Mitigating container image vulnerabilities: Best practices for DevSecOps teams

Key Takeaways

• Vulnerable container images spread flaws to every container built on top of them.
• Vulnerabilities can arise in OS packages, libraries, dependencies, misconfigurations, and more.
• Scanning container images helps catch CVEs before they reach production, where the risk is higher, and they are harder to fix.
• Best practices to prevent container image vulnerabilities include using minimal base images, multi-stage builds, and enforcing non-root privileges.
• Hardened container images like echo are the fastest way to eliminate vulnerabilities at the source.

What Are Container Image Vulnerabilities

Container images are blueprints for running containers. They package everything an application needs to run, including code, runtime, libraries, configurations, system tools and OS components. Developers build these images and use them to spin up consistent workloads across environments.

Since every container is instantiated from an image, whatever exists inside that image is replicated at scale. This enables predictable, repeatable deployments across environments.

However, the same speed and convenience that make images attractive also introduce security risks. Container image vulnerabilities are weaknesses baked into the image’s filesystem: vulnerable OS packages, outdated libraries, risky application dependencies, insecure configurations, or even flaws in how the image was built.

Every container instantiated from that image inherits those weaknesses, meaning a single vulnerable base image or dependency version can propagate across dozens of services and hundreds of containers. This makes container images a high-risk point in the supply chain.

Types of Vulnerabilities Found in Container Images

Container images can carry multiple types of vulnerabilities. For developers and security teams, mapping them can help with finding the right mitigation tools and strategies.

• OS Package & Image Vulnerabilities - Outdated OS packages or stale system libraries can contain CVEs that haven’t been patched. These vulnerabilities often reside in core components like crypto libraries and networking stacks. Because these sit low in the stack, exploitation has a broad impact and is difficult to contain. Using hardened base images from a vendor like echo ensures images are secure and vulnerabilities won’t propagate throughout the SDLC. 
• Application Dependency Vulnerabilities - Dependencies pulled from npm, pip, Maven, and similar ecosystems often introduce direct and transitive vulnerabilities such as prototype pollution, RCEs, or SQL injection flaws. These risks are amplified by deep dependency trees that developers rarely audit manually.
• Misconfigurations and Insecure Defaults - Images may be built with unsafe defaults like running as root, excessive permissions, open ports, or writable filesystem paths. If exploited, these weaknesses enable privilege escalation, container breakout, or lateral movement.
• Hardcoded Secrets and Sensitive Data - Secrets like API keys, tokens, or certificates embedded in images are immediately exposed to anyone who can pull or inspect the image. If they are leaked or discovered by an attacker inside the system, they can be used to move laterally into downstream systems and exfiltrate data.
• Insecure Debugging Binaries Left in Production - Debug tools like curl, wget, bash, compilers, or package managers increase the attack surface if left in production images. Attackers can “live off the land” and use them to download payloads, compile exploits, move laterally, or install malicious software. A best practice is to use minimal base images in production, like those provided by echo, which contain only the application and its required libraries.
• Malware or Malicious Upstream Modifications - Compromised upstream components can introduce backdoors, crypto-miners, or command-and-control beacons directly into images. These threats are especially dangerous because they look like legitimate dependencies. When developers update their software, they unknowingly pull the attacker's malicious code directly into their private environment. 
• License and Policy Violations (Compliance Vulnerabilities) - Vulnerable images may include components that violate licensing terms or regulatory requirements (e.g., GPL conflicts, non-FIPS crypto). These issues create legal and compliance risk even if no exploit exists. Making images compliant is resource-intensive. 

Best Practices For Vulnerability Scanning

Image scanning catches known CVEs early in the supply chain, before they reach production and become much harder and riskier to fix. Enterprise-grade container images like echo are supported by all major scanners, such as Wiz, Orca, Trivy, and Grype, to ensure clear visibility into your strong security posture.

Follow these container vulnerability scanning and remediating best practices:

1. Integrate scanners natively into CI/CD - Vulnerability scanning should run automatically as part of your build pipeline, immediately after an image is built and tagged. Builds should fail based on clear, configurable thresholds (for example, any Critical vulnerabilities or more than N High findings).

2. Scan at multiple checkpoints - On top of build time scanning, use scanning tools to:

• Automatically scan newly pushed images
• Re-scan existing images when vulnerability databases update
• Scan before deployment to block non-compliant images
• Periodically rescan post-deployment images to catch newly disclosed CVEs that weren’t known when the image was built.

3. Use SBOMs as core metadata - Generate SBOMs for every image during the build and store them alongside the image in the registry or artifact store. Use the SBOM to trace and re-evaluate vulnerabilities and licenses as needed.

