A container security assessment is a structured review of your images, registries, orchestration configuration, and runtime behavior against known weaknesses, done deliberately so you find the gaps before an attacker does. It is not a single scan; it is a repeatable process across four layers, and this guide gives you a concrete checklist for each one.
Layer 1: the image
Everything starts with what is inside the image. A thorough assessment of an image covers:
- Known vulnerabilities in the OS packages and application dependencies, matched against public advisory databases.
- Malicious or unexpected content such as backdoors, cryptominers, or binaries that have no business being there.
- Secrets baked into layers like API keys, private certificates, or database passwords.
- Base image hygiene including whether it is minimal, pinned by digest, and still maintained upstream.
# Scan an image for known-vulnerable packages
trivy image --severity HIGH,CRITICAL myorg/api:latest
The transitive dependency graph is where surprises hide. A vulnerability three levels deep in a package you never explicitly installed is exactly what a manual review misses, which is why an automated SCA pass belongs in this step.
Layer 2: the registry and build pipeline
An assessment that stops at the image ignores how the image got there. Check:
- Access control on the registry. Who can push? A registry that lets any CI job push over any tag is a supply chain risk.
- Image signing and provenance. Are images signed, and does the cluster verify signatures at admission?
- Build environment integrity. Is the pipeline that produces images itself hardened, or can a poisoned dependency in the build compromise every artifact?
- Tag immutability. Can someone overwrite
v1.2.3with different content after it shipped?
A signed, digest-pinned image from a locked-down registry is dramatically harder to tamper with than a mutable tag anyone can overwrite.
Layer 3: orchestration configuration
For most teams this means Kubernetes, and misconfiguration here is where a lot of real risk lives. The high-value checks:
- Containers running as root. Set
runAsNonRoot: trueand a non-zerorunAsUser. - Privileged containers and host mounts. A container with
privileged: trueor the host filesystem mounted is effectively running on the node. - Missing resource limits, which turn a single compromised or buggy pod into a noisy-neighbor or denial-of-service problem.
- Overly broad RBAC, especially service accounts with cluster-admin they do not need.
- Network policies. Without them, every pod can talk to every other pod, so one compromised workload reaches the whole cluster.
# A hardened securityContext for a pod
securityContext:
runAsNonRoot: true
runAsUser: 10001
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
capabilities:
drop: ["ALL"]
Run a benchmark tool such as kube-bench (which checks against the CIS Kubernetes Benchmark) to get a fast baseline of where your cluster stands.
Layer 4: runtime behavior
The first three layers are static. Runtime assessment watches what containers actually do once they are live:
- Does a container spawn an unexpected shell or process?
- Does it make outbound connections to addresses it never should?
- Does it write to directories that ought to be read-only?
Runtime security tools like Falco define rules over syscall activity and alert on deviations. Even a modest set of rules ("alert if a shell starts in a production container") catches a meaningful class of attacks that static scanning cannot see, because the malicious behavior only appears at execution time. A dynamic testing pass against the running application rounds this out by probing the exposed endpoints the way an attacker would.
Turning the assessment into a habit
A one-time assessment produces a snapshot that goes stale within days as new CVEs land and configs drift. The teams that stay ahead bake these checks into continuous pipelines: image scanning on every build, config policy checks on every manifest change, and runtime monitoring always on. The assessment then becomes the periodic deep review that validates the automation is actually catching things.
Score each finding by severity and exploitability so you fix the internet-facing root container before the theoretical issue in an internal batch job. A prioritized list of ten real risks beats an unranked list of a thousand.
FAQ
What does a container security assessment cover?
Four layers: the image contents (vulnerabilities, malware, secrets), the registry and build pipeline (access control, signing, provenance), orchestration configuration (Kubernetes RBAC, securityContext, network policies), and runtime behavior. Assessing only one layer leaves the others exposed.
What is the single highest-value fix in most assessments?
Stopping containers from running as root and dropping unnecessary Linux capabilities. Combined with network policies that limit pod-to-pod traffic, this removes some of the most common escalation paths after an initial compromise.
How often should I run one?
Continuous automated checks on every build and config change, with a deeper manual assessment quarterly or after major architecture changes. A static snapshot goes stale quickly as new vulnerabilities are disclosed.
Do I need runtime security if my images scan clean?
Yes. Clean images can still be exploited through an application flaw or a zero-day, and runtime monitoring is what catches the resulting anomalous behavior. Static scanning and runtime detection cover different stages of an attack.