[{"data":1,"prerenderedAt":817},["ShallowReactive",2],{"/en-us/blog/migration-guide-github-advanced-security-to-gitlab-ultimate":3,"navigation-en-us":40,"banner-en-us":450,"footer-en-us":460,"blog-post-authors-en-us-Fernando Diaz":701,"blog-related-posts-en-us-migration-guide-github-advanced-security-to-gitlab-ultimate":715,"blog-promotions-en-us":755,"next-steps-en-us":807},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":27,"isFeatured":12,"meta":28,"navigation":12,"path":29,"publishedDate":20,"seo":30,"stem":35,"tagSlugs":36,"__hash__":39},"blogPosts/en-us/blog/migration-guide-github-advanced-security-to-gitlab-ultimate.yml","Migration Guide Github Advanced Security To Gitlab Ultimate",[7],"fernando-diaz",null,"security",{"slug":11,"featured":12,"template":13},"migration-guide-github-advanced-security-to-gitlab-ultimate",true,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"Migration guide: GitHub Advanced Security to GitLab Ultimate","Understand the similarities and differences between GitLab Ultimate and GitHub Advanced Security. Then follow this in-depth tutorial to make the move to the GitLab DevSecOps platform.",[18],"Fernando Diaz","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749666187/Blog/Hero%20Images/blog-image-template-1800x945__6_.png","2024-05-01","GitLab is the most comprehensive AI-powered DevSecOps platform, enabling organizations to deliver more secure software faster with one platform for your entire software delivery lifecycle. GitHub provides an Advanced Security add-on, which enables additional security features within GitHub. However, it lacks the depth and breadth of security features provided natively by GitLab. Organizations looking to migrate to GitLab Ultimate to enhance their security across all areas of the SDLC can use this guide to compare the two offerings and as a tutorial to move to the GitLab platform.\n\nThis article includes:\n\n- [A comparison between GitLab Ultimate and GitHub Advanced Security](#a-comparison-between-gitlab-ultimate-and-github-advanced-security)\n- [How to migrate a GitHub repository to GitLab](#how-to-migrate-a-github-repository-to-gitlab)\n- [How to migrate from GitHub Advanced Security to GitLab Ultimate feature-by-feature](#how-to-migrate-feature-by-feature)\n- [An introduction to additional GitLab Ultimate's security features](#additional-gitlab-ultimate-security-features)\n\n## A comparison between GitLab Ultimate and GitHub Advanced Security\n\n[GitLab Ultimate](https://about.gitlab.com/pricing/ultimate/) is GitLab's top subscription tier for enterprises looking to deliver secure software faster. GitHub Advanced Security is an add-on to GitHub Enterprise, which enables additional security features.\n\n### Similarities between GitLab Ultimate and GitHub Advanced Security\n\nGitLab Ultimate and GitHub Advanced Security both provide:\n- Static Application Security Testing ([SAST](https://docs.gitlab.com/ee/user/application_security/sast/)), secret scanning, and dependency scanning\n- contextual vulnerability intelligence and resolution advice\n- a list of dependencies or software bill of materials ([SBOM](https://about.gitlab.com/blog/the-ultimate-guide-to-sboms/))\n- security metrics and insights\n\n### Differences between GitLab Ultimate and GitHub Advanced Security\n\nGitLab Ultimate differs from GitHub Advanced Security in the following ways:\n\n- GitLab natively provides additional code scanners such as container scanning, Dynamic Application Security Testing ([DAST](https://docs.gitlab.com/ee/user/application_security/dast/)), Web API fuzz testing, and more. These scanners are a mix of optimized proprietary and open source technologies with custom rulesets. For a full list, see the [GitLab AppSec documentation](https://docs.gitlab.com/ee/user/application_security/secure_your_application.html).\n- GitLab provides [granular security guardrails](https://docs.gitlab.com/ee/user/application_security/policies/) to prevent insecure code from being merged without approval.\n- GitLab security scanners can be run in [air-gapped or limited-connectivity environments](https://docs.gitlab.com/ee/user/application_security/offline_deployments/).\n- GitLab provides the [Compliance Center](https://docs.gitlab.com/ee/user/compliance/compliance_center/), which enables oversight of compliance violations across an entire organization.\n\nGitLab Ultimate also provides additional security and compliance capabilities, portfolio and value stream management, live upgrade assistance, and more. See the [GitLab Ultimate documentation](https://about.gitlab.com/pricing/ultimate/) to learn more about these additional features.