from the Regions of your choice. To get started, you can describe your idea in v0 using natural language. The tool automatically generates a spec-driven design, deploys code and infrastructure, and stores your application data in the AWS database that best fits your needs with no hands-on coding or provisioning required. Vercel provides an end-to-end setup experience where you can create database resources in seconds under a new AWS account or link to an existing one, all without leaving Vercel. New AWS accounts created from Vercel include access to all three databases and $100 USD in credits, usable across any of these database options for up to six months. You can manage your plan, add payment information, and view usage details anytime from the AWS settings portal in the Vercel dashboard. To learn more, visit v0 or the AWS landing page on the Vercel Marketplace. You can now create an Aurora PostgreSQL database or Amazon DynamoDB table through Vercel from 17 AWS Regions enabled by default, and Aurora DSQL from 16 AWS Regions including: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Osaka), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), and South America (São Paulo). AWS Databases deliver security, reliability, and price performance without the operational overhead, whether you’re prototyping your next big idea or running production AI and data driven applications. For more information, visit the AWS Databases webpage.
Quelle: aws.amazon.com

Amazon EKS Capabilities now supports Amazon CloudWatch Vended Logs

Amazon Elastic Kubernetes Service (Amazon EKS) Capabilities can now be configured as log delivery sources using Amazon CloudWatch Vended Logs. This enables customers to monitor and troubleshoot their EKS Capabilities for Argo CD, AWS Controllers for Kubernetes (ACK), and kro (Kubernetes Resource Orchestrator) by monitoring logs collected from the managed controllers that run in AWS-managed infrastructure. Customers can enable log delivery for each capability using CloudWatch APIs or the AWS Console. Logs are configured as a CloudWatch Vended Logs delivery source, enabling reliable, secure log delivery to CloudWatch Logs, Amazon S3, or Amazon Kinesis Data Firehose destinations. This feature is available in all AWS Regions where the EKS Capabilities feature is supported. Standard CloudWatch Vended Logs pricing applies based on the chosen destination. There is no additional EKS charge. To learn more about EKS Capabilities, visit the Amazon EKS documentation.
Quelle: aws.amazon.com

Amazon SageMaker Data Agent integrates business context into conversations

Amazon SageMaker Data Agent now integrates with SageMaker Catalog business context and metadata, enabling data practitioners to discover datasets and generate more accurate SQL and Python code using business terminology instead of cryptic technical table names. This integration allows the Data Agent to leverage the business context that companies have invested months curating in their SageMaker Catalog, including those synced from Collibra, Atlan, and Alation, to deliver more accurate data discovery and code generation.
With this capability, data practitioners can ask questions like “Calculate customer retention rate” or “What data do I have on customer churn?” and the Data Agent will search glossary terms, custom metadata forms, asset summaries, and README content to identify the correct tables and columns. The agent generates more accurate code on first attempt by understanding business context, plans multi-step workflows with the correct sequence of tables and transformations, and respects data governance by checking subscription status and providing access request links when needed. Organizations maximize their existing catalog investment without changing the current data workflows, reducing time-to-insight, and enabling data teams to work in business language rather than deciphering technical table names.
This integration is available in SageMaker Unified Studio notebooks and Query Editor in all AWS Regions where Amazon SageMaker Unified Studio is available. To learn more, visit the Amazon SageMaker Unified Studio page and Amazon SageMaker Data Agent documentation.
Quelle: aws.amazon.com

What is Software Supply Chain Security?

Software supply chain attacks have accelerated faster than most security teams anticipated. Sonatype’s 2026 State of the Software Supply Chain report identified more than 454,000 new malicious packages published to open source repositories in 2025, bringing the cumulative total to over 1.2 million since 2019. The blast radius keeps expanding as organizations consume more open source software, ship more container-based workloads, and distribute software through increasingly complex pipelines.

Software supply chain security is the discipline of protecting every component, process, and system involved in building and delivering software, from the source code developers write to the dependencies they pull in, the build systems that compile and package their code, the registries that store their artifacts, and the infrastructure that runs those artifacts in production. It’s a lifecycle concern, not just a deployment-time check.

What makes this discipline distinct from traditional application security is the scope. Application security focuses on the code your team writes. Supply chain security focuses on everything your code depends on, and everything that touches your code on its way to production. For container-based delivery pipelines, that means every base image, every package, every build tool, and every registry interaction is part of the attack surface.

