Configuring CodeQL CLI in your CI system

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 each supported programming language in the repository.
2. database analyze to run queries to analyze each CodeQL database and summarize the results in a SARIF file.
3. github upload-results to upload the resulting SARIF files 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.

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 CodeQL databases" and "Creating CodeQL databases."

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.

   # Single supported language - create one CodeQL database
   codeql database create <database> --command <build> \
         --language=<language-identifier>
   
   # Multiple supported languages - create one CodeQL database per language
   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.

For more information, see "Creating CodeQL databases."

Single language 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.

Multiple language example

This example creates two CodeQL databases for the repository checked out at /checkouts/example-repo-multi. It uses:

• --db-cluster to request analysis of more than one language.
• --language to specify which languages to create databases for.
• --command to tell the tool the build command for the codebase, here make.
• --no-run-unnecessary-builds to tell the tool to skip the build command for languages where it is not needed (like Python).

The resulting databases are stored in python and cpp subdirectories of /codeql-dbs/example-repo-multi.

$ 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] [2] 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.
$

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>

codeql database analyze <database> --format=<format> \
    --sarif-category=<language-specifier> --output=<output> \
    <queries>

For more information, see Analyzing databases with the CodeQL CLI."

Basic example of analyzing a CodeQL database

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 --sarif-category to include extra information in the SARIF file that identifies the results as JavaScript. This is essential when you have more than one CodeQL database to analyze for a single commit in a repository.

$ codeql database analyze /codeql-dbs/example-repo \
    javascript-code-scanning.qls --sarif-category=javascript \
    --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

You can check that the SARIF properties have the supported size for upload and that the file is compatible with code scanning. For more information, see "SARIF support for code scanning".

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:

• Interfacing with a secret store 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.
• For testing purposes you can pass the --github-auth-stdin command-line option and supply a temporary token via standard input.

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.

# GitHub App or personal access token available from a secret store
<call-to-retrieve-secret> | codeql github upload-results \
    --repository=<repository-name> \
    --ref=<ref> --commit=<commit> \
    --sarif=<file> --github-url=<URL> \
    --github-auth-stdin

# GitHub App or personal access token available in GITHUB_TOKEN
codeql github upload-results \
    --repository=<repository-name> \
    --ref=<ref> --commit=<commit> \
    --sarif=<file> --github-url=<URL> \
    

For more information, see "github upload-results."

Basic example of uploading results to GitHub Enterprise Server

The following 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. The example assumes that the GitHub App or personal access token created for authentication with GitHub's REST API uses the GITHUB_TOKEN environment variable.

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 \
    

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."

Example CI configuration for CodeQL analysis

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 Enterprise Server.

# 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

Troubleshooting the CodeQL CLI in your CI system

Viewing log and diagnostic information

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 --verbose option.

For more information about the type of diagnostic information available, see "Viewing code scanning logs".

Code scanning only shows analysis results from one of the analyzed languages

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.

Further reading

• Creating CodeQL databases
• Analyzing databases with the CodeQL CLI