\n\n## How to migrate a GitHub repository to GitLab\n\nGitLab provides a built-in importer, which allows you to import your GitHub projects from either GitHub.com or GitHub Enterprise to GitLab. The importer allows you to migrate not only the GitHub Repository to GitLab, but several other objects, including issues, collaborators (members), and pull requests. For a complete list of what can be migrated, see the [GitHub imported data documentation](https://docs.gitlab.com/ee/user/project/import/github.html#imported-data). You can perform the migration as follows:\n1. On the left sidebar, at the top, select **Create new (+)**.\n2. Select **New project/repository** under the **In GitLab** section.\n3. Select **Import project**.\n\n![Import project selection](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/1-Import-Project.png)\n\n4. Press the **GitHub** button.\n    - If using GitLab self-managed, then you must [enable the GitHub importer](https://docs.gitlab.com/ee/administration/settings/import_and_export_settings.html#configure-allowed-import-sources).\n    - Note that other importers can be initiated in the same way.\n5. Now, you can do one of the following:\n    - Authorize with GitHub Oauth by selecting **Authorize with GitHub**.\n    - Use a GitHub personal access token:\n       - Go to [https://github.com/settings/tokens/new](https://github.com/settings/tokens/new).\n       - In the **Note** field, enter a token description.\n       - Select the **repo** scope.\n       - Optionally, to import Collaborators, select the **read:org** scope.\n       - Press the **Generate token** button.\n       - On the GitLab import page, in the Personal Access Token field, paste the GitHub personal access token.\n6. Press the **Authenticate** button.\n7. Select the items you wish to migrate.\n8. Select the projects you wish to migrate and to where.\n9. Press the **Import** button.\n\nYour imported project should now be in your workspace. For additional guidance on migrating from GitHub to GitLab, watch this video:\n\n\u003C!-- blank line -->\n\u003Cfigure class=\"video_container\">\n  \u003Ciframe src=\"https://www.youtube.com/embed/0Id5oMl1Kqs?si=HEpZVy94cpfPfAky\" frameborder=\"0\" allowfullscreen=\"true\"> \u003C/iframe>\n\u003C/figure>\n\u003C!-- blank line -->\n\nYou can also perform the migration using a [GitHub personal access token](https://docs.gitlab.com/ee/user/project/import/github.html#use-a-github-personal-access-token) or the [GitLab REST API](https://docs.gitlab.com/ee/user/project/import/github.html#use-the-api). The importer also allows importing from other sources such as Bitbucket or Gitea. To learn more, read the [importer documentation](https://docs.gitlab.com/ee/user/project/import/).\n\n## How to migrate feature-by-feature\n\nLet’s go over how to leverage each feature provided by GitHub Advanced Security in GitLab Ultimate. You must have a [GitLab Ultimate license](https://about.gitlab.com/pricing/ultimate/) to continue. GitLab provides a [free trial](https://about.gitlab.com/free-trial/devsecops/) to get you started.\n\n### Code scanning\nGitHub provides code scanning to provide contextual vulnerability intelligence and advice for static source code. The same can be done within GitLab by enabling [SAST](https://docs.gitlab.com/ee/user/application_security/sast/). GitLab SAST scanners cover a wider set of programming languages and frameworks than GitHub’s [CodeQL](https://docs.github.com/en/code-security/code-scanning/introduction-to-code-scanning/about-code-scanning-with-codeql#about-codeql).\n\nTo enable code scanning in GitLab, you can simply add the [SAST template](https://docs.gitlab.com/ee/user/application_security/sast/#configure-sast-in-your-cicd-yaml) to your `.gitlab-ci.yml`:\n\n```yaml\ninclude:\n  - template: Jobs/SAST.gitlab-ci.yml\n```\n\nOnce the template has been added, any time new code is checked in, SAST will auto-detect the [programming languages](https://docs.gitlab.com/ee/user/application_security/sast/#supported-languages-and-frameworks ) used in your project. It will then scan the source code for known vulnerabilities.\n\n**Note:** Security scanners can also be added to your project using GitLab's [security configuration](https://docs.gitlab.com/ee/user/application_security/configuration/), which can automatically create a merge request to update your pipeline. To learn more, see the [Configure SAST by using the UI documentation](https://docs.gitlab.com/ee/user/application_security/sast/#configure-sast-by-using-the-ui).\n\nSAST results of the diff between the feature-branch and the target-branch display in the merge request widget. The merge request widget displays SAST results and resolutions that were introduced by the changes made in the merge request.\n\n![Security scanning in merge request](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/2-SAST-MR-View.png)\n\nEach vulnerability displays data to assist with remediation, including detailed description, severity, location, and resolution information:\n\n![SAST vulnerability details](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/3-SAST-MR-View-Detailed.png)\n\nYou can take action on these vulnerabilities:\n\n- **Dismiss vulnerability**: Allows a developer to dismiss the vulnerability with a comment. This assists the security team performing a review.