Key takeaways

Supply chain security protects every stage from source code and dependencies through build, registry, and production deployment.

Modern software is assembled from hundreds of packages, and any one can introduce vulnerabilities that propagate downstream.

Effective programs start with trusted content (verified images, signed artifacts, SBOMs) enforced at every pipeline stage.

Treat supply chain security as an infrastructure discipline, not a compliance checkbox, to catch threats early and respond faster.

Why software supply chain security matters now

The urgency behind software supply chain security is driven by a structural shift in how software is built. Modern applications are overwhelmingly assembled from existing components rather than written from scratch. A typical container image contains hundreds of packages, each with its own dependency tree, maintainers, and update cadence. Every one of those components is a trust decision, and most organizations are making those trust decisions implicitly rather than deliberately.

The dependency problem is a trust problem

When a developer adds a package to a project, they’re trusting that the package does what it claims, that the maintainers are who they say they are, the package registry has not been compromised, and the package will continue to receive security updates. Multiply that trust decision across every dependency in every container image across an organization, and the scale of implicit trust becomes clear.

Attackers have recognized that compromising a single widely used package can give them access to thousands of downstream organizations. Techniques like dependency confusion, typosquatting, and maintainer account takeovers have become standard tools in the attacker playbook. The impact of software supply chain attacks extends well beyond the initial compromise, propagating downstream through every organization that consumes the affected component. The software supply chain has become the preferred vector precisely because the trust relationships are implicit and the verification infrastructure is often absent.

Containers changed the attack surface

Container security has always been a multi-layered concern, but containerization accelerated the supply chain security challenge in ways that are still catching up with many organizations. A container image is a complete, immutable software artifact that bundles application code with its operating system dependencies, runtime, and configuration. That immutability is a security advantage because what you test is exactly what you deploy. But it also means every vulnerability in every layer of that image ships to production unless you’re actively scanning, verifying, and updating.

The container registry has become one of the most critical points in the supply chain. It’s where images are stored, distributed, and pulled for deployment. If an attacker can push a tampered image to a registry, or trick a deployment pipeline into pulling an unverified image, the compromise reaches production without triggering any code-level security controls. Registry security, image signing, and pull policies are supply chain security concerns that did not exist before containerized delivery became the default.

Regulatory pressure is accelerating

Government and industry mandates are making supply chain security a compliance requirement, not just a best practice. Executive Order 14028 on Improving the Nation’s Cybersecurity requires US federal software suppliers to meet specific supply chain security standards, including SBOM generation and secure development practices. The NIST Secure Software Development Framework (SSDF) provides the reference architecture. And SLSA (Supply-chain Levels for Software Artifacts) offers a graduated framework for verifying that artifacts were built securely.

These frameworks are not just government requirements. They’re shaping procurement standards across industries. Modern software is overwhelmingly assembled from open source components, and those components frequently carry known vulnerabilities. Organizations that cannot demonstrate supply chain integrity through provenance attestations, SBOMs, and verifiable build processes are increasingly locked out of enterprise and public-sector contracts.

How software supply chain security works

Supply chain security is not a single tool or practice. It’s a set of controls applied at every stage of the software delivery pipeline. Each stage has distinct attack surfaces and requires specific protections.

Securing source code and dependencies

The supply chain starts where the code starts. Source code repositories need access controls, commit signing, and branch protection rules that ensure only authorized changes make it into the codebase. But the bigger risk is usually in dependencies, not the first-party code itself.

Dependency management for supply chain security goes beyond keeping packages updated. It includes verifying that packages come from trusted sources, that they have not been tampered with since publication, and that their transitive dependencies (the packages your packages depend on) are also trustworthy. Lockfiles, hash verification, and dependency pinning are baseline controls. Private registries and curated package feeds add a layer of organizational control over what enters the dependency tree.

Securing the build process

The build system is where source code and dependencies are transformed into deployable artifacts. A compromised build environment can inject malicious code into every artifact it produces, regardless of how clean the source code is. Build integrity means running builds in isolated, ephemeral environments that start clean every time, producing provenance attestations that record exactly what was built, with what tools, from what source, and generating SBOMs that provide a complete inventory of every component in the final artifact. It’s one of the hardest stages to secure because the compromise is invisible at the source code level.

