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Container security is an end-to-end practice: secure the host and build process, control images and registries, restrict Kubernetes access and workload permissions, protect credentials, and watch for unexpected activity after deployment. The 2023 adoption figures below are historical survey results; operational guidance reflects Kubernetes documentation reviewed on September 30, 2026, alongside foundational NIST and CNCF guidance.
What is container security?
Container security is the set of controls used to protect containerized applications and the infrastructure that builds, stores, deploys, and runs them. NIST describes containers as “a form of operating system virtualization combined with application software packaging” in SP 800-190, Application Container Security Guide (September 2017).
A container packages an application and its dependencies, but it is not a complete virtual-machine boundary. Containers commonly share the host operating-system kernel, so a security plan must cover the host, container runtime, orchestration platform, application, and connections between them. CNCF implementation guidance also emphasizes patching and hardening the shared host.
That boundary makes container security a lifecycle concern, not simply a matter of scanning a Docker image or enabling a Kubernetes setting. A useful threat model identifies what must be protected, who or what can access it, and how a compromise could move between workloads or into the control plane.
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What did container-security trends look like in 2023?
The Cloud Native Computing Foundation’s 2023 survey reported broad container adoption alongside persistent security and skills challenges. These figures describe the survey population and year, not current adoption in 2026.
| 2023 finding | What the figure describes |
|---|---|
| More than 90% | Container use, including piloting or active evaluation, reported by the Cloud Native Computing Foundation in its 2023 survey. |
| 40% | Organizations that potentially or generally consume cloud services identified security as the leading challenge for container use or deployment, according to the Cloud Native Computing Foundation’s 2023 survey. |
| 84% overall: 66% in production and 18% evaluating | Potential or actual cloud-service consumers reported using or evaluating Kubernetes in the Cloud Native Computing Foundation’s 2023 survey. The survey excluded organizations whose primary revenue came from cloud-native products and services; its population differed from the 2022 sample, so the figures should not be treated as a direct year-over-year comparison. |
| 46% | Organizations that had not started or were just beginning their cloud-native journey cited lack of training as their biggest challenge in the Cloud Native Computing Foundation’s 2023 survey. |
The practical implication is that security controls need to fit ordinary delivery and platform operations. Teams also need enough training to understand findings, set workable policies, and respond when something goes wrong.
How do I secure a Docker container and its image?
Start before deployment. Image scanning can identify known vulnerabilities, but a finding is not a repair: someone must assess its relevance, update or replace the affected component, and confirm the result. CNCF TAG Security’s Cloud Native Security Whitepaper, version 2, recommends image scanning and hardening, artifact registries, and signing and trust.
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- Choose maintained base images. Use sources your organization trusts, track image provenance, and replace images that are no longer maintained.
- Reduce what the image contains. Remove unnecessary packages and avoid building in tools or permissions the application does not need.
- Scan and remediate. Run vulnerability checks in the build process, assign findings for review, and rebuild or update affected images rather than treating a scan report as remediation.
- Protect the registry. Limit who can publish, alter, or pull images according to job needs. Keep credentials out of image layers and build output.
- Sign and verify artifacts. Signing can help establish an image’s provenance and integrity; verification before deployment checks that the artifact meets the organization’s trust policy.
These controls work together: a signed image can still contain vulnerable software, while a clean scan does not establish who produced an image or whether it was changed after scanning.
How should I build security into CI/CD and deployment?
Run tests and policy checks early enough that developers can act on feedback, then check again at deployment. Earlier feedback complements runtime defenses; it does not replace them.
- Check the build. Scan images and dependencies, test the application, and apply the organization’s image-hardening requirements.
- Review deployment manifests. Validate the requested image, identity, permissions, and workload configuration against the team’s policy before release.
- Enforce policy at admission. Kubernetes admission controllers intercept API requests and can validate or mutate them. Use this point to reject requests that violate required controls or to apply approved defaults.
- Manage policy changes carefully. Test admission policies against the API versions and workloads in use. A policy that does not account for API changes can cause unintended deployment failures.
- Record decisions and exceptions. Keep an accountable path for reviewing exceptions so a temporary bypass does not silently become permanent.
How do I secure Kubernetes workloads and the cluster?
Kubernetes security spans the control plane, nodes, workload configuration, and network paths. The Kubernetes security documentation states, “A key security mechanism for any Kubernetes cluster is to control access to the Kubernetes API.” The precise defaults and available features can vary by Kubernetes release and managed distribution.
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Restrict control-plane access
Authenticate users and services that access the API, grant only the permissions they need, and limit who can administer the cluster. Kubernetes expects TLS for control-plane communications and supports encryption at rest for control-plane data; configure these protections to match the cluster and its data requirements.
Apply workload security settings
Use Kubernetes Pod Security Standards to set and enforce an appropriate baseline for pods. Avoid unnecessary privileges and capabilities. Where a workload needs stronger or custom isolation, assess whether a RuntimeClass is appropriate for the cluster and workload.
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Use network policies to define which pod-to-pod and pod-to-external connections are allowed. Set rules around actual application flows rather than assuming every workload needs unrestricted communication.
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How should I manage secrets in Kubernetes?
Inventory the credentials each workload needs, how they are issued, where they are stored, who can access them, and how they are rotated. Kubernetes Secrets are API objects intended for small sensitive values; workloads can consume them through mounts or environment variables. They are useful configuration objects, but they are not by themselves a complete secrets-management system for every environment.
- Do not hard-code credentials into source code, container images, or deployment manifests.
- Restrict access to Secret objects and to the workloads and identities that need them.
- Plan credential rotation and revocation, including how a workload receives updated values.
- Use an external secrets-management approach when cross-environment use, centralized lifecycle controls, or other requirements exceed what cluster-local handling provides.
CNCF’s container-security implementation guidance notes that Kubernetes Secret values are base64-encoded; base64 encoding is not encryption. Kubernetes documentation separately describes Secrets as basic protection for confidential configuration and documents control-plane encryption options. Treat storage, access, and encryption as separate parts of the control design.
What should I monitor after deployment?
Preventive checks cannot reveal every compromise or unexpected behavior. Monitor the control plane, nodes, container engine, workloads, middleware, and networking, and collect the logs, events, and metrics needed to investigate incidents. CNCF’s 2023 survey identified monitoring and observability as more challenging at large container scale; CNCF TAG Security also recommends ongoing monitoring and runtime detection.
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- Establish a response path for investigating alerts, isolating affected workloads, and replacing them when needed.
- Be able to trace an affected workload to its image and identify credentials that may need revocation or rotation.
How should I use container-security benchmarks?
NIST SP 800-190 provides application-container security recommendations and maps to control areas such as access control, configuration management, identification and authentication, incident response, and system integrity. CNCF TAG Security’s Cloud Native Security Whitepaper, version 2, cites NIST and CIS benchmarks as ways to test a hardened baseline. It says that adopting benchmarks helps teams test for a hardened baseline and deploy secure-by-default workloads, while cautioning that benchmarks cannot account for every data flow or customized platform use.
Use a benchmark to establish and assess a baseline, then adapt it to the application, data flows, platform, and threat model. A benchmark result is evidence about the checks it covers—not proof that a particular workload or organization is secure.
