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Showing content from https://docs.gitlab.com/user/application_security/secret_detection/pipeline/ below:

Pipeline secret detection | GitLab Docs

• Tier: Free, Premium, Ultimate
• Offering: GitLab.com, GitLab Self-Managed, GitLab Dedicated

Pipeline secret detection scans files after they are committed to a Git repository and pushed to GitLab.

After you enable pipeline secret detection, scans run in a CI/CD job named secret_detection. You can run scans and view pipeline secret detection JSON report artifacts in any GitLab tier.

With GitLab Ultimate, pipeline secret detection results are also processed so you can:

• See them in the merge request widget, pipeline security report, and vulnerability report.
• Use them in approval workflows.
• Review them in the security dashboard.
• Automatically respond to leaks in public repositories.
• Enforce consistent secret detection rules across projects by using security policies.

For an interactive reading and how-to demo of this pipeline secret detection documentation see:

• How to enable secret detection in GitLab Application Security Part 1/2
• How to enable secret detection in GitLab Application Security Part 2/2

For other interactive reading and how-to demos, see the Get Started With GitLab Application Security Playlist.

Different features are available in different GitLab tiers.

To get started with pipeline secret detection, select a pilot project and enable the analyzer.

Prerequisites:

• You have a Linux-based runner with the docker or kubernetes executor. If you use hosted runners for GitLab.com, this is enabled by default.
  • Windows Runners are not supported.
  • CPU architectures other than amd64 are not supported.
• You have a .gitlab-ci.yml file that includes the test stage.

Enable the secret detection analyzer by using one of the following:

• Edit the .gitlab-ci.yml file manually. Use this method if your CI/CD configuration is complex.
• Use an automatically configured merge request. Use this method if you don’t have a CI/CD configuration, or your configuration is minimal.
• Enable pipeline secret detection in a scan execution policy.

If this is your first time running a secret detection scan on your project, you should run a historic scan immediately after you enable the analyzer.

After you enable pipeline secret detection, you can customize the analyzer settings.

This method requires you to manually edit an existing .gitlab-ci.yml file.

1. On the left sidebar, select Search or go to and find your project.

2. Select Build > Pipeline editor.

3. Copy and paste the following to the bottom of the .gitlab-ci.yml file:

   include:
     - template: Jobs/Secret-Detection.gitlab-ci.yml

4. Select the Validate tab, then select Validate pipeline. The message Simulation completed successfully indicates the file is valid.

5. Select the Edit tab.

6. Optional. In the Commit message text box, customize the commit message.

7. In the Branch text box, enter the name of the default branch.

8. Select Commit changes.

Pipelines now include a pipeline secret detection job. Consider running a historic scan after you enable the analyzer.

This method automatically prepares a merge request to add a .gitlab-ci.yml file that includes the pipeline secret detection template. Merge the merge request to enable pipeline secret detection.

To enable pipeline secret detection:

1. On the left sidebar, select Search or go to and find your project.
2. Select Secure > Security configuration.
3. In the Pipeline secret detection row, select Configure with a merge request.
4. Optional. Complete the fields.
5. Select Create merge request.
6. Review and merge the merge request.

Pipelines now include a pipeline secret detection job.

Pipeline secret detection is optimized to balance coverage and run time. Only the current state of the repository and future commits are scanned for secrets. To identify secrets already present in the repository’s history, run a historic scan once after enabling pipeline secret detection. Scan results are available only after the pipeline is completed.

Exactly what is scanned for secrets depends on the type of pipeline, and whether any additional configuration is set.

By default, when you run a pipeline:

• On a branch:
  • On the default branch, the Git working tree is scanned. This means the current repository state is scanned as though it were a typical directory.
  • On a new, non-default branch, the content of all commits from the most recent commit on the parent branch to the latest commit is scanned.
  • On an existing, non-default branch, the content of all commits from the last pushed commit to the latest commit is scanned.
• On a merge request, the content of all commits on the branch is scanned. If the analyzer can’t access every commit, the content of all commits from the parent to the latest commit is scanned. To scan all commits, you must enable merge request pipelines.

To override the default behavior, use the available CI/CD variables.

By default, pipeline secret detection scans only the current state of the Git repository. Any secrets contained in the repository’s history are not detected. Run a historic scan to check for secrets from all commits and branches in the Git repository.

You should run a historic scan only once, after enabling pipeline secret detection. Historic scans can take a long time, especially for larger repositories with lengthy Git histories. After completing an initial historic scan, use only standard pipeline secret detection as part of your pipeline.

If you enable pipeline secret detection with a scan execution policy, by default the first scheduled scan is a historic scan.

