Container scanning best practices for 2025

Key Takeaways

• Containers are scanned to identify potential security issues before they get deployed, including known vulnerabilities, misconfigurations, and compliance issues.
  
• Automating the container scanning process in CI/CD enables teams to identify issues early and significantly reduce production risk.
  
• Choosing the right scanner is crucial and requires evaluating accuracy, integration options, and support for compliance standards such as FedRAMP.
  
• Developer involvement is key to a successful scanning strategy, fast feedback loops, and quick fixes.
  
• Scans with open source images can be extremely noisy, which is why many companies choose to build with clean enterprise-grade infrastructure.

What is container scanning, and why does it matter?

Container scanning involves analyzing container images and runtime environments to identify potential security issues, such as known vulnerabilities (CVEs), misconfigurations, secrets, outdated software, and license violations. In most teams, it’s automated as part of DevSecOps pipelines to ensure security checks happen in tandem with builds and deployments, preventing delivery delays.

To understand why container scanning matters, it’s important to break down the layers that make up a container. At the base is the operating system, such as Debian, Ubuntu, or Alpine. On top of that are application libraries, frameworks, and finally, your custom application code. And while all are essential, each of these layers can introduce security risks, including:

• Vulnerable or outdated packages that attackers can exploit.
• Components with known CVEs that have been publicly disclosed.
• Insecure configurations that expand the attack surface.
• Software with noncompliant licenses that create legal or operational challenges.

With a large portion of these layers typically coming from public registries, it’s scarily easy to inherit vulnerabilities in your containers. In fact, most container vulnerabilities originate in the base image, long before your developers even write a single line of application logic. And without scanning, these risks remain invisible until runtime, where fixes become much slower, costlier, and riskier to implement.

With scanning, teams can:

• Catch vulnerabilities earlier in the SDLC before they reach production environments, minimizing the risk of potential attacks.
• Ensure compliance requirements are met with essential visibility and security policies.
• Automate remediation or gating decisions and reduce MTTR (mean time to remediation) to improve security postures.

How container scanning works in practice:

1. Image retrieval: The scanner pulls the container image from a registry or local build output.
2. Image unpacking: The image layers are decompressed to expose their full file system structure.
3. Component inventory: The scanner builds a complete software bill of materials (SBOM), listing every package, library, and binary.
4. Vulnerability matching: Components are compared against one or more vulnerability databases (e.g., NVD, vendor-specific advisories) to identify CVEs.
5. Configuration checks: The scanner evaluates security settings like file permissions, user privileges, network ports, and kernel capabilities.
6. Secrets detection: The scanner searches for sensitive strings or credentials embedded in code, configs, or environment variables.
7. Policy enforcement: Scan results are evaluated against predefined rules. If it fails, the pipeline can block the build, flag the image, or trigger an automated fix.

Common vulnerabilities detected by container scanning

Container scanning open source tools inspect each layer of a container, comparing the contents to known vulnerability databases and security policies to uncover issues like:

1. Recognized CVEs (Common Vulnerabilities and Exposures)

These are publicly disclosed flaws in software packages that malicious attackers can exploit. Scanning tools match package versions against vulnerability databases such as The National Vulnerability Database (NVD), GitHub Security Advisories, Alpine SecDB, and Red Hat OVAL. Each known CVE has a severity score (CVSS), vector details, and suggested remediation strategies.

2. Outdated or unsupported software

As more code is written, some packages may pass their end-of-life (EOL) and no longer receive updates. Others may be outdated by several versions, and some simply don’t have clear owners, leaving them effectively unmaintained. Regardless, these packages can trigger significant supply chain risk. 

See How CVEs fall through the cracks in upstream bug trackers to learn more about unmaintained software.

3. Secrets and credentials

It’s common for Secrets to slip into container images through overlooked files like .env, Kubernetes config maps, or even shell history. These can include API keys, AWS credentials, SSH private keys, and database connection strings.

And, to be blunt, even a single leaked key can be catastrophic – enabling attackers to bypass authentication and directly access production systems or sensitive customer data. 

That’s why quality scanners don’t just look for obvious filenames; they also use pattern-matching to detect the structure of common credentials (e.g., AWS key formats, JWT tokens), which helps reduce false positives while catching more subtle leaks. For example, a scan might flag an .env file with an AWS_SECRET_ACCESS_KEY. This early detection allows security teams to rotate the key and mitigate the risk before it gets deployed. 

