Checkov vs Sonobuoy

Checkov is a free tool for scanning infrastructure-as-code files for configuration problems that could affect security or compliance. Its documented targets include Terraform, CloudFormation, ARM, Serverless, Helm, Kubernetes, and Docker. The policy library contains more than 750 predefined checks, including checks for standards such as CIS and the AWS Foundations Benchmark. Checkov can also identify common credentials in IaC files, including AWS access keys, Azure service credentials, and private keys. Teams can create custom attribute policies in Python or YAML and composite policies in YAML. Documented continuous-integration integrations include Jenkins, Bitbucket Cloud Pipelines, GitHub Actions, and GitLab CI. Add-ons for Visual Studio Code and JetBrains provide real-time scanning and inline fixes. Installation is documented through pip and Homebrew, with Homebrew specified for macOS or Linux. The project supports Python 3.9 through 3.13 and is distributed under the Apache-2.0 license. Prisma Cloud extends Checkov with runtime scanning, visibility, native VCS integrations, drift detection, and pull request annotations. Alpine is not officially tested or supported; it requires Python 3.11 or later.

Sonobuoy is a free, open-source diagnostic tool for examining Kubernetes cluster state with non-destructive configuration tests. It can check a cluster against official Kubernetes specifications and produce diagnostics for troublesome workloads. Teams can build plugins for additional tests and data collection. Its default plugins run Kubernetes end-to-end tests and gather systemd logs; community options include CIS Benchmarks, Kube-hunter, Who-can, Cluster-Inventory, and Reliability Scanner. It is cluster agnostic and officially supports the latest three minor Kubernetes versions. Beginning with version 0.20, it supports Kubernetes 1.17 or later. Sonobuoy can run end-to-end tests with custom registries in air-gapped deployments. It requires an active Kubernetes cluster and an admin kubeconfig, and can be installed from binary releases or through Homebrew on macOS. The project provides community support through GitHub. Its documentation warns that default settings need explicit hardening, and notes that some logging and retrieval commands can fail on Docker Desktop Kubernetes.