Conftest vs DryRun Security IaC Security

Conftest is a free utility for testing structured configuration data, designed for use in CI environments. It uses the Open Policy Agent Rego language to express policies, then evaluates deny, violation, and warning rules within namespaces. Configuration can be read from individual files, directories, multiple files, or standard input. Supported inputs include Kubernetes-style YAML, JSON, HCL and HCL2, Dockerfiles, Terraform-related data, JSONnet, TOML, and XML. Results can be output as plaintext, JSON, TAP, table, JUnit, GitHub, Azure DevOps, or SARIF; the GitHub outputter can annotate test results in workflows. The `conftest verify` command runs policy unit tests. Policies can be pulled from HTTPS URLs, Git repositories, and OCI registries, or pushed to compatible OCI registries. Plugins extend the CLI, with downloads available from sources including OCI, Git, HTTP/HTTPS, Mercurial, and cloud storage. Pre-commit hooks support policy workflows, and integrations are documented for CircleCI, GitHub Actions, and Tekton. Conftest is available for Linux, macOS, and Windows.

DryRun Security IaC Security scans infrastructure-as-code changes for security risks by analyzing infrastructure and application code together. It covers Terraform, Kubernetes, and other IaC, with checks for overly permissive IAM policies, publicly exposed resources, insecure defaults, and subdomain takeover risks. Scans run in pull requests and provide guidance during infrastructure design. Teams can write natural-language guardrails for public access, permitted cloud regions, approved resource types, and organization-specific requirements; the Custom Policy Agent enforces them on changes. Terraform findings can appear as pull-request comments and Risk Register entries containing the affected resource, risk description, and remediation guidance. Listed integrations include Claude Code, Claude Desktop, Codex, Cursor, GitHub, GitLab, and Slack. The SaaS service supports GitHub.com personal, organization, and Enterprise Cloud repositories, plus GitLab SaaS; custom instances and other source-control systems require contacting DryRun. DryRun says it uses private models, sends no data to public AI systems, stores minimal metadata and findings, and allows code-access revocation through repository permissions. Pricing is on request, aligned with team size, and a free trial is available.