Securing Kubernetes Pods: Challenges with Runtime Approach

For Kubernetes, the basic unit of execution is the pod, which encapsulates one or more containers sharing the same network namespace and storage volumes. While Kubernetes excels in orchestrating and scaling containerized workloads, it introduces significant runtime security concerns that are deeply rooted in its architecture. One of the most critical of these is how secrets and tokens are mounted into pods, often granting every binary in every container within the pod equal access. Securing Kubernetes pods thus requires more than just configuration hygiene—it demands a rethinking of runtime access models and attack surface reduction.

Equal Access: A Fundamental Risk

A standard Kubernetes pod may include multiple containers, each running various binaries. All these containers typically share volume mounts, which can include sensitive resources such as service account tokens and Kubernetes secrets. The problem is that Kubernetes does not natively differentiate which binaries should or should not have access to these sensitive resources. As a result, all running code inside a pod has potential access to them.

This model creates a broad attack surface. In fact, many Kubernetes-based attacks take advantage of this very principle. An attacker doesn’t need to compromise the whole system—just one binary with a vulnerability is enough. If any container in the pod is compromised, an attacker can inject malicious code and gain unrestricted access to the mounted secrets and tokens. This level of privilege makes lateral movement across the cluster significantly easier.

Why Runtime Controls Are Difficult

In theory, one could argue for limiting access at the process or binary level. Only specific binaries that absolutely need secret access should be able to reach the mount points where these secrets reside. However, enforcing this in practice is extremely challenging.

Firstly, the list of binaries requiring access can change frequently due to application updates. In modern DevOps environments, applications are often updated every few weeks, sometimes even daily. Each update can introduce new binaries, change execution paths, or alter the required access patterns. Therefore, any static allowlist quickly becomes obsolete, and manual updates are error-prone and unsustainable.

Secondly, containers are designed to be ephemeral and stateless. While this is a strength for scalability, it becomes a liability for enforcing fine-grained, stateful runtime security policies. Traditional access control models simply don’t map well to the dynamic and fast-changing nature of Kubernetes pods.

Runtime Security: Partial Solutions, Persistent Problems

Several tools have emerged to address runtime security for Kubernetes, including solutions like seccomp, AppArmor, SELinux, and eBPF-based monitoring tools. While they offer some level of control, they often require expert-level configuration and do not automatically adapt to application updates. Moreover, these tools generally focus on syscall filtering or behavioral monitoring rather than access control for secrets or service account tokens.

The ideal solution for securing Kubernetes pods would be a dynamic and automated framework that can determine which binaries within a pod need access to which secrets. This framework would need to analyze the application’s behavior during runtime, learn legitimate access patterns, and enforce least-privilege principles automatically. However, building such a solution at scale remains an ongoing challenge in the Kubernetes ecosystem.

Toward a More Secure Pod Architecture

Some proposed solutions suggest decoupling secret access from the pod entirely. For example, secrets can be accessed via external secret management systems (like HashiCorp Vault or AWS Secrets Manager) at runtime over encrypted channels, rather than being mounted into the pod file system. Other approaches include service meshes and sidecar containers that proxy and tightly control access to secrets, rather than exposing them to all processes.

Another promising direction involves using policy engines like Open Policy Agent (OPA) with tools like Gatekeeper to enforce more granular runtime policies. When combined with software supply chain tools (like SLSA or SBOMs), it becomes possible to establish and enforce trusted execution environments.

Conclusion

Securing Kubernetes pods is a complex task fraught with challenges, particularly at runtime. The core design of Kubernetes, which allows broad access to mounted secrets within a pod, leaves too much room for exploitation. While several tools and best practices exist to mitigate these risks, most fall short when applications are frequently updated and the attack surface shifts with each release. Addressing these issues will require a combination of runtime intelligence, automated policy enforcement, and rethinking how secrets are delivered to pods in the first place.

Learn more about AccuKnox
Website: https://accuknox.com/
Help Docs: https://help.accuknox.com/
Blogs: https://accuknox.com/blog
Get help with AccuKnox queries
Email: [email protected]
Slack: https://kubearmor.slack.com/
Policy Templates: https://github.com/kubearmor/policy-templates
——————————————————
Follow AccuKnox on social media
Twitter: https://twitter.com/accuknox
LinkedIn: https://www.linkedin.com/company/accuknox/
——————————————————
✅ Subscribe to Accuknox’s YouTube channel