SLSA framework levels provide a useful maturity model here. At SLSA Build Level 3, the build process runs on a hardened build platform, the provenance is non-falsifiable, and the build platform isolates each build to prevent tampering between runs. This is where hardened, provenance-verified images become essential, providing cryptographic proof of how each image was produced.

Securing container images and registries

Container images are the primary delivery artifact in modern supply chains, which makes image security a central supply chain concern. Securing images starts with the base image. If the foundation is unverified, outdated, or bloated with unnecessary packages, every image built on top of it inherits those risks.

Trusted base images are minimal, regularly rebuilt against upstream security fixes, and distributed with verifiable provenance. They come with SBOMs that document every package included, vulnerability scan results that are transparent rather than suppressed, and cryptographic signatures that let consumers verify the image has not been tampered with since it was built. 

That transparency distinction matters: some image providers suppress or downplay vulnerability data to make their scan results look cleaner. A genuinely trusted image shows you everything, including what has not been patched yet, so your team can make informed decisions rather than operating on incomplete information.

Registry security involves controlling who can push and pull images, enforcing image signing policies, scanning images for vulnerabilities before they are deployed, and maintaining audit trails of every registry interaction. Organizations that treat their container registry as a trusted source of truth rather than a dumping ground for artifacts are materially better positioned to prevent supply chain compromises.

Securing deployment and runtime

The final stages of the supply chain are deployment and runtime. Deployment controls ensure that only verified, signed images from trusted registries are pulled into production environments. Admission controllers, image verification policies, and deploy-time SBOM checks create enforcement points that prevent unverified artifacts from reaching production.

Runtime security adds the last layer of defense. Even with a fully secured build and deployment pipeline, runtime monitoring detects anomalous behavior that might indicate a compromised component: unexpected network connections, unusual file system access, or processes that should not be running. Sandboxed execution environments provide isolation that limits the blast radius if a compromised component makes it past earlier controls.

The role of SBOMs in supply chain security

A Software Bill of Materials (SBOM) is a machine-readable inventory of every component in a software artifact: packages, libraries, versions, licenses, and their relationships. In the context of supply chain security, SBOMs serve as the transparency layer that makes everything else possible. You cannot verify what you cannot see, and SBOMs make the contents of software artifacts visible.

What distinguishes SBOMs as a supply chain security tool from SBOMs as a compliance artifact is how they’re generated and used. A compliance-oriented SBOM is generated once, filed away, and referenced during audits. A security-oriented SBOM is generated automatically with every build, attached to the artifact it describes, and consumed by automated tools that check for known vulnerabilities, license conflicts, and policy violations before the artifact reaches production. As GitHub’s analysis of vulnerability trends shows, the volume of published CVEs continues to grow each year, making automated SBOM-driven scanning essential rather than optional.

The most effective supply chain security programs treat SBOMs as living artifacts that travel with the software they describe. When a new vulnerability is disclosed, the SBOM lets you answer immediately: are we affected, where, and in which deployed artifacts? That response time is the difference between a controlled remediation and a scramble. For a deeper look at implementation, see our guide on software supply chain security best practices.

4 Common software supply chain attack vectors

Understanding how supply chains are attacked is essential to understanding how to defend them. Attack vectors target different stages of the pipeline, and each requires specific controls.

1. Dependency-based attacks

These target the packages and libraries your software depends on. Dependency confusion exploits the way package managers resolve names, tricking build systems into pulling a malicious public package instead of a legitimate private one. Typosquatting registers packages with names similar to popular libraries, banking on developer typos. Maintainer account takeovers compromise the credentials of a trusted package maintainer and push malicious updates through the legitimate distribution channel.

2. Build system compromises

Attackers who compromise a build system can inject code into every artifact it produces. This is particularly dangerous because the source code remains clean, and code review will not catch the compromise.

3. Image and registry attacks

Container-specific attack vectors include pushing tampered images to public registries, creating malicious images with names that mimic popular official images, and exploiting misconfigured registry access controls to replace legitimate images with compromised ones. Organizations without image signing verification and registry access management policies are particularly vulnerable to these vectors.

4. CI/CD pipeline exploitation

CI/CD pipelines often have elevated privileges (access to secrets, deployment credentials, production environments) that make them high-value targets. Attackers exploit pipeline configurations to exfiltrate secrets, modify build outputs, or inject steps that execute during otherwise legitimate workflows.

