Steampunk Spotter
5 Best Ansible Playbook Scanning Tools in 2025
April 15, 2025 - Words by The Spotter team - 7 min read
As your environment grows in complexity, maintaining reliable and secure Ansible playbooks requires extra care and attention. With frequent updates to both infrastructure and automation processes, keeping playbooks efficient and free from security risks is no easy feat. Fortunately, there are Ansible playbook scanning tools that help simplify this task.
Ansible playbook scanning tools simplify this process, but they also come with their own set of considerations. In this article, we’ll cover the top 5 Ansible playbook scanning tools to try in 2025. We’ll explore each tool’s key features, types and cons to help you find the best fit for your automation needs. First, let’s clarify what exactly Ansible playbook scanning is.
What is Ansible playbook scanning?
Ansible playbook scanning refers to the process of reviewing and analyzing Ansible playbooks for potential issues, code quality, vulnerabilities, or misconfigurations. It ensures your playbooks adhere to best practices, security standards, and compliance requirements through a combination of pre-built and customizable checks.
Best Tools for Scanning Ansible Code
Below are several tools (open-source and commercial) that scan Ansible playbooks, roles, inventory files, and related configuration for best practices, security issues, and code quality. Each tool is well-known or widely used in the Ansible community and provides specialized linting or analysis of Ansible content.
Ansible Lint
Steampunk Spotter
KICS (Keeping Infrastructure as Code Secure)
Checkov
Ansible Molecule
1. Ansible Lint
Ansible Lint is an open-source command-line tool that analyzes Ansible playbooks, roles, and collections to enforce proven best practices and coding standards. It catches common issues such as syntax errors, use of deprecated modules, and potential security misconfigurations, helping to ensure playbooks are reliable and secure.
Key Features for Ansible Code:
Comes with a wide set of built-in rules to flag anti-patterns (e.g. using features removed in newer Ansible versions, exposing credentials, idempotency issues).
Users can write custom linting rules (in Python) to extend or override checks, tailoring the tool to their organization’s policies.
It offers clear and useful tips to improve the quality of the playbook. Ansible Galaxy uses this linter to help score community roles, indicating its alignment with community best practices.
Cons: Ansible Lint focuses mainly on syntax errors and basic checks, making it a great starting point for improving playbook quality. However, it doesn’t catch more complex issues, and it lacks built-in reporting features for deeper insights and analytics. No graphical user interface (GUI), currently available only as a command-line interface (CLI).
Type: CLI tool (often integrated into CI pipelines, pre-commit hooks, and editor/IDE plugins for on-the-fly feedback).
License: Open-source (community-maintained, originally by Will Thames, now under the Ansible Community team).
Website: home - Ansible Lint Documentation
GitHub: ansible-lint
2. Steampunk Spotter
Steampunk Spotter is a commercial Ansible playbook analysis platform that goes beyond basic linting. It performs in-depth static analysis of playbooks to identify hard-to-catch errors, suboptimal patterns, and security issues, thereby improving the quality, reliability, and security of your Ansible automation. Spotter also helps with Ansible version upgrades by checking playbook compatibility and making automatic fixes for smoother migrations. Spotter is a tool built exclusively for Ansible, developed by highly skilled Ansible experts.
Key Features for Ansible Code:
Performs advanced best-practice checks beyond syntax (e.g. flags logic mistakes or risky configurations), ensures compliance with security standards by detecting misconfigurations and vulnerabilities, and even provides guidance for upgrading to newer Ansible releases.
Users can define custom policies (Spotter includes an Open Policy Agent engine) to enforce organization-specific rules.
It produces detailed reports and recommendations for remediation, with a dashboard to track issues and improvements over time.
Integrates with APP: Validates Ansible content before and during execution in AAP, ensuring thorough testing across the entire workflow. Prevents risky deployments, enforces compliance, and saves time by catching issues early.
Cons: You can enjoy Spotter Pro free for 14 days with no strings attached. After that, you’re welcome to continue with a free account (with limited features), or upgrade to Spotter Pro or an Enterprise plan, depending on your needs.
At Steampunk Spotter, we’re always happy to chat and help you find the right fit .
Type: Available as a web UI (dashboard with reports), a CLI tool, and via API, making it easy to integrate into CI/CD pipelines. There is also an IDE plugin (e.g. VS Code) for on-the-fly feedback.
License: Commercial (enterprise-focused). Free plan available – the CLI is open-source, but the full knowledge base and advanced features are proprietary. The free tier allows a limited number of scans per month for individuals or small projects.