4. Misconfigurations

Sometimes, risk actually lies in how the container is configured, which can quietly weaken defenses and give attackers easier entry points or greater freedom once inside. 

Examples of this include root privileges giving attackers full control over the host or other containers, missing security context settings, unrestricted network access, and writable filesystem layers that allow attackers to plant persistent backdoors or modify binaries.

That’s why the best scanners automatically flag these risky configurations, map them to compliance frameworks like CIS Benchmarks, and even provide ready-to-apply Kubernetes or Dockerfile fixes so teams can harden images without guesswork.

5. License risks

Including code with the wrong license can trigger extremely costly legal, compliance, or operational issues. For example, if used improperly, licenses like GPL or AGPL may require making your source code public, which can create serious intellectual property risks.

The challenge is that open source components often come bundled into dependencies several layers deep, making it easy for unapproved licenses to slide in unnoticed. The good news? Scanners not only identify the license type of every package in your SBOM, they also map them against your organization’s approved license policy.

Done right, scanners can:

• Flag license types that are prohibited or require review.
• Highlight transitive dependencies carrying risky licenses.
• Integrate with developer workflows so issues are caught before code is merged.
• Suggest remediation tactics like swapping in a permissively licensed alternative.
  

By catching license risks early, teams avoid costly rework, maintain critical compliance with frameworks like FedRAMP or SOC 2, and keep legal surprises out of production.

Best practices for container scanning

1. Scan early and often

It’s a big mistake to just scan at deployment. Vulnerabilities and misconfigurations are cheapest to fix when they’re caught early in the software development lifecycle (SDLC).

So, be sure to scan at multiple points:

• Pre-commit: Scanning at this stage enables you to catch risky dependencies before they hit the repo.
• CI/CD pipeline: Scanning within the pipeline block builds with high/critical CVEs or misconfigurations.
• Pre-deployment: Scanning pre-deployment enables you to double-check what’s about to go live.
• Post-deployment: Rescanning stored images regularly ensures you can detect newly disclosed CVEs right away.

This layered approach avoids the risk of being blindsided and unprepared.

2. Automate container scanning

Trying to manually scan your containers is a really slow process and, frankly, not scalable. That’s why automating has become so common, as it ensures consistent and proactive coverage without developer overhead. 

For example, GitHub Actions snippet using Trivy is:

- name: Scan Docker image
  uses: aquasecurity/trivy-action@master
  with:
    image-ref: my-app:latest
    format: 'table'
    exit-code: '1'

This setup scans each build and fails the pipeline if critical vulnerabilities are identified – without any exceptions or need for manual intervention.

3. Use trusted and secure base images

Container base images are the foundation for everything you build. So, while pulling from public registries may be more considered more convenient, it often brings outdated or bloated packages that can trigger way more issues down the line.

Instead:

• When relevant, start with slim and minimal images like Alpine and Distroless.
• Pin versions to avoid unexpected or unwanted updates.
• Choose enterprise-grade base images like echo that are built and kept CVE-free.
• For regulated environments, follow FedRAMP or CIS-approved baselines.

4. Scan private dependencies and custom packages

Unfortunately, it’s not enough to simply scan open source images. Even your private code and internal packages can also carry vulnerabilities, so it’s important to choose scanners that also: 

• Index and scan internal registries and package repos.
• Support SBOM generation for custom code.
• Track package provenance to spot compromised or unmaintained libraries.

5. Track CVE drift over time

New CVEs are constantly being discovered, so you can’t treat scanning as a one-and-done process. In fact, it’s very possible that an image that scans clean today may not scan clean tomorrow. That’s why it’s best to build a proper vulnerability feed and make scanning a continuous part of your workflow – rescanning production images weekly or even daily. When a new high or critical CVE appears in your base image, it’s best practice to automate rebuilds. 

6. Ensure scan results are accessible to developers

Let’s be honest: scan results stuck in security tools that no one even checks aren’t helpful. To ensure successful remediation, you need to give developers clear visibility. The best way to do it? 