\n- **Create issue**: Allows an issue to be created to keep track of a vulnerability that requires additional oversight.\n\nThese changes can also be seen inline when changing to the **Changes** view within the merge request.\n\n![SAST vulnerability changes view](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/4-SAST-MR-View-Changes.png)\n\n#### Customizing SAST scanners\n\nGitLab allows you to override a SAST job definition so you can change properties like variables, dependencies, or rules. You can do this by declaring a job with the same name as the SAST job to override. Then, place this new job after the template inclusion and specify any additional keys under it.\n\nFor example, the following configuration:\n- overwrites the version the `semgrep-sast` scanner uses\n- runs a script to fetch modules from private projects before running `gosec-sast`\n- configures all scanners to search at a maximum depth of 10\n\n```yaml\ninclude:\n  - template: Jobs/SAST.gitlab-ci.yml\n\nvariables:\n  SEARCH_MAX_DEPTH: 10\n\nsemgrep-sast:\n  variables:\n    SAST_ANALYZER_IMAGE_TAG: \"3.7\"\n\ngosec-sast:\n  before_script:\n    - |\n      cat \u003C\u003CEOF > ~/.netrc\n      machine gitlab.com\n      login $CI_DEPLOY_USER\n      password $CI_DEPLOY_PASSWORD\n      EOF\n```\n\n**Note:** The available SAST jobs can be found in the [`SAST.gitlab-ci.yml` template](https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/ci/templates/Jobs/SAST.gitlab-ci.yml). Configurations can be found in the [Available SAST CI/CD variables documentation](https://docs.gitlab.com/ee/user/application_security/sast/#available-cicd-variables).\n\n#### Customizing SAST rulesets\n\nFor each SAST analyzer, GitLab processes the code then uses rules to find possible weaknesses in source code. These rules determine what types of weaknesses the scanner reports.\n\n- For Semgrep-based SAST scanners, GitLab creates, maintains, and supports the rules that are used. It combines the Semgrep open source engine, GitLab-managed detection rules, and GitLab proprietary technology for vulnerability tracking and false positive detection.\n- For other SAST analyzers, the rules are defined in the upstream projects for each scanner.\n\nYou can customize the behavior of the SAST scanners by defining a ruleset configuration file in the repository being scanned:\n- Disable predefined rules (available for all analyzers)\n- Override predefined rules (available for all analyzers)\n- Replace predefined rules by synthesizing a custom configuration using passthroughs\n\nFor more information and examples on configuring SAST rules, see the [SAST rules](https://docs.gitlab.com/ee/user/application_security/sast/rules.html) and [Customizing rulesets documentation](https://docs.gitlab.com/ee/user/application_security/sast/customize_rulesets.html).\n\n### Secret scanning\n\nGitHub provides secret scanning, which can find, block, and revoke leaked secrets. The same can be done within GitLab by enabling [Secret Detection](https://docs.gitlab.com/ee/user/application_security/secret_detection/).\n\nTo enable Secret Detection in GitLab, you can simply add the following template to your `.gitlab-ci.yml`:\n\n```yaml\ninclude:\n  - template: Jobs/Secret-Detection.gitlab-ci.yml\n```\n\nOnce the template has been added, any time new code is checked in (or a pipeline is run), the secret scanner will scan the source code for known secrets. Pipeline Secret Detection scans different aspects of your code, depending on the situation. For all methods except the “Default branch”, Pipeline Secret Detection scans commits, not the working tree. See the [Secret detection coverage documentation](https://docs.gitlab.com/ee/user/application_security/secret_detection/pipeline/#coverage) to learn more about how secret scanning works.\n\nWhen creating a merge request, Secret Detection scans every commit made on the source branch. Just like in SAST, each detected vulnerability provides the following information (such as location) and identifiers to assist with the remediation process:\n\n![Secret Detection vulnerability details](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/5-Secret-Detection-MR-Detailed.png)\n\nSimilar to SAST, you can take action on these vulnerabilities straight from the merge request, including dismissing vulnerabilities, and creating issues.