Website: Steampunk Spotter | XLAB Steampunk
GitHub: xlab-steampunk/spotter-action
3. KICS
KICS by Checkmarx is an open-source static analysis tool that finds security vulnerabilities, compliance issues, and misconfigurations in infrastructure-as-code definitions. KICS specializes in cloud infrastructure. It supports a wide range of IaC formats – including Terraform, Kubernetes manifests, Dockerfiles, CloudFormation, and Ansible playbooks. KICS is designed to help catch issues before deployment to avoid security risks in automated infrastructure.
KeyFeatures for Ansible Code
Scans Ansible playbooks for misconfigurations and security concerns alongside other IaC types. It comes with 2,000+ pre-defined policies (queries) covering a broad range of issues and cloud provider best practices. For Ansible, this includes checks like ensuring secure file permissions, avoiding plain-text secrets, correct module usage, etc.
All policies are customizable, and you can add new ones. KICS provides detailed output and reports pinpointing where a playbook may violate security or compliance rules, often with remediation guidance.
Cons: KICS is limited to detecting security vulnerabilities, compliance issues, and infrastructure misconfigurations, focusing mainly on these use cases. KICS is centered around cloud infrastructure. While it supports a broad range of platforms, including Ansible, it is not specialized forAnsible, which may result in less targeted insights.
Type: CLI tool (written in Go). It can be run locally or in CI (there’s a Docker image for convenience). KICS can also be integrated into IDEs or other tools via its JSON results.
License: Open-source (Apache 2.0).
Website: KICS by Checkmarx
GitHub: Checkmarx/kics
4. Checkov
Like KICS, Checkov focuses on cloud infrastructure. This open-source static analysis tool, originally developed by Bridgecrew.io and now owned by Palo Alto Networks, scans Infrastructure-as-Code for misconfigurations and security issues before the code deploys the infrastructure. Checkov can parse Ansible playbooks/tasks and apply policies to ensure they adhere to security best practices and configuration standard.
Key Features for Ansible Code:
Includes dozens of built-in policies specific to Ansible (identified with CKV_ANSIBLE_*) that catch issues like disabled SSL certificate validation in get url or yum tasks, use of insecure protocols, improper permissions, etc.
It ensures Ansible code is following best practices (for example, enforcing HTTPS for downloads and validating certificates) and flags risky configurations before deployment.
In addition to Ansible, it has over 1000 policies covering AWS/Azure/GCP security standards across various IaC frameworks, making it useful if your automation spans multiple technologies.
Cons: Like KICS, Checkov focuses on scanning cloud infrastructure configurations to identify misconfigurations and vulnerabilities before they are deployed. However, it lacks support for use cases such as accelerating Ansible upgrades, dashboard-based reporting, or advanced collaboration features. Additionally, while Checkov supports a wide range of tools like Terraform, Terraform Plan, CloudFormation, Kubernetes, ARM Templates, Serverless, Helm, and AWS CDK, it’s built for broader platform coverage, not specifically for Ansible workflows.
Type: CLI tool. Checkov is typically run in a terminal or CI pipeline (checkov -d
License: Open-source (Apache 2.0 License).
Website: Checkov – Ansible Scanning
GitHub: bridgecrewio/checkov
5. Ansible Molecule
Molecule is not a linter but a testing framework for Ansible that ensures roles and playbooks work as intended. It automates the process of provisioning test instances (using Docker, Vagrant, etc.), applying your Ansible roles and playbooks, and verifying the results. While Molecule doesn’t statically scan code for style, it is invaluable for quality assurance because it catches logic errors and regressions by actually running the code in clean environments.
Key Features for Ansible Code:
Enables writing scenarios to test Ansible roles across multiple platforms or Linux distributions to ensure compatibility.
Supports integration with test frameworks (like Testinfra or Inspec for writing assertions about the system state after playbook run).
Molecule can be plugged into CI pipelines for automated testing of Ansible content on each change.
By validating roles in isolated environments, it helps identify issues (including potential security problems or idempotency bugs) before roles are used in production.
Cons: Molecule is primarily a testing framework for Ansible roles, not a dedicated scanning tool.
Type: CLI tool (development/Test framework). It uses drivers (Docker, Podman, EC2, etc.) to spin up instances and a verifier (e.g. pytest) to run tests.
License: Open-source (part of the Ansible project).
Website: Molecule Documentation
GitHub: ansible-community/molecule
Which one should you choose?
Each of these tools targets a different area, from static analysis (like linting and policy compliance) to dynamic testing, and many organizations use them together for optimal results. By incorporating one or more into your workflow, you can catch bugs early, enforce Ansible best practices, and enhance the security and maintainability of your automation code.
So, which tool should you choose? There’s no one-size-fits-all answer. Each scanner complements the others in its own way, helping you achieve the best possible outcome.
If you’re just getting started, consider selecting a tool that not only scans your playbook but also automatically fixes errors. Start your free trial today.