To run a historic scan:

1. On the left sidebar, select Search or go to and find your project.
2. Select Build > Pipelines.
3. Select New pipeline.
4. Add a CI/CD variable:
   1. From the dropdown list, select Variable.
   2. In the Input variable key box, enter SECRET_DETECTION_HISTORIC_SCAN.
   3. In the Input variable value box, enter true.
5. Select New pipeline.

• Tier: Ultimate
• Offering: GitLab.com, GitLab Self-Managed, GitLab Dedicated

History

• Introduced in GitLab 17.0.

When developers make changes to a file with identified secrets, it’s likely that the positions of these secrets will also change. Pipeline secret detection may have already flagged these secrets as vulnerabilities, tracked in the vulnerability report. These vulnerabilities are associated with specific secrets for easy identification and action. However, if the detected secrets aren’t accurately tracked as they shift, managing vulnerabilities becomes challenging, potentially resulting in duplicate vulnerability reports.

Pipeline secret detection uses an advanced vulnerability tracking algorithm to more accurately identify when the same secret has moved within a file due to refactoring or unrelated changes.

For more information, see the confidential project https://gitlab.com/gitlab-org/security-products/post-analyzers/tracking-calculator. The content of this project is available only to GitLab team members.

• The algorithm does not support the workflow where the existing finding lacks a tracking signature and does not share the same location as the newly detected finding.
• For some rule types, such as cryptographic keys, pipeline secret detection identifies leaks by matching prefix of the secret rather than the entire secret value. In this scenario, the algorithm consolidates different secrets of the same rule type in a file into a single finding, rather than treating each distinct secret as a separate finding. For example, the SSH Private Key rule type matches only the -----BEGIN OPENSSH PRIVATE KEY----- prefix of a value to confirm the presence of a SSH private key. If there are two distinct SSH Private Keys within the same file, the algorithm considers both values as identical and reports only one finding instead of two.
• The algorithm’s scope is limited to a per-file basis, meaning that the same secret appearing in two different files is treated as two distinct findings.

Pipeline secret detection scans the repository’s content for specific patterns. Each pattern matches a specific type of secret and is specified in a rule by using a TOML syntax. GitLab maintains the default set of rules.

With GitLab Ultimate you can extend these rules to suit your needs. For example, while personal access tokens that use a custom prefix are not detected by default, you can customize the rules to identify these tokens. For details, see Customize analyzer rulesets.

To confirm which secrets are detected by pipeline secret detection, see Detected secrets. To provide reliable, high-confidence results, pipeline secret detection only looks for passwords or other unstructured secrets in specific contexts like URLs.

When a secret is detected a vulnerability is created for it. The vulnerability remains as “Still detected” even if the secret is removed from the scanned file and pipeline secret detection has been run again. This is because the leaked secret continues to be a security risk until it has been revoked. Removed secrets also persist in the Git history. To remove a secret from the Git repository’s history, see Redact text from repository.

Pipeline secret detection outputs the file gl-secret-detection-report.json as a job artifact. The file contains detected secrets. You can download the file for processing outside GitLab.

For more information, see the report file schema and the example report file.

Job results are also reported on the:

• Merge request widget: shows new findings introduced in the merge request.
• Pipeline security report: displays all findings from the latest pipeline run.
• Vulnerability report: provides centralized management of all security findings.
• Security dashboard: offers organization-wide visibility into all vulnerabilities across projects and groups.

Pipeline secret detection provides detailed information about potential secrets found in your repository. Each secret includes the type of secret leaked and remediation guidelines.

When reviewing results:

1. Look at the surrounding code to determine if the detected pattern is actually a secret
2. Test whether the detected value is a working credential.
3. Consider the repository’s visibility and the secret’s scope.
4. Address active, high-privilege secrets first.

Detections by pipeline secret detection often fall into one of three categories:

• True positives: Legitimate secrets that should be rotated and removed. For example:
  • Active API keys, database passwords, authentication tokens
  • Private keys and certificates
  • Service account credentials
• False positives: Detected patterns that aren’t actual secrets. For example:
  • Example values in documentation
  • Test data or mock credentials
  • Configuration templates with placeholder values
• Historical findings: Secrets that were previously committed but might not be active. These detections:
  • Require investigation to determine current status
  • Should still be rotated as a precaution

When a secret is detected, you should rotate it immediately. GitLab attempts to automatically revoke some types of leaked secrets. For those that are not automatically revoked, you must do so manually.

Purging a secret from the repository’s history does not fully address the leak. The original secret remains in any existing forks or clones of the repository.

For instructions on how to respond to a leaked secret, select the vulnerability in the vulnerability report.

Before deploying pipeline secret detection across your organization, optimize the configuration to reduce false positives and improve accuracy for your specific environment.

False positives can create alert fatigue and reduce trust in the tool. Consider using custom ruleset configuration (Ultimate only):

• Exclude known safe patterns specific to your codebase.
• Adjust sensitivity for rules that frequently trigger on non-secrets.
• Add custom rules for organization-specific secret formats.

