Once you've made the CodeQL CLI available to servers in your CI system, and ensured that they can authenticate with GitHub, you're ready to generate data.
You use three different commands to generate results and upload them to GitHub:
database createto create a CodeQL database to represent the hierarchical structure of each supported programming language in the repository.
database analyzeto run queries to analyze each CodeQL database and summarize the results in a SARIF file.
github upload-resultsto upload the resulting SARIF files to GitHub where the results are matched to a branch or pull request and displayed as code scanning alerts.
You can display the command-line help for any command using the
Note: Uploading SARIF data to display as code scanning results in GitHub is supported for organization-owned repositories with GitHub Advanced Security enabled, and public repositories on GitHub.com. For more information, see "Managing security and analysis settings for your repository."
Check out the code that you want to analyze:
- For a branch, check out the head of the branch that you want to analyze.
- For a pull request, check out either the head commit of the pull request, or check out a GitHub-generated merge commit of the pull request.
Set up the environment for the codebase, making sure that any dependencies are available. For more information, see Creating databases for non-compiled languages and Creating databases for compiled languages in the documentation for the CodeQL CLI.
Find the build command, if any, for the codebase. Typically this is available in a configuration file in the CI system.
codeql database createfrom the checkout root of your repository and build the codebase.
# Single supported language - create one CodeQL databsae codeql database create <database> --command<build> --language=<language-identifier> # Multiple supported languages - create one CodeQL database per langauge codeql database create <database> --command<build> \ --db-cluster --language=<language-identifier>,<language-identifier>
Note: If you use a containerized build, you need to run the CodeQL CLI inside the container where your build task takes place.
|Specify the name and location of a directory to create for the CodeQL database. The command will fail if you try to overwrite an existing directory. If you also specify |
|Specify the identifier for the language to create a database for, one of: |
|Recommended. Use to specify the build command or script that invokes the build process for the codebase. Commands are run from the current folder or, where it is defined, from |
|Optional. Use in multi-language codebases to generate one database for each language specified by |
|Optional. Use if you run the CLI outside the checkout root of the repository. By default, the |
For more information, see Creating CodeQL databases in the documentation for the CodeQL CLI.
This example creates a CodeQL database for the repository checked out at
This example creates two CodeQL databases for the repository checked out at
/checkouts/example-repo-multi. It uses:
--db-clusterto request analysis of more than one language.
--languageto specify which languages to create databases for.
--commandto tell the tool the build command for the codebase, here
--no-run-unnecessary-buildsto tell the tool to skip the build command for languages where it is not needed (like Python).
The resulting databases are stored in
cpp subdirectories of
$ codeql database create /codeql-dbs/example-repo-multi \ --db-cluster --language python,cpp \ --command make --no-run-unnecessary-builds \ --source-root /checkouts/example-repo-multi Initializing databases at /codeql-dbs/example-repo-multi. Running build command: [make] [build-stdout] Calling python3 /codeql-bundle/codeql/python/tools/get_venv_lib.py [build-stdout] Calling python3 -S /codeql-bundle/codeql/python/tools/python_tracer.py -v -z all -c /codeql-dbs/example-repo-multi/python/working/trap_cache -p ERROR: 'pip' not installed. [build-stdout] /usr/local/lib/python3.6/dist-packages -R /checkouts/example-repo-multi [build-stdout] [INFO] Python version 3.6.9 [build-stdout] [INFO] Python extractor version 5.16 [build-stdout] [INFO]  Extracted file /checkouts/example-repo-multi/hello.py in 5ms [build-stdout] [INFO] Processed 1 modules in 0.15s [build-stdout] <output from calling 'make' to build the C/C++ code> Finalizing databases at /codeql-dbs/example-repo-multi. Successfully created databases at /codeql-dbs/example-repo-multi. $
- Create a CodeQL database (see above).
codeql database analyzeon the database and specify which queries to use.
codeql database analyze <database> --format=<format> \ --output=<output> <queries>
Note: If you analyze more than one CodeQL database for a single commit, you must specify a SARIF category for each set of results generated by this command. When you upload the results to GitHub, code scanning uses this category to store the results for each language separately. If you forget to do this, each upload overwrites the previous results.
codeql database analyze <database> --format=<format> \ --sarif-category=<language-specifier> --output=<output> <queries>
|Specify the path for the directory that contains the CodeQL database to analyze.|
|Specify the queries to run. To run the standard queries used for code scanning, use: |
|Specify the format for the results file generated by the command. For upload to GitHub this should be: |
|Specify where to save the SARIF results file.|
|Optional for single database analysis. Required to define the language when you analyze multiple databases for a single commit in a repository. Specify a category to include in the SARIF results file for this analysis. A category is used to distinguish multiple analyses for the same tool and commit, but performed on different languages or different parts of the code.|
|Optional. Use if you want to use more than one thread to run queries. The default value is |
|Optional. Use to get more detailed information about the analysis process and diagnostic data from the database creation process.|
For more information, see Analyzing databases with the CodeQL CLI in the documentation for the CodeQL CLI.