4. Maintain multiple vulnerability data sources - Relying on a single vulnerability feed creates blind spots, especially for OS-level packages and language-specific dependencies. Aggregate NVD data with distro-specific advisories and ecosystem-specific feeds from package managers like npm, PyPI, and Maven. Update scanner databases continuously in CI runners and registries.

5. Normalize severity and prioritize by exploitability - Raw CVSS scores are insufficient for real-world prioritization. They should be mapped into an internal risk model that incorporates exploit maturity, exposure, and asset criticality. Determine context, such as whether the vulnerable component is reachable at runtime, whether the container is internet-facing, and whether active exploits exist. Then, combine this with the severity ratings and add to automated triage. This will prevent developers from being overwhelmed by low-impact findings.

6. Make scan results developer-consumable - Scan output should be structured to help developers fix issues quickly. Vulnerabilities should be grouped by affected package rather than by individual CVE to reduce noise, remediation guidance should be explicit, and results should surface directly into the right developer workflows.

7. Implement exception workflows and SLAs - Not all vulnerabilities can be fixed immediately. Define severity-based SLAs and a formal exception process for risks that are accepted. Include expiration dates and re-evaluate periodically and when conditions change. For example, when new exploits become available or a service moves into a production environment.

How To Avoid Container Image Vulnerabilities

While scanning is essential, alone, it’s not enough. A secure container image is essential to ensuring a secure supply chain. To minimize and mitigate container image vulnerabilities, follow these technical recommendations:

Use minimal, trusted base images

The surest way to avoid vulnerabilities is to start with the smallest, most purpose-built base image that still meets your functionality needs. 

• Default/Developer Image: Includes tooling (shell + package manager). Good for development, debugging, and iterative work.
• Minimal/Production Image: Reduce exposure by using images that are stripped down to only what’s needed to run the application. No shell. No extra packages.

Secure enterprise-grade container images like echo are offered in both versions and are drop-in replacements for the upstream open source images used today. Its purpose-built AI agents work autonomously to build clean container images from scratch and keep them secure as new vulnerabilities arise. This means that when new CVEs emerge, echo's agents are equipped to automatically research them, identify affected images, find or develop fixes, apply patches, run compatibility testing, and create pull requests for human review to ensure images stay clean over time.

Use multi-stage builds aggressively

Multi-stage builds separate build from runtime. Heavy compilers, SDKs, and package managers live only in the build stage, while the final image contains just the compiled binary or minimal runtime artifacts. This sharply reduces the number of installed packages and tools available to an attacker if the container is compromised. Always verify that no build-time tools or debuggers remain in the final image, as they are common post-exploitation enablers. Enforce non-root and least privilege in images

Containers should never run with "Admin" (root) privileges. If the application needs to save files, specify exactly which folders the user is allowed to touch. By avoiding "privileged" mode or extra system powers, you ensure that if an attacker breaks into the container, they are "trapped" in a low-power account and cannot take over the entire server.

Externalize secrets and configuration

Secrets do not belong in images, neither as environment variables nor as copied configuration files. They should be injected at runtime from a dedicated secret manager or secure store, ensuring rotation and access control are handled centrally.

Rebuild images frequently and automate patching 

Images should be rebuilt regularly to pick up patched base images and updated OS packages. Automating dependency and base image updates through PRs keeps the process visible and reviewable, while scanners and CI validate that security posture improves without breaking functionality.

Sign and verify images

Signing images at build time and verifying signatures before execution ensures that only artifacts produced by your pipelines are allowed to run. Unsigned or tampered images should never make it past admission control.

FAQs

What is the difference between image scanning and container scanning?

Image scanning analyzes the static artifact stored in the registry: layers, packages, SBOM, and config metadata, whereas container scanning inspects the running instance: environment variables, mounted volumes, runtime-installed packages, active processes, and network behavior.

How often should you scan container images?

Practically, you should scan continuously on every build, whenever an image is pushed to a registry, and on a scheduled basis for all images stored in registries. Additionally, re-evaluate all images when high-impact CVEs are disclosed by triggering targeted rescans based on SBOMs. The goal is for any change in code, dependencies, or vulnerability intel to quickly reflect in scanned risk posture without manual intervention. 

Can scanning tools detect runtime threats?

No, traditional image scanners cannot see runtime behavior; they only inspect bytes in the image and known advisories. Runtime threat detection needs agents or sidecars instrumenting syscalls, process trees, network flows, and Kubernetes events.

What are the most common vulnerabilities in container images?

Outdated OS packages, unpatched language libraries pulled transitively, images running as root with excessive permissions, and bloated images with debugging tools and package managers that dramatically increase the attack surface. Instead of relying on public base images, use a trusted, secure-by-design container image for hardened images you can pull with confidence.

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

Container registries are the central control plane for images. They can enforce signed-only images, automatically scan new artifacts, attach SBOMs and attestations, block pulls of non-compliant images into sensitive environments, and create audit trails for who pushed which image when.