\n\n#### Customizing Secret Detection jobs\n\nGitLab allows you to override a Secret Detection job definition so you change properties like variables, dependencies, or rules. You can do this by declaring a job with the same name as the Secret Detection job. Then place this new job after the template inclusion and specify any additional keys under it. For example, the following configuration:\n\n- overwrites the stage the secret detection job runs on to `security`\n- enables the historic scanning\n- changes the Secrets Analyzer version to 4.5\n\n```yaml\ninclude:\n  - template: Jobs/Secret-Detection.gitlab-ci.yml\n\nsecret_detection:\n  stage: security\n  variables:\n    SECRET_DETECTION_HISTORIC_SCAN: \"true\"\n    SECRETS_ANALYZER_VERSION: \"4.5\"\n```\n\n**Note:** The available Secret Detection jobs can be found in the [SAST.gitlab-ci.yml template](https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/ci/templates/Jobs/Secret-Detection.gitlab-ci.yml). Available configurations can be found in the [Available Secret Detection CI/CD variables documentation](https://docs.gitlab.com/ee/user/application_security/secret_detection/pipeline/#customizing-analyzer-settings).\n\n#### Customizing Secret Detection rulesets\n\nThe Secret Detection analyzer allows you to customize which secrets are reported in the GitLab UI. The following customization options can be used separately, or in combination:\n\n- disable predefined rules\n- override predefined rules\n- synthesize a custom configuration\n- specify a remote configuration file\n\nFor example, by creating the file `.gitlab/secret-detection-ruleset.toml`, in the root directory of your project, the default GitLeaks package is extended to ignore test tokens from detection:\n\n```yaml\n### extended-gitleaks-config.toml\ntitle = \"extension of gitlab's default gitleaks config\"\n\n[extend]\n### Extends default packaged path\npath = \"/gitleaks.toml\"\n\n[allowlist]\n  description = \"allow list of test tokens to ignore in detection\"\n  regexTarget = \"match\"\n  regexes = [\n    '''glpat-1234567890abcdefghij''',\n  ]\n```\n\nFor more information on overriding the predefined analyzer rules, check out the [Secret Detection documentation](https://docs.gitlab.com/ee/user/application_security/secret_detection/pipeline/#override-predefined-analyzer-rules).\n\n#### Automatic response to leaked secrets\n\nGitLab Secret Detection automatically responds when it finds certain types of leaked secrets. Automatic responses can:\n- automatically revoke the secret\n- notify the partner that issued the secret and the partner can then revoke the secret, notify its owner, or otherwise protect against abuse\n\nGitLab can also notify partners when credentials they issue are leaked in public repositories on GitLab.com. If you operate a cloud or SaaS product and you’re interested in receiving these notifications, you can implement a Partner API, which is called by the GitLab Token Revocation API.\n\nSee the [Automatic response to leaked secrets documentation](https://docs.gitlab.com/ee/user/application_security/secret_detection/automatic_response.html) to learn more.\n\n### Supply chain security\n\nGitHub enables you to secure, manage, and report on software supply chains with automated security and version updates and one-click SBOMs. GitLab can meet your supply chain security needs using the Dependency Scanning and Dependency List (SBOM) features.\n\nTo enable Dependency Scanning in GitLab, you can simply add the following template to your `.gitlab-ci.yml`:\n\n```yaml\ninclude:\n  - template: Jobs/Dependency-Scanning.gitlab-ci.yml\n```\n\nOnce the template has been added, any time new code is checked in, Dependency Scanning will auto-detect the [package managers](https://docs.gitlab.com/ee/user/application_security/dependency_scanning/#supported-languages-and-package-managers) used in your project. It will then scan the dependencies used for known vulnerabilities.\n\nDependency Scanning results of the diff between the feature-branch and the target-branch display in the merge request widget. The merge request widget displays Dependency Scanning results and resolutions that were introduced by the changes made in the merge request. Within a merge request, each vulnerability displays relevant information to assist with remediation such as identifiers, evidence, and solutions:\n\n![Dependency Scanner vulnerability details](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/6-Dependency-Scanner-MR-View-Detailed.png)\n\nSimilar to SAST and Secret Detection, you can take action on these vulnerabilities straight from the merge request, including dismissing vulnerabilities and creating issues.