Container Security Scanning: A Complete Guide to Prioritizing Your Findings

Container security scans usually consist of automated checks that tell you whether an image is safe to ship or if a container that's already running has drifted away from where it's supposed to be.

This guide walks through the mechanics of container security scanning: what a scan actually inspects, the types that cover images, cloud registries, and running containers, and a working setup for automating it in CI/CD.

It also covers how to prioritize what a scan finds, so a report full of known vulnerabilities doesn't just become noise your security team starts to ignore.

What is container security scanning?

Container security scanning is the (mostly) automated process of inspecting container images and running containers for known vulnerabilities, exposed secrets, and misconfigurations before and after they reach production.

 It's a check that catches an outdated package, a hardcoded API key, or a container running with more privileges than it needs, ideally before the risk becomes an incident.

Scanning can be separated into two broad categories:

1. Static scanning inspects a container image before it runs, comparing every package inside it against vulnerability databases.
2. Runtime scanning watches a container after it's live, flagging behavior that doesn't match what that container should be doing.

The two aren't interchangeable. A clean static scan only reflects what an image looked like at build time, but it gives no indication about what a container does once traffic starts hitting it.

Most container security programs use both, at different points across the container lifecycle, rather than treating a passing scan result as enough.

How container security scanning works

A scanning tool starts by unpacking a container image layer by layer—the same layers built and cached during a Docker build. From there, it builds or reads a software bill of materials listing every operating system package, language dependency, and library baked into the image, down to specific version numbers.

That list gets checked against vulnerability databases, most commonly the National Vulnerability Database and the GitHub Advisory Database, matching each package version against known CVEs.

If a scanner finds openssl 1.1.1a in a layer, it then checks that exact version against every disclosed vulnerability affecting that package, reporting back a severity score and, in tools with better remediation guidance, the version that actually fixes it.

What a scan actually checks

A single container security scan usually covers more ground than just known vulnerabilities:

• Known vulnerabilities. Outdated operating system packages and third-party libraries pulled in during a build, checked against public vulnerability databases.
• Embedded secrets. API keys, passwords, and tokens accidentally baked into an image layer, whether in a config file, an environment variable set at build time, or a leftover build log.
• Risky configuration. Ports left open unnecessarily, or a container configured to run as root when it doesn't need to.
• Malicious code. Signs that an image has been tampered with, or that it's one of the malicious container images uploaded to public registries under names designed to look legitimate.

None of these checks require the container to run. As a result, image scanning is cheap to run, but it's also a limiting factor: a scan only reports on what's present in the image, not on what a container does once it's live.

Types of container security scanning

An effective scanning strategy doesn't just consist of one check run once. It's a set of checks that apply at different points in a container's life, with each one catching something the others structurally can't.

Container image security scanning

Container image security scanning happens before deployment, against container images themselves rather than a running container.

It's static analysis: unpack the image, list what's inside, check it against known vulnerabilities. Base images, outdated packages, and third-party libraries get caught at this stage, and it's the cheapest point in the whole process to fix a problem, since nothing has shipped yet.

Using minimal base images makes your scans more efficient. A smaller image has fewer packages for a scanner to check and fewer places for a container vulnerability to hide. A full operating system base image scans slower and returns more findings than a distroless equivalent doing the same job.

Cloud container security scanning

Once an image moves into a cloud environment, scanning has to cover the registries and cloud workloads it passes through.

Most major cloud providers now bundle scanning into their container registries: images get scanned automatically as they're pushed, without a separate tool needed.

That native coverage is convenient, but it's also worth checking what it actually covers. Native cloud scanners are typically strong on known vulnerabilities and weaker on the secrets and configuration checks a dedicated scanning tool handles.

Cloud container security scanning has one gap that's easy to miss: short-lived cloud workloads. A container that spins up, does its job, and terminates within minutes can come and go faster than a periodic registry scan runs, meaning it's technically never scanned despite having been live.

To make sure containers don't slip through, scan at build time and enforce a policy before deployment – don't just rely on a scheduled registry scan alone.

Scanning running containers

Scanning running containers, or runtime scanning, watches active containers rather than static images.

It monitors containers for behavior a static scan can't predict, such as an unexpected process spawning, unusual file access, a network connection to somewhere that the container has no reason to reach, or a privilege change nobody approved.

Scanners can encounter configuration drift here too, when a container that started out locked down has quietly drifted toward a less secure state over weeks of small, individual, reasonable changes.

Runtime scanning and image scanning solve different problems. An image can pass every check at build time and still cause an incident months later that only runtime monitoring can catch. The vulnerability that caused it just hadn't been disclosed yet when the image shipped.

To observe container security best practices, run all the types of scans relevant to your use case.

How to automate container security scanning in CI/CD pipelines

You can't really scale manual scanning past a couple of images, largely because, to be effective, it depends on someone remembering to run it before every release. Automate container security scanning in your CI/CD pipeline to remove that dependency.

