Overview

If you experience issues setting up or configuring Datadog Code Analysis, use this page to start troubleshooting. If you continue to have trouble, contact Datadog Support.

Static Analysis

For issues with the Datadog Static Analyzer, include the following information in a bug report to Support as well as your Customer Success Manager.

• Your static-analysis.datadog.yml file
• The output of your static analysis tool (such as a CLI) that is run locally or in a CI/CD pipeline
• The SARIF file produced (if there are any available)
• The URL of your repository (public or private)
• The name of the branch you ran the analysis on
• The exact command line used to run the Datadog Static Analyzer

Performance issues

If you are experiencing performance issues, you can enable the --performance-statistics flag when running the static analysis tool from the command line.

For performance issues, include the following information:

• Your static-analysis.datadog.yml file
• The output of your static analysis tool (such as a CLI) that is run locally or in a CI/CD pipeline
• The URL of your repository (public or private)

Note: If you are using Static Analysis and GitHub Actions, set the enable_performance_statistics parameter to true.

Blocking issues

If you are experiencing issues unrelated to performance or if the Datadog Static Analyzer fails to exit, run the Datadog Static Analyzer with the --debug true --performance-statistics flag.

Getting a 403 error when running the analyzer

Ensure that the following variables are correctly specified: DD_APP_KEY, DD_API_KEY, and DD_SITE when running the analyzer and datadog-ci.

Issues with SARIF uploads

When uploading results from third-party static analysis tools to Datadog, ensure that they are in the interoperable Static Analysis Results Interchange Format (SARIF) Format. Node.js version 14 or later is required.

To upload a SARIF report, follow the steps below:

1. Ensure the DD_API_KEY and DD_APP_KEY variables are defined.

2. Optionally, set a DD_SITE variable (this default to datadoghq.com).

3. Install the datadog-ci utility:

   npm install -g @datadog/datadog-ci
   

4. Run the third-party static analysis tool on your code and output the results in the SARIF format.

5. Upload the results to Datadog:

   datadog-ci sarif upload $OUTPUT_LOCATION
   

GLIBC_X.YY not found error message

If you run the static analyzer in your CI pipeline and get an error message similar to the following line:

version `GLIBC_X.YY' not found

It means that you are either:

• running your CI pipeline with a Linux distribution that contains an old version of the glibc. In this case, Datadog recommends upgrading to the latest version. The analyzer always runs with the latest of Ubuntu/Debian based-systems.
• running your CI pipeline with a Linux distribution that does not rely on the glibc (such as Alpine Linux). Instead, run your CI pipeline with a distribution that supports the latest version of the glibc (such as the stable version of Ubuntu).

Results are not being surfaced in the Datadog UI

If you are running Code Analysis on a non-GitHub repository, ensure that the first scan is ran on your default branch (for example, a branch name like master, main, prod, or production). After you commit on your default branch, non-default branches are analyzed. You can always configure your default branch in-app under Repository Settings.

If you are using Datadog’s analyzer, diff-aware scanning is enabled by default. If you running the tool within your CI pipeline, make sure that datadog-ci runs at the root of the repository being analyzed.

Software Composition Analysis

For issues with Datadog Software Composition Analysis, include the following information in a bug report to Support as well as your Customer Success Manager.

• The output of your SCA tool (such as CLI) that is run locally or in a CI/CD pipeline
• The SBOM file produced (if there are any available)
• The URL of your repository (public or private)
• The name of the branch you ran the analysis on
• The list of dependency files in your repository (such as package-lock.json, requirements.txt, or pom.xml)

Issues with SBOM uploads

While the Datadog SBOM generator is recommended, Datadog supports the ingestion of any SBOM files. Please ensure your files adhere to either the Cyclone-DX 1.4 or Cyclone-DX 1.5 formats.

Ingestion of SBOM files is verified for the following third-party tools:

• osv-scanner
• trivy

To ingest your SBOM file into Datadog, follow the steps below:

1. Install the datadog-ci CLI (requires that Node.js is installed).
2. Ensure that your DD_SITE, DD_API_KEY and DD_APP_KEY environment variables are set.
3. Invoke the tool to upload the file to Datadog. Installing and invoking the tool can be done using these two commands:

# Install datadog-ci
npm install -g @datadog/datadog-ci

# Upload SBOM file
datadog-ci sbom upload /path/to/sbom-file.json

Results are not being surfaced in the Datadog UI

If you are running Code Analysis on a non-GitHub repository, ensure that the first scan is ran on your default branch (for example, a branch name like master, main, prod, or production). After you commit on your default branch, non-default branches are analyzed.

You can always configure your default branch in-app under Repository Settings.

No package detected for C# projects

Our SBOM generator, (osv-scanner), extracts dependencies from a packages.lock.json file. If you do not have this file, you can update your project definition to generate it. Follow these instructions to update your project definition to generate a packages.lock.json file.

The generated lock file is used by osv-scanner to extract dependencies and generate an SBOM.

Further reading

Additional helpful documentation, links, and articles:

Learn about Code AnalysisDOCUMENTATION Learn about Static AnalysisDOCUMENTATION Learn about Software Composition AnalysisDOCUMENTATION