Integrate scan results directly into developer workflows:

• PR comments in GitHub or GitLab
• Real-time alerts in Slack or Microsoft Teams
• Auto-generated Jira tickets with remediation details
• IDE plugins for immediate feedback while coding

This way, you seamlessly guarantee fast, contextual, and developer-friendly feedback loops, which dramatically improve fix rates.

Choosing the right container security scanner

So, what’s the best container security scanner? Truthfully, there’s no one-size-fits-all solution – it simply depends on your architecture, compliance needs, and team size. 

Check out the categories below to choose the one that’s right for your needs. And remember, it’s highly recommended to use more than one scanner to avoid false positives and CVE blindspots. 

Popular Docker container scanning tools

Open source:

• Trivy: Fast, comprehensive, and supports SBOMs.
• Grype: CLI-based, integrates with Syft for SBOM generation.
• Clair: Focused on scanning container registries.

Commercial (dedicated container security)

• Snyk Container: Developer-friendly, integrates with Git repos and registries.
• Aqua Security: Enterprise-ready with runtime security and policy enforcement.
• Anchore Enterprise: Deep SBOM and policy engine features.

CNAPP platforms with built-in scanning

• Palo Alto Prisma Cloud: Broad CNAPP capabilities with integrated scanning and compliance checks.
• Wiz: Cloud security platform with registry scanning, config checks, and runtime context.
• Sysdig Secure: Combines scanning, runtime detection, and Kubernetes security.
• Orca Security: Agentless CNAPP with scanning for registries and running workloads.

When to choose a CNAPP for container scanning

If you’re looking to bundle container scanning with other cloud security functions like posture management, workload protection, and compliance reporting, CNAPPs (Cloud-Native Application Protection Platform) are a great option. For many teams, this consolidation simplifies tooling and significantly reduces integration overhead.

That said, CNAPPs may not scan as deeply as dedicated container security tools, and their vulnerability results often depend on broader cloud context rather than image-level precision. That’s why a popular best practice is to use CNAPP scanning for broad coverage and compliance visibility, and pair it with a dedicated or open source scanner for fast, high-fidelity image checks in CI/CD.

What to look for in container scanners:

• Integrations – Integrated with CI/CD, registries, and developer tools
• Accuracy – Low false positives and contextual triage
• Depth – Secrets, configurations, licenses, and reachability
• Auditability – Reporting and policy enforcement (especially if you’re pursuing FedRAMP)
• Automation – Event-powered scans and gates
• Remediation – Fix suggestions, CVE grouping, and auto PRs

If your organization is part of a regulated industry or handles sensitive data, be sure to prioritize scanners that meet FedRAMP container scanning expectations and offer ongoing visibility into compliance.

FAQs

What is the difference between image scanning and container scanning?

Image scanning refers to scanning the container image at rest, typically before it’s deployed, to detect issues like vulnerabilities, misconfigurations, and secrets. Container scanning, on the other hand, is a broader term that encompasses:

• Build-time scanning: Detecting risks as images are built in CI/CD.
• Registry scanning: Periodic rescans of stored images to catch newly published CVEs.
• Runtime scanning: Inspecting active containers for drift or malicious changes (less common).

Most modern teams prioritize image scanning in CI/CD because it’s automated and blocks vulnerable builds before they reach production.

How often should I scan my containers?

At a minimum, you should be scanning your containers on every build and commit to prevent vulnerabilities from being introduced into main branches, before deployment to ensure a final check before production, and on a recurring schedule (daily or weekly) to catch vulnerabilities disclosed after an image is built. The most secure organizations automate rescan-on-CVE-publish triggers to avoid blind spots.

Can scanning tools detect runtime threats?

Generally no. Image and container scanning focus on static analysis of what’s in the image. Runtime threats, such as process injection, lateral movement, cryptomining, or privilege escalation, require dynamic monitoring tools like runtime security agents, host-based intrusion detection systems (HIDS), and CNAPP runtime protection modules.

Some enterprise platforms integrate both scanning and runtime monitoring, but they’re still distinct capabilities. It’s recommended to pair pre-deployment scanning with runtime behavioral monitoring to ensure end-to-end coverage.

What’s the role of container registries in security scanning?

Many registries integrate scanning as a native feature. Amazon ECR and Google Artifact Registry, for example, auto-scan new images, flag vulnerabilities before deployment, and support a rescan-on-CVE-publish trigger to ensure ongoing visibility.