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このバージョンの GitHub Enterprise はこの日付をもって終了となりました: 2022-06-03. 重大なセキュリティの問題に対してであっても、パッチリリースは作成されません。 パフォーマンスの向上、セキュリティの改善、新機能のためには、最新バージョンのGitHub Enterpriseにアップグレードしてく� さい。 アップグレードに関する支援については、GitHub Enterprise supportに連絡してく� さい。

Configuring CodeQL CLI in your CI system

You can configure your continuous integration system to run the CodeQL CLI, perform CodeQL analysis, and upload the results to GitHub Enterprise Server for display as code scanning alerts.

Code scanning is available for organization-owned repositories where GitHub Advanced Security is enabled. 詳しい情� �については、「GitHub Advanced Security について」を参照してく� さい。

Note: Your site administrator must enable code scanning for GitHub Enterprise Serverインスタンス before you can use this feature. For more information, see "Configuring code scanning for your appliance."

Note: This article describes features present in the version of CodeQL CLI available at the time of the release of GitHub Enterprise Server. If your enterprise uses a more recent version of CodeQL CLI, see the GitHub Enterprise Cloud documentation instead.

About generating code scanning results with CodeQL CLI

Once you've made the CodeQL CLI available to servers in your CI system, and ensured that they can authenticate with GitHub Enterprise Server, you're ready to generate data.

You use three different commands to generate results and upload them to GitHub Enterprise Server:

  1. database create to create a CodeQL database to represent the hierarchical structure of a supported programming language in the repository.
  2. database analyze to run queries to analyze the CodeQL database and summarize the results in a SARIF file.
  3. github upload-results to upload the resulting SARIF file to GitHub Enterprise Server 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 --help option.

Note: Uploading SARIF data to display as code scanning results in GitHub Enterprise Server is supported for organization-owned repositories with GitHub Advanced Security enabled. For more information, see "Managing security and analysis settings for your repository."

Creating CodeQL databases to analyze

  1. 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.
  2. 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.

  3. Find the build command, if any, for the codebase. Typically this is available in a configuration file in the CI system.

  4. Run codeql database create from the checkout root of your repository and build the codebase.

    codeql database create <database> --command<build> --language=<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.

OptionRequiredUsage
<database>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 --db-cluster, this is the parent directory and a subdirectory is created for each language analyzed.
--languageSpecify the identifier for the language to create a database for, one of: cpp`, `csharp`, `go`, `java`, `javascript`, and `python (use javascript to analyze TypeScript code).
--commandRecommended. 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 --source-root. Not needed for Python and JavaScript/TypeScript analysis.
--source-rootOptional. Use if you run the CLI outside the checkout root of the repository. By default, the database create command assumes that the current directory is the root directory for the source files, use this option to specify a different location.

For more information, see Creating CodeQL databases in the documentation for the CodeQL CLI.

Basic example

This example creates a CodeQL database for the repository checked out at /checkouts/example-repo. It uses the JavaScript extractor to create a hierarchical representation of the JavaScript and TypeScript code in the repository. The resulting database is stored in /codeql-dbs/example-repo.

$ codeql database create /codeql-dbs/example-repo --language=javascript \
    --source-root /checkouts/example-repo

> Initializing database at /codeql-dbs/example-repo.
> Running command [/codeql-home/codeql/javascript/tools/autobuild.cmd]
    in /checkouts/example-repo.
> [build-stdout] Single-threaded extraction.
> [build-stdout] Extracting
...
> Finalizing database at /codeql-dbs/example-repo.
> Successfully created database at /codeql-dbs/example-repo.

Analyzing a CodeQL database

  1. Create a CodeQL database (see above).
  2. Run codeql database analyze on the database and specify which queries to use.
    codeql database analyze <database> --format=<format> \
        --output=<output>  <queries>
OptionRequiredUsage
<database>Specify the path for the directory that contains the CodeQL database to analyze.
<packs,queries>Specify CodeQL packs or queries to run. To run the standard queries used for code scanning, omit this parameter. To see the other query suites included in the CodeQL CLI bundle, look in /<extraction-root>/qlpacks/codeql/<language>-queries/codeql-suites. For information about creating your own query suite, see Creating CodeQL query suites in the documentation for the CodeQL CLI.
--formatSpecify the format for the results file generated by the command. For upload to GitHub this should be: sarifv2.1.0. For more information, see "SARIF support for code scanning."
--outputSpecify where to save the SARIF results file.
--threadsOptional. Use if you want to use more than one thread to run queries. The default value is 1. You can specify more threads to speed up query execution. To set the number of threads to the number of logical processors, specify 0.
--verboseOptional. Use to get more detailed information about the analysis process.

For more information, see Analyzing databases with the CodeQL CLI in the documentation for the CodeQL CLI.

Basic example

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.

$ codeql database analyze /codeql-dbs/example-repo  \
    javascript-code-scanning.qls 
    --format=sarifv2.1.0 --output=/temp/example-repo-js.sarif

> Running queries.
> Compiling query plan for /codeql-home/codeql/qlpacks/codeql-javascript/AngularJS/DisablingSce.ql.
...
> Shutting down query evaluator.
> Interpreting results.

Uploading results to GitHub Enterprise Server

ノート:

  • SARIF upload supports a maximum of 5000 results per upload. この制限を超えた結果は無視されます。 ツールがあまりに多くの結果を生成する� �合、最も重要なルールやクエリに対する結果に焦点を当てるよう、設定を更新すべきです。

  • For each upload, SARIF upload supports a maximum size of 10 MB for the gzip-compressed SARIF file. Any uploads over this limit will be rejected. If your SARIF file is too large because it contains 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 Enterprise Server, 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 --github-auth-stdin option (recommended).
  • Saving the secret in the environment variable GITHUB_TOKEN and running the CLI without including the --github-auth-stdin option.

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 GITHUB_TOKEN.

echo "$UPLOAD_TOKEN" | codeql github upload-results --repository=<repository-name> \
      --ref=<ref> --commit=<commit> --sarif=<file> \
      --github-url=<URL> --github-auth-stdin
OptionRequiredUsage
--repositorySpecify 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. For more information, see "Managing security and analysis settings for your repository."
--refSpecify the name of the ref you checked out and analyzed so that the results can be matched to the correct code. For a branch use: refs/heads/BRANCH-NAME, for the head commit of a pull request use refs/pull/NUMBER/head, or for the GitHub-generated merge commit of a pull request use refs/pull/NUMBER/merge.
--commitSpecify the full SHA of the commit you analyzed.
--sarifSpecify the SARIF file to load.
--github-urlSpecify the URL for GitHub Enterprise Server.
--github-auth-stdinOptional. 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 GITHUB_TOKEN environment variable set with this token.

For more information, see github upload-results in the documentation for the CodeQL CLI.

Basic example

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 main branch.

$ 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-url=https://github.example.com \
    --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 Enterprise Server 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."

Further reading