The rise of AI coding agents adds a new dimension to this threat: agents that generate code or modify dependencies can introduce supply chain risks at machine speed if they are not operating within secure, isolated environments. Poisoned pipelines are especially dangerous because they can produce artifacts that pass all automated security checks while carrying malicious payloads.

Core principles of software supply chain security

Effective supply chain security programs share a set of principles that guide both technical implementation and organizational culture.

Principle

What this means in practice

Verify, don’t assume 

Every component, dependency, and artifact should be cryptographically verified before it’s consumed. Build verification into the pipeline rather than relying on assumptions about source integrity, maintainer identity, or registry trustworthiness. 

Start with trusted content

The base images and packages at the foundation of your supply chain determine the security posture of everything built on top of them. Hardened, minimal, provenance-verified base images reduce the attack surface at the root.

Verify at every transition

Each time an artifact moves from one stage to another (source to build, build to registry, registry to deploy), verify its integrity. Signing, attestation, and hash verification at transition points prevent tampered artifacts from propagating.

Generate transparency artifacts automatically

SBOMs, provenance attestations, and vulnerability scan results should be generated automatically as part of the build process, not manually or after the fact.

Enforce policy at the infrastructure level

Supply chain security policies (which registries are allowed, which images can be deployed, what vulnerability thresholds are acceptable) should be enforced by infrastructure, not by process documentation.

Minimize the blast radius

Assume that some component will eventually be compromised and design your pipeline to limit the damage. Least-privilege access, isolated build environments, and runtime sandboxing reduce the impact of any single compromise.

Building a software supply chain security program

Moving from ad hoc security practices to a structured supply chain security program involves layering controls at each stage of the pipeline. The goal is not to implement everything at once but to establish a foundation and build on it as the organization matures.

1. Establish a trusted image foundation

The single highest-leverage action most organizations can take is to control what goes into their base images. If developers are pulling arbitrary images from public registries without verification, every other supply chain security investment is built on an unstable foundation.

A trusted image foundation means maintaining a curated set of approved base images that are minimal (reducing attack surface), regularly rebuilt (incorporating upstream fixes), and distributed with provenance attestations and SBOMs. 

The good news is that you do not have to build this from scratch. Hardened, continuously rebuilt base images with SLSA Build Level 3 provenance and full vulnerability transparency can be used as drop-in replacements for standard images, so teams can adopt them without reworking existing CI/CD pipelines.

2. Implement SBOM generation and consumption

SBOMs should be generated automatically as part of every build pipeline, attached to the artifacts they describe, and consumed by automated tools that check for vulnerabilities and policy violations. The two standard SBOM formats, SPDX and CycloneDX, are both widely supported by scanning and policy tools. Choose one and standardize across the organization.

3. Deploy image signing and verification

Image signing creates a cryptographic chain of trust between the entity that built an image and the environment that deploys it. Signing keys should be managed centrally, signing should happen automatically as part of the build pipeline, and verification should be enforced at deployment time through admission controllers or registry policies. If an image is not signed by a trusted key, it should not reach production.

4. Enforce registry and image access policies

Control which registries developers and deployment pipelines can pull from. Block access to unapproved public registries and enforce policies that require images to come from verified sources. For Docker Desktop, Registry Access Management provides these controls, ensuring policies are enforced consistently across developer workstations, not just in CI/CD.

5. Integrate vulnerability scanning into the pipeline

Scanning should happen at multiple points: 

When dependencies are added

When images are built

When images are pushed to registries

On a continuous basis for deployed artifacts

The goal is to catch vulnerabilities as early as possible in the pipeline, when remediation is cheapest and least disruptive. You’ll want continuous vulnerability analysis integrated directly into the developer workflow so issues are surfaced where engineers can act on them, rather than buried in a security dashboard that rarely gets checked.

6. Establish incident response for supply chain compromises

Supply chain incidents are different from typical security incidents because the compromise often originates outside the organization. Your incident response plan should account for scenarios where a trusted dependency is compromised, where a base image contains a newly disclosed vulnerability, or where a build system produces artifacts that cannot be verified. 

The faster you can identify which deployed artifacts are affected (this is where SBOMs pay for themselves), the faster you can respond.

Where does your supply chain security stand?