This example analyzes a CodeQL database stored at
/codeql-dbs/example-repo and saves the results as a SARIF file:
/temp/example-repo-js.sarif. It uses
Note: SARIF upload supports a maximum of 5000 results per upload. Any results over this limit are ignored. If a tool generates too many results, you should update the configuration to focus on results for the most important rules or queries.
Before you can upload results to GitHub, you must determine the best way to pass the GitHub App or personal access token you created earlier to the CodeQL CLI (see Installing CodeQL CLI in your CI system). We recommend that you review your CI system's guidance on the secure use of a secret store. The CodeQL CLI supports:
- Passing the token to the CLI via standard input using the
- Saving the secret in the environment variable
GITHUB_TOKENand running the CLI without including the
When you have decided on the most secure and reliable method for your CI server, run
codeql github upload-results on each SARIF results file and include
--github-auth-stdin unless the token is available in the environment variable
echo "$UPLOAD_TOKEN" | codeql github upload-results --repository=<repository-name> \ --ref=<ref> --commit=<commit> --sarif=<file> \ --github-auth-stdin
|Specify the OWNER/NAME of the repository to upload data to. The owner must be an organization within an enterprise that has a license for GitHub Advanced Security and GitHub Advanced Security must be enabled for the repository, unless the repository is public. For more information, see "Managing security and analysis settings for your repository."|
|Specify the name of the |
|Specify the full SHA of the commit you analyzed.|
|Specify the SARIF file to load.|
|Optional. Use to pass the CLI the GitHub App or personal access token created for authentication with GitHub's REST API via standard input. This is not needed if the command has access to a |
For more information, see github upload-results in the documentation for the CodeQL CLI.
This example uploads results from the SARIF file
temp/example-repo-js.sarif to the repository
my-org/example-repo. It tells the code scanning API that the results are for the commit
deb275d2d5fe9a522a0b7bd8b6b6a1c939552718 on the
$ echo $UPLOAD_TOKEN | codeql github upload-results --repository=my-org/example-repo \ --ref=refs/heads/main --commit=deb275d2d5fe9a522a0b7bd8b6b6a1c939552718 \ --sarif=/temp/example-repo-js.sarif --github-auth-stdin
There is no output from this command unless the upload was unsuccessful. The command prompt returns when the upload is complete and data processing has begun. On smaller codebases, you should be able to explore the code scanning alerts in GitHub shortly afterward. You can see alerts directly in the pull request or on the Security tab for branches, depending on the code you checked out. For more information, see "Triaging code scanning alerts in pull requests" and "Managing code scanning alerts for your repository."
This is an example of the series of commands 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' echo $UPLOAD_TOKEN | codeql github upload-results --repository=my-org/example-repo \ --ref=refs/heads/main --commit=deb275d2d5fe9a522a0b7bd8b6b6a1c939552718 \ --sarif=java-results.sarif --github-auth-stdin # Upload the SARIF file with the Python results: 'python-results.sarif' echo $UPLOAD_TOKEN | codeql github upload-results --repository=my-org/example-repo \ --ref=refs/heads/main --commit=deb275d2d5fe9a522a0b7bd8b6b6a1c939552718 \ --sarif=python-results.sarif --github-auth-stdin
When you analyze a CodeQL database using a code scanning query suite, in addition to generating detailed information about alerts, the CLI reports diagnostic data from the database generation step and summary metrics. For repositories with few alerts, you may find this information useful for determining if there are genuinely few problems in the code, or if there were errors generating the CodeQL database. For more detailed output from
codeql database analyze, use the
For more information about the type of diagnostic information available, see "Viewing code scanning logs".
By default, code scanning expects one SARIF results file per analysis for a repository. Consequently, when you upload a second SARIF results file for a commit, it is treated as a replacement for the original set of data.
If you want to upload more than one set of results to the code scanning API for a commit in a repository, you must identify each set of results as a unique set. For repositories where you create more than one CodeQL database to analyze for each commit, use the
--sarif-category option to specify a language or other unique category for each SARIF file that you generate for that repository.
If the CodeQL CLI is unsuitable for use in your CI system, the CodeQL runner is available as an alternative. Typically, this is needed if the CI system would need to orchestrate compiler invocations as well as running CodeQL analysis. For more information, see "Running CodeQL runner in your CI system."