\n\n#### Configuring Dependency Scanning\n\nTo override a job definition (for example, to change properties like variables or dependencies), declare a new job with the same name as the one to override. Place this new job after the template inclusion and specify any additional keys under it. For example, the following code:\n\n- disables automatic remediation of vulnerable dependencies\n- requires a build job to complete before Dependency Scanning\n\n```yaml\ninclude:\n  - template: Jobs/Dependency-Scanning.gitlab-ci.yml\n\ngemnasium-dependency_scanning:\n  variables:\n    DS_REMEDIATE: \"false\"\n  dependencies: [\"build\"]\n```\n\nTo learn more about configuring the dependency scanners, see the [Customizing analyzer behavior documentation](https://docs.gitlab.com/ee/user/application_security/dependency_scanning/#customizing-analyzer-behavior).\n\n#### Generating an SBOM\n\nGitLab provides a Dependency List (SBOM) to review your project or group dependencies and key details about those dependencies, including their known vulnerabilities. This list is a collection of dependencies in your project, including existing and new findings. The Dependency List is generated after the dependency scanner runs successfully on the [default branch](https://docs.gitlab.com/ee/user/project/repository/branches/default.html). To access the Dependency List:\n\n1. On the left sidebar, select **Search or go to** and find your project.\n2. Select **Secure > Dependency List**.\n\n![Dependency list (SBOM)](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/7-Dependency-List.png)\n\nFrom here you can see the following information on your dependencies:\n\n| Field\t| Description |\n| ----- | ----------- |\n| Component\t| The dependency’s name and version. |\n| Packager | The packager used to install the dependency. |\n| Location | For system dependencies, this lists the image that was scanned. For application dependencies, this shows a link to the packager-specific lock file in your project that declared the dependency. It also shows the dependency path to a top-level dependency, if any, and if supported. |\n| License | Links to dependency’s software licenses. A warning badge that includes the number of vulnerabilities detected in the dependency. |\n| Projects | Links to the project with the dependency. If multiple projects have the same dependency, the total number of these projects is shown. To go to a project with this dependency, select the Project's number, then search for and select its name. The project search feature is supported only on groups that have up to 600 occurrences in their group hierarchy. |\n\n\u003Cp>\u003C/p>\n\nSee the [Dependency List documentation](https://docs.gitlab.com/ee/user/application_security/dependency_list/) to learn more.\n\n### Security and compliance administration\n\nGitHub Advanced Security allows you to view security metrics and insights and assess code security risk. Now let’s examine how to do the same with GitLab Ultimate.\n\n#### Viewing security metrics and insights\n\nGitLab provides [Security dashboards](https://docs.gitlab.com/ee/user/application_security/security_dashboard/) to help assess the security posture of your applications. These dashboards display a collection of metrics, ratings, and charts for the vulnerabilities detected by the security scanners run on your project:\n\n- vulnerability trends over a 30-, 60-, or 90-day timeframe for all projects in a group\n- a letter grade rating for each project based on vulnerability severity\n- the total number of vulnerabilities detected within the past 365 days, including their severity\n\nTo access the Security dashboard:\n\n1. On the left sidebar, select **Search or go to** and find your project or group.\n2. From the side tab, select **Secure > Security** dashboard.\n3. Filter and search for what you need.\n\nThe group view displays your security posture for all projects in your group:\n\n![Group Security dashboard](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/8-SD-Group.png)\n\nThe project view displays your security posture for just the project:\n\n![Project Security dashboard](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/9-SD-Project.png)\n\n#### Assess code security risk\n\nGitLab Ultimate features a [Vulnerability Report](https://docs.gitlab.com/ee/user/application_security/vulnerability_report/), which provides information about vulnerabilities from scans of the default branch. It contains cumulative results of all successful jobs, regardless of whether the pipeline was successful. At all levels, the Vulnerability Report contains:\n\n- totals of vulnerabilities per severity level\n- filters for common vulnerability attributes\n- details of each vulnerability, presented in tabular layout\n\n![Vulnerability Report](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/10-Vulnerability-Report.png)\n\nClicking on a vulnerability enables access to its [Vulnerability Page](https://docs.gitlab.com/ee/user/application_security/vulnerabilities/), which contains details of the vulnerability including a description, location, identifiers, and more. Below is an example of the Vulnerability Page for an SQL Injection vulnerability detected by our SAST scanner:\n\n![SQL Injection Vulnerability Page](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/11-Vulnerability-Page-1.png)\n\nFrom here the security team can collaborate by [changing the status of a vulnerability](https://docs.gitlab.com/ee/user/application_security/vulnerabilities/#change-the-status-of-a-vulnerability) along with a reason and [creating issues to better track changes](https://docs.gitlab.com/ee/user/application_security/vulnerabilities/#create-a-gitlab-issue-for-a-vulnerability).