Supply chain security maturity varies widely across organizations. Use this self-assessment to identify where your organization falls and what to prioritize next.

Frameworks and standards

Several frameworks provide structured approaches to supply chain security. They’re complementary rather than competing, and mature organizations typically align with multiple frameworks.

SLSA (Supply-chain Levels for Software Artifacts)

SLSA provides a graduated framework for verifying the integrity of software artifacts. Its build levels establish increasingly rigorous requirements for how artifacts are produced, from basic build provenance at Level 1 to hardened build platforms with non-falsifiable provenance at Level 3. SLSA is particularly valuable because it translates abstract supply chain security goals into concrete, verifiable technical requirements.

NIST SSDF (Secure Software Development Framework)

The NIST SSDF (SP 800-218) provides a comprehensive set of secure development practices organized around four practice groups: Prepare the Organization, Protect the Software, Produce Well-Secured Software, and Respond to Vulnerabilities. It’s the primary reference framework for federal software supply chain requirements under Executive Order 14028.

OpenSSF Scorecard and GUAC

The Open Source Security Foundation provides tools for evaluating the security posture of open source projects (Scorecard) and for aggregating and querying supply chain metadata (GUAC, Graph for Understanding Artifact Composition). These tools help organizations make informed decisions about which open source components to trust.

Getting started

Supply chain security is an infrastructure discipline. The organizations that approach it as a set of pipeline controls rather than a compliance checklist are the ones building the most resilient software delivery systems. The practices in this guide are designed to be layered incrementally. If your organization is starting from scratch, begin with the highest-leverage action: establish a trusted image foundation. Control what goes into your base images, generate SBOMs automatically, and enforce verification at every pipeline stage from there.

Docker Hardened Images provide a production-ready foundation with SLSA Build Level 3 provenance, continuous vulnerability monitoring, and cryptographic signatures that verify integrity from build to deployment. Combined with Docker Scout for continuous vulnerability analysis and Registry Access Management for policy enforcement, teams can create an infrastructure layer for supply chain security across their full delivery pipeline.

Explore our full catalog of hardened images and start replacing your base images today.

Frequently asked questions

What is software supply chain security?

Software supply chain security is the practice of protecting every component and process involved in building and delivering software. This includes the source code, open source dependencies, build systems, container images, registries, and deployment pipelines. The goal is to ensure that every artifact deployed in production is exactly what it claims to be, has not been tampered with, and is free of known vulnerabilities. It’s a lifecycle discipline, not a single tool or checkpoint.

Why is software supply chain security important?

Modern software is assembled from hundreds or thousands of open source components, each with its own maintainers, vulnerabilities, and update cadences. A single compromised component can propagate through the entire delivery pipeline and into production. Supply chain attacks have increased significantly because they allow attackers to reach many downstream organizations by compromising a single upstream dependency or build system.

What is the difference between software supply chain security and application security?

Application security focuses on vulnerabilities in the code your team writes: injection flaws, authentication bugs, authorization issues. Supply chain security focuses on everything your code depends on and everything that touches it on the way to production. The distinction matters because most code in a modern application is not written by the team deploying it. It’s pulled in from open source libraries, base images, and system packages.

What is an SBOM and why does it matter for supply chain security?

An SBOM (Software Bill of Materials) is a machine-readable inventory of every component in a software artifact. It matters because you cannot secure what you cannot see. SBOMs enable automated vulnerability scanning, license compliance checking, and rapid incident response when a new vulnerability is disclosed. When generated automatically with every build and attached to the artifact, they provide a continuous transparency layer across the entire supply chain.

How do container images relate to supply chain security?

Container images are the primary delivery artifact in containerized supply chains. They bundle application code with all of its dependencies, making them a complete representation of everything that will run in production. This makes image security a central supply chain concern: the base image you start from, the packages you add, and how the image is signed, stored, and verified all directly impact supply chain integrity.

What frameworks should I follow for software supply chain security?

The most widely adopted frameworks are SLSA (Supply-chain Levels for Software Artifacts) for build integrity, NIST SSDF (SP 800-218) for secure development practices, and the OpenSSF Scorecard for evaluating open source dependencies. Executive Order 14028 mandates NIST SSDF alignment for federal software suppliers, and its requirements are increasingly adopted as industry standards.

