Checkov vs tfsec Terraform testing framework

Checkov is an open source static code analysis tool for infrastructure as code (IaC) that helps you to ensure that your Terraform, CloudFormation, and Kubernetes resource configurations adhere to best practices and are secure. It scans your IaC code and flags potential security issues, such as exposed secrets, unencrypted data at rest, and open firewall ports.

To use Checkov with Terraform, you can install the tool using pip (the Python package manager) and then run it against your Terraform code. For example:

pip install checkov
checkov -d path/to/terraform/code

Checkov will analyze the code and output a report of any potential security issues it finds. You can also specify certain checks to ignore or configure Checkov to fail the scan if certain types of issues are found.

In addition to the command-line interface, Checkov also provides integrations with popular continuous integration (CI) and continuous delivery (CD) platforms, such as Jenkins and Azure DevOps, so you can automate the scanning of your IaC code as part of your build and deployment process.

Here is an example of a pipeline that installs Checkov, runs it against a directory of Terraform code, and publishes the results as an artifact:

# YAML Pipeline
# Build and test a Terraform project with Checkov

trigger:
- master

pool:
  vmImage: ubuntu-latest

steps:
- script: |
    # Install Checkov
    pip install checkov
  displayName: 'Install Checkov'

- script: |
    # Run Checkov
    checkov -d path/to/terraform/code
  displayName: 'Run Checkov'

- task: PublishTestResults@2
  inputs:
    testResultsFormat: 'JUnit'
    testResultsFiles: 'checkov-report.xml'
  displayName: 'Publish Checkov results'

- task: PublishPipelineArtifact@1
  inputs:
    targetPath: '$(System.ArtifactsDirectory)'
    artifact: 'checkov-report'
  displayName: 'Publish Checkov artifact'

TFSec

tfsec is an open source static code analysis tool for infrastructure as code (IaC) that helps you to identify potential security issues in your Terraform configurations. It scans your Terraform code and flags potential security issues, such as exposed secrets, unencrypted data at rest, and open firewall ports.

To use tfsec, you can install it as a standalone binary or as a Docker container, and then invoke it from the command line by specifying the path to your Terraform code. For example:

tfsec path/to/terraform/code


tfsec will analyze the code and output a report of any potential security issues it finds. You can also specify custom rules to include or ignore certain checks, and configure tfsec to fail the scan if certain types of issues are found.

In addition to the command-line interface, tfsec also provides integrations with popular continuous integration (CI) and continuous delivery (CD) platforms, such as Jenkins and Azure DevOps, so you can automate the scanning of your Terraform code as part of your build and deployment process.

Here is an example of a pipeline that installs tfsec, runs it against a directory of Terraform code, and publishes the results as an artifact:

# YAML Pipeline
# Build and test a Terraform project with tfsec

trigger:
- master

pool:
  vmImage: ubuntu-latest

steps:
- script: |
    # Install tfsec
    wget https://github.com/tfsec/tfsec/releases/download/v0.34.1/tfsec-linux-amd64 -O tfsec
    chmod +x tfsec
    mv tfsec /usr/local/bin
  displayName: 'Install tfsec'

- script: |
    # Run tfsec
    tfsec path/to/terraform/code
  displayName: 'Run tfsec'

- task: PublishTestResults@2
  inputs:
    testResultsFormat: 'JUnit'
    testResultsFiles: 'tfsec-report.xml'
  displayName: 'Publish tfsec results'

- task: PublishPipelineArtifact@1
  inputs:
    targetPath: '$(System.ArtifactsDirectory)'
    artifact: 'tfsec-report'
  displayName: 'Publish tfsec artifact'

In this example, the pipeline installs tfsec using a script that downloads the binary and makes it executable, runs tfsec against the specified directory of Terraform code, and then publishes the results as a JUnit-formatted XML file and an artifact.

You can customize this pipeline to fit your specific needs, such as specifying custom rules or failure conditions for tfsec, or integrating with a continuous integration (CI) or continuous delivery (CD) platform.

Key differences between Checkov and tfsec

tfsec and Checkov are both static code analysis tools for infrastructure as code (IaC) that help you to identify potential security issues in your Terraform, CloudFormation, and Kubernetes resource configurations. Both tools scan your IaC code and flag potential issues, such as exposed secrets, unencrypted data at rest, and open firewall ports.

There are a few key differences between the two tools:

  1. Language support: tfsec is written in Go and supports only Terraform code, while Checkov is written in Python and supports Terraform, CloudFormation, and Kubernetes resource configurations.
  2. Installation and usage: tfsec can be installed as a standalone binary or as a Docker container, and it is invoked from the command line. Checkov can be installed using pip (the Python package manager) and is also invoked from the command line.
  3. Customization and configuration: tfsec allows you to specify custom rules and ignore certain checks, but it does not have as many customization options as Checkov. Checkov provides a more flexible configuration system, allowing you to customize the checks that are run and specify failure conditions.

Overall, both tfsec and Checkov are useful tools for identifying potential security issues in your IaC code, and which one you choose will depend on your specific needs and preferences.

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