Open Source Container Scanner
Container images bundle layers of someone else's dependencies, and a vulnerability that slipped into a base image weeks ago ships to production unless something catches it first. The open source tools here let you see precisely how images and manifests are evaluated and run that check inside your own pipeline, so you can gate deploys on findings you trust without sending your build artifacts to a third party.
Harbor
Cloud native registry for storing, signing, scanning, and replicating container images and Helm charts
Kubescape
Kubernetes security platform spanning IDEs, CI/CD pipelines, and live clusters
Clair
Static analysis for container image vulnerabilities, accessed through an API
Docker Bench for Security
Automated checks for Docker hosts and containers against the CIS Docker Benchmark
Falco
Cloud native runtime security for Linux that detects abnormal behavior in containers and hosts in real time
kube-bench
Checks whether Kubernetes is deployed according to the CIS Kubernetes Benchmark
KubeLinter
Static analysis for Kubernetes YAML files, Helm charts, and Kustomize manifests
Dockle
Container image linter that checks images against best practices and CIS Benchmarks
KICS
Static analysis for infrastructure as code that finds security, compliance, and misconfiguration issues
How to choose an open source container scanner
Start with what the scanner can actually see inside your images. Some tools rely on OS package manager metadata, which works well for common distro bases but misses hand-copied binaries, vendored libraries, or language packages installed outside the expected paths. Others unpack layers more deeply and map application dependencies, archives, and statically linked components. If you use scratch, distroless, multi-stage builds, or private base images, test those cases directly. A useful container scanner should explain which layer introduced a finding and whether the package is still present in the final image.
The vulnerability matching model matters as much as coverage. Container results depend on distro advisories, package names, backported patches, CPE matching, and how quickly the local vulnerability database is refreshed. A scanner that reports raw CVEs without understanding patched vendor packages will create noise for engineering teams. Check how it handles severity normalization, ignored vulnerabilities, unfixed issues, and VEX or other status signals. For regulated environments, look for reproducible outputs such as SBOMs, stable JSON, and clear evidence trails that can survive audits.
Fit the scanner to your release path, not just to a command-line demo. CI scans are good for fast feedback, registry scans catch images built outside the main pipeline, and admission controls can stop risky deployments before they reach a cluster. Decide where policy belongs: warnings in pull requests, failed builds, deployment blocks, or periodic reporting. Also check authentication to private registries, caching behavior, API support, SARIF or ticket output, and whether exceptions have owners and expiration dates. Without that workflow, even accurate findings become backlog noise.
Related categories
Frequently asked questions
What should a container scanner check besides CVEs?+
A useful container scanner should identify OS packages, language dependencies, package versions, base image lineage, and sometimes secrets or risky configuration. CVE matching is only one part of the job. For container images, layer context matters because the vulnerable package may have been introduced in an earlier stage, removed later, or hidden inside an archive that basic package metadata will not show.
How do open source container scanner costs usually work?+
The scanner itself may be free to run, but cost can appear in infrastructure, vulnerability feed access, storage, and staff time spent triaging findings. Some deployments need private registry access, scheduled rescans, and retained reports for audit evidence. Also review the license if you plan to embed the scanner into a commercial platform or redistribute modified builds.
Where should scanning happen in the container delivery pipeline?+
Most teams get the best coverage by scanning in more than one place. CI gives developers fast feedback before images are promoted. Registry scanning catches images built outside the main workflow or rescans old images when new CVEs appear. Admission or deployment checks enforce policy at the cluster boundary. The right mix depends on build speed, release risk, and how many exceptions you can tolerate.
Why do container scanners disagree about the same image?+
They may use different vulnerability sources, package detection logic, severity mappings, and rules for vendor backports. One scanner may treat a distro-patched package as fixed while another reports the upstream CVE as open. Differences are normal, so evaluate with your own images and compare whether the tool explains its evidence. Raw finding counts are a weak selection metric.
Does a container scanner understand application dependencies inside an image?+
Some do, but depth varies. A scanner may detect packages installed by a system package manager yet miss dependencies from language ecosystems, copied build artifacts, or nested archives. If your images contain compiled services, vendored modules, or monorepo builds, test whether the scanner finds those components and maps them to useful fix guidance instead of only reporting the base image.
How should a scanner handle patched packages with unfixed upstream CVEs?+
Container images often use distro packages that include backported security fixes without changing the upstream version number. A scanner should understand the vendor advisory, not just compare version strings. Otherwise it will flag packages that are already patched. Check whether findings cite the distro source, installed package release, fixed version, and the reason an issue is considered open or resolved.
Can a container scanner run in an air-gapped environment?+
Yes, if it supports offline database mirroring and can scan images from a local registry or saved archive. The key question is how vulnerability updates are transported, verified, and applied without internet access. Also confirm that reports, SBOMs, and policy decisions do not call external services. Air-gapped scanning is practical, but database freshness becomes an operational responsibility.
Which output formats matter for container scanner integrations?+
Look for stable machine-readable output such as JSON, SARIF for code review systems, and SBOM formats your compliance process already accepts. Human-readable terminal output is useful locally but weak for automation. If you need ticket creation, dashboards, or risk acceptance workflows, verify the API and schema stability. Breaking output changes can quietly damage CI gates and reporting jobs.
How strict should build-fail policies be for container vulnerabilities?+
Avoid failing every build on every high-severity CVE without context. Start with rules based on severity, fix availability, package reachability if available, image environment, and exception age. A production internet-facing service should have a different threshold than an internal one-off job. Good policies create predictable engineering work; bad policies train teams to bypass the scanner.
Do container scanners find secrets and unsafe image configuration?+
Some container scanners include checks for embedded secrets, weak file permissions, root users, exposed ports, package manager caches, and risky Dockerfile patterns. Others focus only on vulnerability matching. Decide whether you want one tool to cover both image hygiene and CVEs or separate tools with clearer ownership. For secrets, confirm detection quality and the process for revoking anything that was actually exposed.
What special issues come up with scratch, distroless, or multi-arch images?+
Minimal images often have little or no package manager metadata, so scanners must infer components from files, language manifests, or SBOMs generated during the build. Multi-arch images can produce different findings per architecture because packages and binaries differ. Test the exact image variants you deploy, not just one tag. Otherwise a clean scan on one platform can hide risk on another.
How should teams manage exceptions and ownership?+
Exceptions need an owner, reason, scope, and expiration date. A blanket ignore file that never expires becomes another form of technical debt. Prefer exceptions tied to package, CVE, image, and environment so they do not suppress unrelated findings. The scanner should make it easy to review expired exceptions and distinguish accepted risk from items that still need engineering action.
What happens if we need to change container scanners later?+
Migration is easier when your current process stores standard outputs such as SBOMs, JSON reports, SARIF, and policy files outside the scanner database. Findings, ignore rules, and dashboards may not transfer cleanly because scanners identify packages and CVEs differently. Keep raw scan artifacts, image digests, and exception rationale under your control so you can compare results during a staged switch.