Quelle: https://blog.docker.com/feed/

Hardened Images Explained: Fewer CVEs, Smaller Attack Surface

When security teams scan their container environments for the first time, they often discover hundreds of known vulnerabilities, and almost none of them trace back to application code.

The overwhelming majority come from packages that shipped with the base image: shells, compilers, debug utilities, and libraries the application never calls. In a software supply chain built on containers, the base image is the foundation. If that foundation ships with unnecessary components, every workload built on top of it inherits the risk.

Hardened images address this problem at the source. They are purpose-built base images stripped down to only the runtime components an application needs, continuously patched, and shipped with verifiable metadata that lets security teams confirm exactly what is inside and how it was built.

Key takeaways

Most container vulnerabilities come from unnecessary packages inherited from base images, not from application code.

Hardened images strip out everything a containerized application does not need, reducing attack surface by up to 95%.

Beyond minimization, hardened images include verifiable supply chain metadata: SBOMs, build provenance, and exploitability data.

Container hardening differs from VM hardening; it focuses on image contents and build integrity, not OS-level configuration benchmark.

Why standard container images carry hidden risk

A general-purpose base image like a standard Linux distribution might ship with 400 or more installed packages. A typical containerized application uses 20 to 30 of them. The rest are inherited baggage: package managers, text editors, network diagnostic tools, documentation files, and libraries for use cases the container was never intended to serve.

Each of those unused packages is a potential attack surface. Vulnerability scanners flag them because they are genuinely present in the image, even if the application never imports or executes them. The result is a signal-to-noise problem that burns through security team capacity. When a team faces 200 findings and 80% of them exist in packages no running workload touches, the real vulnerabilities that need immediate attention get buried in triage.

The packages themselves are the other half of the problem. A shell in a production container gives an attacker an interactive environment to work from if they achieve initial access. A package manager lets them install additional tooling. Debug utilities help them map the network and identify lateral movement targets. None of these belong in a production container, but they ship by default in most general-purpose base images, quietly expanding the blast radius of any breach.

What makes a container image “hardened”

So what are hardened images in practice? Minimization gets the most attention, but it’s only one of three requirements. A genuinely hardened image is also continuously maintained and independently verifiable.

Quick definition: Hardened images are minimal, continuously patched base images that ship only the runtime components an application needs, paired with verifiable supply chain metadata like SBOMs, build provenance, and cryptographic signatures.

Minimized attack surface

The most visible characteristic of a hardened image is minimization. Shells, package managers, and debug tools are removed. Only the runtime components the application needs to function are included. This is more aggressive than simply choosing a slim base image variant. Hardened images are often rebuilt from the package level up, selecting each component deliberately rather than subtracting from a general-purpose distribution.

The result is a dramatically smaller CVE surface. Where a general-purpose image might carry hundreds of known vulnerabilities, a hardened equivalent for the same runtime typically carries single digits or none.

Continuous patching and rebuilds

A hardened image that’s never updated becomes a snapshot of the day it was built. An image hardened on Tuesday can start drifting by Friday: three upstream CVEs published, two library patches released, and the image is already accumulating the kind of exposure it was designed to prevent.

Security requires ongoing maintenance: monitoring upstream projects for fixes, rebuilding images to incorporate patches, and doing this on a defined cadence with clear SLAs. The best hardened images are rebuilt continuously, not on a quarterly or release-driven schedule. That’s what separates production-grade hardened images from one-time efforts to slim down a Dockerfile.

Verifiable supply chain metadata

This is where hardened images connect to the broader supply chain security best practices that organizations are adopting. A truly hardened image ships with:

Software Bills of Materials (SBOMs) that list every package, version, and dependency in the image

Build provenance attestations aligned to frameworks like SLSA, providing cryptographic proof of how and where the image was built

Vulnerability Exploitability eXchange (VEX) data that identifies which CVEs present in the image are not exploitable given how the software is actually configured

Cryptographic signatures that verify the image has not been tampered with between build and deployment

This metadata is what makes automated policy enforcement possible in CI/CD pipelines. A CI gate that blocks deployments unless the base image has a signed SBOM and valid provenance attestation is only feasible when the image provider builds that metadata into the supply chain from the start. For organizations operating in regulated environments, it’s also what allows security and compliance teams to verify an image without reverse-engineering its contents.

