Acerca de la CLI de CodeQL

Software developers and security researchers can secure their code using CodeQL analysis. For more information about CodeQL, see "About code scanning with CodeQL."

The CodeQL CLI is a standalone, command-line tool that you can use to analyze code. Its main purpose is to generate a database representation of a codebase, a CodeQL database. Once the database is ready, you can query it interactively, or run a suite of queries to generate a set of results in SARIF format and upload the results to GitHub.

You can use the CodeQL CLI to:

• Run CodeQL analyses using queries provided by GitHub engineers and the open source community
• Generate code scanning alerts that you can upload to display in GitHub
• Create CodeQL databases to use in the CodeQL for Visual Studio Code extension.
• Develop and test custom CodeQL queries to use in your own analyses

The CodeQL CLI can analyze:

• Dynamic languages, for example, JavaScript and Python.
• Compiled languages, for example, C/C++, C#, Go, Java, Kotlin, and Swift
• Codebases written in a mixture of languages.

For information about setting up the CodeQL CLI, see "Setting up the CodeQL CLI."

About using the CodeQL CLI for code scanning

You can use the CodeQL CLI to run code scanning on code that you're processing in a third-party continuous integration (CI) system. Code scanning is a feature that you use to analyze the code in a GitHub repository to find security vulnerabilities and coding errors. Any problems identified by the analysis are shown in your repository. For an overview of using code scanning with external CI systems, see "Using code scanning with your existing CI system." For recommended specifications (RAM, CPU cores, and disk) for running CodeQL analysis, see "Recommended hardware resources for running CodeQL."

Alternatively, you can use GitHub Actions or Azure DevOps pipelines to scan code using the CodeQL CLI. For more information, see "Configuring default setup for code scanning" or Configure GitHub Advanced Security for Azure DevOps in Microsoft Learn.

For an overview of all the options for using CodeQL analysis for code scanning, see "About code scanning with CodeQL."

About generating code scanning results with the CodeQL CLI

If you choose to run the CodeQL CLI directly, you first have to install the CodeQL CLI locally. If you are planning to use the CodeQL CLI with an external CI system, you need to make the CodeQL CLI available to servers in your CI system. For more information, see "Setting up the CodeQL CLI."

Once the CodeQL CLI is set up, you can use three different commands to generate results and upload them to GitHub:

1. database create to create a CodeQL database to represent the hierarchical structure of each supported programming language in the repository. For more information, see "Preparing your code for CodeQL analysis."
2. database analyze to run queries to analyze each CodeQL database and summarize the results in a SARIF file. For more information, see "Analyzing your code with CodeQL queries."
3. github upload-results to upload the resulting SARIF files to GitHub where the results are matched to a branch or pull request and displayed as code scanning alerts. For more information, see "Uploading CodeQL analysis results to GitHub."

Example CI configuration for CodeQL analysis

This is an example of the full series of commands for the CodeQL CLI that you might use to analyze a codebase with two supported languages and then upload the results to GitHub.

# Create CodeQL databases for Java and Python in the 'codeql-dbs' directory
# Call the normal build script for the codebase: 'myBuildScript'

codeql database create codeql-dbs --source-root=src \
    --db-cluster --language=java,python --command=./myBuildScript

# Analyze the CodeQL database for Java, 'codeql-dbs/java'
# Tag the data as 'java' results and store in: 'java-results.sarif'

codeql database analyze codeql-dbs/java java-code-scanning.qls \
    --format=sarif-latest --sarif-category=java --output=java-results.sarif

# Analyze the CodeQL database for Python, 'codeql-dbs/python'
# Tag the data as 'python' results and store in: 'python-results.sarif'

codeql database analyze codeql-dbs/python python-code-scanning.qls \
    --format=sarif-latest --sarif-category=python --output=python-results.sarif

# Upload the SARIF file with the Java results: 'java-results.sarif'
# The GitHub App or personal access token created for authentication
# with GitHub's REST API is available in the `GITHUB_TOKEN` environment variable.

codeql github upload-results \
    --repository=my-org/example-repo \
    --ref=refs/heads/main --commit=deb275d2d5fe9a522a0b7bd8b6b6a1c939552718 \
    --sarif=java-results.sarif

# Upload the SARIF file with the Python results: 'python-results.sarif'

codeql github upload-results \
    --repository=my-org/example-repo \
    --ref=refs/heads/main --commit=deb275d2d5fe9a522a0b7bd8b6b6a1c939552718 \
    --sarif=python-results.sarif

About the GitHub CodeQL license

License notice: If you don’t have a license for GitHub Advanced Security then, by installing this product, you are agreeing to the GitHub CodeQL Terms and Conditions.

For information about how you can try GitHub Enterprise with GitHub Advanced Security for free, see "Setting up a trial of GitHub Enterprise Cloud" and "Setting up a trial of GitHub Advanced Security" in the GitHub Enterprise Cloud documentation.