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If you experience issues setting up or configuring Datadog Code Security, use this page to start troubleshooting. If you continue to have trouble, contact Datadog Support.
For issues with the Datadog static analyzer, include the following information in a bug report to Datadog Support.
static-analysis.datadog.yml
fileIf 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:
static-analysis.datadog.yml
fileNote: If you are using Static Analysis and GitHub Actions, set the enable_performance_statistics
parameter to true.
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.
Ensure that the following variables are correctly specified: DD_APP_KEY
, DD_API_KEY
, and DD_SITE
when running the analyzer and datadog-ci
.
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:
Ensure the DD_API_KEY
and DD_APP_KEY
variables are defined.
Optionally, set a DD_SITE
variable (this default to datadoghq.com
).
Install the datadog-ci
utility:
npm install -g @datadog/datadog-ci
Run the third-party static analysis tool on your code and output the results in the SARIF format.
Upload the results to Datadog:
datadog-ci sarif upload $OUTPUT_LOCATION
GLIBC_X.YY not found
error messageIf 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:
If you are running Code Security 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.
For issues with Datadog Software Composition Analysis (SCA), include the following information in a bug report to Datadog Support.
package-lock.json
, requirements.txt
, or pom.xml
)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:
To ingest your SBOM file into Datadog, follow the steps below:
datadog-ci
CLI (requires that Node.js is installed).DD_SITE
, DD_API_KEY
and DD_APP_KEY
environment variables are set.# Install datadog-ci
npm install -g @datadog/datadog-ci
# Upload SBOM file
datadog-ci sbom upload /path/to/sbom-file.json
If you are running static scanning 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.
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.
There are a series of steps that must run successfully for vulnerability information to appear either in the Service Catalog Security View or in the Vulnerability Explorer. It is important to check each step when investigating this issue.
If you have enabled runtime vulnerability detection, you can use the metric datadog.apm.appsec_host
to check if SCA is running.
datadog.apm.appsec_host
. If the metric doesn’t exist, then there are no services running ASM. If the metric exists, the services are reported with the metric tags host
and service
.service
to see which services are running ASM.If you are not seeing datadog.apm.appsec_host
, check the in-app instructions to confirm that all steps for the initial setup are complete.
ASM data is sent with APM traces. See APM troubleshooting to confirm APM setup and check for connection errors.
See the Application Security product set up documentation to validate you you are using the right version of the tracer. These minimum versions are required to start sending telemetry data that includes library information.
Ensure the DD_INSTRUMENTATION_TELEMETRY_ENABLED
environment variable (DD_TRACE_TELEMETRY_ENABLED
for Node.js) is set to true
, or the corresponding system property for your language is enabled. For example in Java: -Ddd.instrumentation.telemetry.enabled=true
.
SCA can be enabled using two methods: the UI or manually using an environment variable. When you disable SCA, you must use the same method you used to enable SCA. For example, if you enabled SCA manually, you cannot disable it using the UI. You must disable it manually.
Typically, SCA is enabled and disabled on a service using the UI.
To disable [Software Composition Analysis][14] using the UI:
To disable SCA manually:
DD_APPSEC_SCA_ENABLED
environment variable, remove the DD_APPSEC_SCA_ENABLED=true
environment variable from your application configuration, and restart your service. This does not apply to PHP apps.To disable IAST, remove the DD_IAST_ENABLED=true
environment variable from your application configuration or set it to false
as DD_IAST_ENABLED=false
, and restart your service.