Container hardening vs. VM hardening

The term “hardened image” appears in both container and virtual machine contexts, but the two practices address different layers of the stack.

VM hardening focuses on OS configuration: disabling unnecessary services, tightening firewall rules, restricting user permissions, and tuning kernel parameters. Defined by frameworks like CIS Linux Benchmarks. Takes a full operating system and locks it down.

Container hardening operates at the image layer: what is packaged (minimization), how the image was assembled (provenance), and whether the contents are transparent (SBOMs and vulnerability data). Starts from a minimal foundation and builds up only what the application requires.

Both practices are valid and often coexist. Many organizations apply VM hardening to their container host nodes and container hardening to the images running on those nodes. They complement each other, but the techniques, tooling, and evaluation criteria are different. A CIS-hardened AMI and a hardened container base image solve distinct problems at distinct layers.

How to evaluate hardened images

Not all images marketed as hardened meet the same standards. When evaluating options, look for these characteristics:

Transparency: Can you see every package in the image? Is there a complete, machine-readable SBOM?

Provenance: Can you independently verify how and where the image was built? Are attestations signed and aligned to a recognized framework?

Patch cadence: How quickly are upstream security fixes incorporated? Is there a defined SLA, or is patching best-effort?

Compatibility: Do the images work as drop-in replacements in existing Dockerfiles and CI/CD pipelines, or do they require workflow changes?

Vulnerability data integrity: Does the provider suppress or filter CVE data to make the image look cleaner, or do they publish full vulnerability transparency with exploitability context?

The answers to these questions separate genuinely hardened images from images that are simply minimal. Minimization is necessary but not sufficient. Without provenance, patching discipline, and transparency, a small image is just a smaller attack surface with less visibility.

What hardened images are not

The term “hardened” is sometimes applied loosely. Because of this, it’s worth clarifying what does not qualify, because each of these approaches solves part of the problem while leaving the rest exposed.

Choosing a slim or Alpine variant reduces image size, but it does not address provenance, patching cadence, or supply chain metadata. The image is smaller, not hardened.

Running a scanner and manually removing flagged packages produces a point-in-time fix, not a continuously maintained hardened image. The next upstream CVE puts you back where you started.

Building a distroless image from scratch achieves minimization but requires significant ongoing effort to maintain patch currency across every image in a portfolio. Without a defined rebuild cadence and verifiable metadata, the maintenance burden scales with the number of images.

Hardening, in the supply chain security sense, means all of these concerns are addressed systematically: the image is minimal, maintained, and verifiable.

Getting started with hardened images

Hardened container images are becoming the standard foundation for secure container deployments. They address the root cause of most container vulnerability findings: unnecessary packages inherited from general-purpose base images. And with verifiable supply chain metadata, they give security teams the transparency and audit trail that modern compliance requirements demand.

Docker Hardened Images provide this foundation across several thousand images spanning runtimes, frameworks, databases, and infrastructure components. Every image ships with SBOMs, SLSA Build Level 3 provenance, VEX data, and cryptographic signatures. The Community tier is free and open under Apache 2.0 with no restrictions on use or redistribution.

Explore our full catalog of hardened images and start replacing your base images today.

Frequently asked questions

What is the difference between a hardened image and a minimal image?

A minimal image has fewer packages, but that’s only one dimension of hardening. A hardened image also includes continuous patching with defined SLAs, verifiable build provenance, complete SBOMs, and vulnerability exploitability data. Minimization reduces the attack surface; hardening ensures the remaining surface is maintained, transparent, and verifiable.

Do hardened images work with existing CI/CD pipelines?

Well-designed hardened images are built to serve as drop-in replacements for standard base images. If your Dockerfile starts with a general-purpose runtime image, you can typically swap in a hardened equivalent without changing your build process. The key consideration is shell access: some hardened images remove shells entirely, which means build steps that rely on shell commands may need adjustment for multi-stage builds.

How do hardened images reduce CVE counts?

Every package in a container image is a potential source of CVEs. By removing packages the application does not need, hardened images eliminate the vulnerabilities those packages carry. A general-purpose base image with 400 packages might have 200 known CVEs. A hardened equivalent with 30 packages might have fewer than 5, because the vast majority of vulnerable components were never included. This significantly shrinks the surface an attacker can target and reduces the triage burden on security teams.

Quelle: https://blog.docker.com/feed/