Set your process up to scan at three points:

• Pull request. A container vulnerability introduced in a code change gets flagged before it merges.
• Registry push. A merge and a release aren't always the same moment.
• Recurring schedule. Images already running in production get rescanned, since new vulnerabilities get disclosed in existing packages long after an image has shipped.

Here's a working example using GitHub Actions and Trivy, an open source scanning tool, that fails the build when it finds a critical vulnerability:

name: Container security scan

on: [pull_request]

jobs:

  scan:

    runs-on: ubuntu-latest

    steps:

      - uses: actions/checkout@v4

      - name: Build image

        run: docker build -t my-app:${{ github.sha }} .

      - name: Scan image

        uses: aquasecurity/[email protected]

        with:

          image-ref: 'my-app:${{ github.sha }}'

          severity: 'CRITICAL,HIGH'

          exit-code: '1'

The exit-code: '1' line means this is a gate rather than a report. If Trivy finds a critical or high vulnerability, the job fails, and the pull request can't merge until it's addressed.

That gate is as much a policy decision as a technical one. A blocking policy, where a critical finding stops the build outright, is worth having for anything customer-facing or that handles sensitive data.

A warn-only policy, where the scan reports but doesn't block, is a better fit for earlier-stage projects where blocking every merge on a default severity threshold would grind the team to a halt before it's tuned to your actual risk tolerance.

Most teams that succeed here start warn-only, tune out false positives over a few weeks, then flip to blocking once the noise is manageable.

Prioritizing what a scan finds

Run a scanner against almost any real-world container image, and it'll return a long list of known vulnerabilities, often numbering in the hundreds once every base image package and dependency is accounted for. Treating that list as a flat priority order, sorted by CVSS score alone, buries the handful of critical vulnerabilities that carry real risk beneath a load of findings that don't.

At this point, you need runtime context. Runtime data, meaning which packages are actually loaded into memory and reachable by the application code once a container is running, tells you which vulnerabilities in that long list represent real container risk and which ones sit in a code path nothing ever calls.

A critical vulnerability in a library that's present in the image but never imported by the running application carries a very different risk than the same severity score in a package handling every incoming request.

By prioritizing this way, you change what your security team actually looks at day to day. Instead of triaging a scan result top to bottom by severity, they can filter the list down to critical vulnerabilities that are both severe and fixable, – a shorter list and a far more useful one.

What to look for in container security scanning tools

Dokploy's best container security tools guide covers a full comparison of the key tools, but there are a few qualities worth watching out for regardless of which scanning tool ends up in your pipeline.

• Vulnerability database coverage. A scanning tool is only as current as the databases it checks against, and a stale one misses recently disclosed CVEs.
• Low false-positive rates. A scanner that buries real findings under noise trains a security team to stop reading its output.
• CI/CD integration. A scanning tool needs a clean path into GitHub Actions, GitLab CI, or whatever pipeline you already run, not a bolt-on step nobody maintains.
• Runtime context. Fewer tools do this well, but the ones that pull in runtime data to prioritize findings save users real time over a flat CVE list.

In the market, you'll find open source tools built around a single job, as well as full commercial platforms like Aqua Security or Anchore Enterprise that bundle scanning with registry controls and policy enforcement in one console.

The one you choose depends on whether your dedicated security team manages the tool, or whether it needs to run with minimal upkeep alongside everything else your small team is already responsible for.

Where Dokploy fits into container security scanning

Dokploy is a self-hostable deployment and application management platform that can work alongside a scanning tool, providing users with scan results somewhere concrete to act on before a deploy happens.

Dokploy's container registry integration connects to any Docker registry, including one that already scans on push, and stores those credentials centrally rather than re-entering them per project.

Deployments can be triggered through a webhook or the API, meaning a CI/CD pipeline can run its scan first and only call the deploy endpoint once that scan passes, instead of deploying on every push regardless of what the scan found – which makes a blocking policy enforceable.

Conclusion

Container security scanning isn't one check; it's a set of them covering the image, the registry, and the running container, with each catching something the others can't.

Getting real value out of your scanning involves automating the checks so they run on every build, and prioritizing what comes back using runtime context instead of a flat CVE list nobody has time to work through.

Sign up for Dokploy and connect your registry and CI/CD pipeline to see how it adds a deployment layer around the scanning tool you already run.

Container security scanning FAQs

Does container security scanning replace runtime security tools?

No. A scan, static or scheduled, reflects a point in time. Runtime security tools watch continuously for behavior a scan can't predict, like a process spawning that has no reason to exist.

How is container scanning different from general vulnerability scanning?

General vulnerability scanning often targets a whole network or host system. Container security scanning is scoped to what's inside an image or a running container, including layers, embedded packages, and secrets a broader network scan isn't built to inspect.

Is container security scanning required for compliance?

Most container-relevant compliance frameworks, including guidance tied to the CIS Benchmarks, expect some form of continuous scanning to demonstrate that known vulnerabilities are being tracked and addressed. Specific requirements vary by framework, so check the standard you're being measured against directly.