To optimize performance in large repositories or organizations with many projects, review your:

• Scan scope management:
  • Turn off historical scanning after you run a historical scan in a project.
  • Schedule historic scans during low-usage periods.
• Resource allocation:
  • Allocate sufficient runner resources for larger repositories.
  • Consider dedicated runners for security scanning workloads.
  • Monitor scan duration and optimize based on repository size.

Before applying optimizations organization-wide:

1. Validate that optimizations don’t miss legitimate secrets.
2. Track false positive reduction and scan performance improvements.
3. Maintain records of effective optimization patterns.

You should implement pipeline secret detection incrementally. Start with a small-scale pilot to understand the tool’s behavior before rolling out the feature across your organization.

Follow these guidelines when you roll out pipeline secret detection:

1. Choose a pilot project. Suitable projects have:
   • Active development with regular commits.
   • A manageable codebase size.
   • A team familiar with GitLab CI/CD.
   • Willingness to iterate on configuration.
2. Start simple. Enable pipeline secret detection with default settings on your pilot project.
3. Monitor results. Run the analyzer for one or two weeks to understand typical findings.
4. Address detected secrets. Remediate any legitimate secrets found.
5. Tune your configuration. Adjust settings based on initial results.
6. Document the implementation. Record common false positives and remediation patterns.

History

• Introduced in GitLab 14.10.

The default scanner images are built off a base Alpine image for size and maintainability. GitLab offers Red Hat UBI versions of the images that are FIPS-enabled.

To use the FIPS-enabled images, either:

• Set the SECRET_DETECTION_IMAGE_SUFFIX CI/CD variable to -fips.
• Add the -fips extension to the default image name.

For example:

variables:
  SECRET_DETECTION_IMAGE_SUFFIX: '-fips'

include:
  - template: Jobs/Secret-Detection.gitlab-ci.yml

Debug-level logging can help when troubleshooting. For details, see debug-level logging.

For information on this, see the general Application Security troubleshooting section.

The pipeline secret detection analyzer relies on generating patches between commits to scan content for secrets. If the number of commits in a merge request is greater than the value of the GIT_DEPTH CI/CD variable, Secret Detection fails to detect secrets.

For example, you could have a pipeline triggered from a merge request containing 60 commits and the GIT_DEPTH variable set to less than 60. In that case the pipeline secret detection job fails because the clone is not deep enough to contain all of the relevant commits. To verify the current value, see pipeline configuration.

To confirm this as the cause of the error, enable debug-level logging, then rerun the pipeline. The logs should look similar to the following example. The text “object not found” is a symptom of this error.

ERRO[2020-11-18T18:05:52Z] object not found
[ERRO] [secrets] [2020-11-18T18:05:52Z] ▶ Couldn't run the gitleaks command: exit status 2
[ERRO] [secrets] [2020-11-18T18:05:52Z] ▶ Gitleaks analysis failed: exit status 2

To resolve the issue, set the GIT_DEPTH CI/CD variable to a higher value. To apply this only to the pipeline secret detection job, the following can be added to your .gitlab-ci.yml file:

secret_detection:
  variables:
    GIT_DEPTH: 100

Pipeline secret detection can fail with the message ERR fatal: ambiguous argument error if your repository’s default branch is unrelated to the branch the job was triggered for. See issue !352014 for more details.

To resolve the issue, make sure to correctly set your default branch on your repository. You should set it to a branch that has related history with the branch you run the secret-detection job on.

The GitLab pipeline secret detection analyzer only supports running on the amd64 CPU architecture. This message indicates that the job is being run on a different architecture, such as arm.

Secret detection might fail with an exit status of 128. This can be caused by a change to the user on the Docker image.

For example:

$ /analyzer run
[INFO] [secrets] [2024-06-06T07:28:13Z] ▶ GitLab secrets analyzer v6.0.1
[INFO] [secrets] [2024-06-06T07:28:13Z] ▶ Detecting project
[INFO] [secrets] [2024-06-06T07:28:13Z] ▶ Analyzer will attempt to analyze all projects in the repository
[INFO] [secrets] [2024-06-06T07:28:13Z] ▶ Loading ruleset for /builds....
[WARN] [secrets] [2024-06-06T07:28:13Z] ▶ /builds/....secret-detection-ruleset.toml not found, ruleset support will be disabled.
[INFO] [secrets] [2024-06-06T07:28:13Z] ▶ Running analyzer
[FATA] [secrets] [2024-06-06T07:28:13Z] ▶ get commit count: exit status 128

To work around this issue, add a before_script with the following:

before_script:
    - git config --global --add safe.directory "$CI_PROJECT_DIR"

For more information about this issue, see issue 465974.

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