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About the CodeQL CLI |
You can use the {% data variables.product.prodname_codeql_cli %} to run {% data variables.product.prodname_codeql %} processes locally on software projects or to generate {% data variables.product.prodname_code_scanning %} results for upload to {% data variables.product.github %}. |
{% data reusables.gated-features.codeql %} |
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Software developers and security researchers can secure their code using {% data variables.product.prodname_codeql %} analysis. For more information about {% data variables.product.prodname_codeql %}, see AUTOTITLE.
{% data reusables.code-scanning.what-is-codeql-cli %}
You can use the {% data variables.product.prodname_codeql_cli %} to:
- Run {% data variables.product.prodname_codeql %} analyses using queries provided by {% data variables.product.prodname_dotcom %} engineers and the open source community
- Generate code scanning alerts that you can upload to display in {% data variables.product.github %}
- Create {% data variables.product.prodname_codeql %} databases to use in the {% data variables.product.prodname_codeql %} for {% data variables.product.prodname_vscode %} extension.
- Develop and test custom {% data variables.product.prodname_codeql %} queries to use in your own analyses
The {% data variables.product.prodname_codeql_cli %} can analyze:
- Dynamic languages, for example, JavaScript and Python.
- Compiled languages, for example, {% data variables.code-scanning.compiled_languages %}
- Codebases written in a mixture of languages.
For information about setting up the {% data variables.product.prodname_codeql_cli %}, see AUTOTITLE.
About using the {% data variables.product.prodname_codeql_cli %} for {% data variables.product.prodname_code_scanning %}
You can use the {% data variables.product.prodname_codeql_cli %} to run {% data variables.product.prodname_code_scanning %} on code that you're processing in a third-party continuous integration (CI) system. {% data reusables.code-scanning.about-code-scanning %} For an overview of using code scanning with external CI systems, see AUTOTITLE. For recommended specifications (RAM, CPU cores, and disk) for running {% data variables.product.prodname_codeql %} analysis, see AUTOTITLE.
Alternatively, you can use {% data variables.product.prodname_actions %} or Azure DevOps pipelines to scan code using the {% data variables.product.prodname_codeql_cli %}. For more information, see AUTOTITLE or Configure {% data variables.product.prodname_ghas_azdo %} in Microsoft Learn.
For an overview of all the options for using {% data variables.product.prodname_codeql %} analysis for code scanning, see AUTOTITLE.
{% data reusables.code-scanning.licensing-note %}
If you choose to run the {% data variables.product.prodname_codeql_cli %} directly, you first have to install the {% data variables.product.prodname_codeql_cli %} locally. If you are planning to use the {% data variables.product.prodname_codeql_cli %} with an external CI system, you need to make the {% data variables.product.prodname_codeql_cli %} available to servers in your CI system. For more information, see AUTOTITLE.
Once the {% data variables.product.prodname_codeql_cli %} is set up, you can use three different commands to generate results and upload them to {% data variables.product.github %}:
database createto create a {% data variables.product.prodname_codeql %} database to represent the hierarchical structure of each supported programming language in the repository. For more information, see AUTOTITLE.database analyzeto run queries to analyze each {% data variables.product.prodname_codeql %} database and summarize the results in a SARIF file. For more information, see AUTOTITLE.github upload-resultsto upload the resulting SARIF files to {% data variables.product.github %} where the results are matched to a branch or pull request and displayed as {% data variables.product.prodname_code_scanning %} alerts. For more information, see AUTOTITLE.
{% data reusables.code-scanning.upload-sarif-ghas %}
This is an example of the full series of commands for the {% data variables.product.prodname_codeql_cli %} that you might use to analyze a codebase with two supported languages and then upload the results to {% data variables.product.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 {% data variables.product.prodname_github_app %} or {% data variables.product.pat_generic %} created for authentication
# with {% data variables.product.company_short %}'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{% data reusables.code-scanning.codeql-license %}