\n\nFrom the Vulnerability Page, you can also leverage [GitLab Duo](https://about.gitlab.com/gitlab-duo-agent-platform/), our AI-powered suite of features, to explain the vulnerability and [automatically create a merge request that resolves the vulnerability](https://docs.gitlab.com/ee/user/application_security/vulnerabilities/#vulnerability-resolution).\nGitLab Duo's [Vulnerability Explanation](https://docs.gitlab.com/ee/user/application_security/vulnerabilities/#vulnerability-explanation) uses a large language model to:\n\n- summarize the vulnerability.\n- help developers and security analysts to understand the vulnerability, how it could be exploited, and how to fix it\n- provide a suggested mitigation\n\n![SQL Injection GitLab Duo AI explanation](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/13-Explain-Vulnerability.png)\n\n## Additional GitLab Ultimate security features\n\nGitLab Ultimate contains many more security features that cannot be found within GitHub Advanced Security. A few examples of these additional security features are: additional security scanners for the complete software development lifecycle (SDLC), granular security guardrails, and custom permissions.\n\n### Security scanners for the entire SDLC\n\nOur portfolio of security scanners extends spans the SDLC.\n\n| Scanner Name | Scans | Languages/Files scanned |\n|  -------------- | ----- | ------------------------- |\n| [Static Application Security Testing (SAST)](https://docs.gitlab.com/ee/user/application_security/sast/) | Static source code | C/C++, Java, Python, Go, JavaScript, C#, and more |\n| [Dynamic Application Security Testing (DAST)](https://docs.gitlab.com/ee/user/application_security/dast/) | Running web application, live API | Language-agnostic |\n| [Infrastructure as Code (IaC) Scanning](https://docs.gitlab.com/ee/user/application_security/iac_scanning/) | IaC files |Terraform, AWS Cloud Formation, Ansible, and more |\n| [Container Scanning](https://docs.gitlab.com/ee/user/application_security/container_scanning/) | Static and running container images | Dockerfile |\n| [Dependency Scanning and License Scanning](https://docs.gitlab.com/ee/user/application_security/dependency_scanning/) | Application dependencies | Requirements.txt, Yarn, Gradle, Npm, and more |\n| [Web API Fuzz Testing](https://docs.gitlab.com/ee/user/application_security/api_fuzzing/) | Sends random/malformed data to web-api | OpenAPI, GraphQL, HAR, Postman Collection |\n| [Coverage-guided Fuzz Testing](https://docs.gitlab.com/ee/user/application_security/coverage_fuzzing/) | Sends random/malformed data to function | C/C++, Go, Swift, Python, Rust, Java, JavaScript, AFL |\n\n\u003Cp>\u003C/p>\n\nGitLab also allows you to integrate [third-party scanners](https://about.gitlab.com/blog/integrate-external-security-scanners-into-your-devsecops-workflow/) and [custom scanners](https://about.gitlab.com/blog/how-to-integrate-custom-security-scanners-into-gitlab/) into the platform. Once integrated, the scanner results are automatically presented in various places in GitLab, such as the Pipeline view, merge request widget, and Security dashboard. See the [Security Scanner Integration documentation](https://docs.gitlab.com/ee/development/integrations/secure.html) to learn more.\n\n### Granular security and compliance policies\n\nPolicies in GitLab provide security and compliance teams with [a way to enforce controls globally in their organization](https://about.gitlab.com/blog/meet-regulatory-standards-with-gitlab/). Security teams can ensure:\n\n- security scanners are enforced in development team pipelines with proper configuration\n- all scan jobs execute without any changes or alterations\n- proper approvals are provided on merge requests based on results from those findings\n\n![Merge Request Security Policies](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/14-MR-Policy.png)\n\nCompliance teams can centrally enforce multiple approvers on all merge requests and ensure various settings are enabled on projects in scope of organizational requirements, such as enabling or locking merge request and repository settings. To learn more see the [GitLab Security Policy](https://docs.gitlab.com/ee/user/application_security/policies/) documentation.\n\n### Custom roles and granular permissions\n\n[GitLab Ultimate provides custom roles](https://about.gitlab.com/blog/how-to-tailor-gitlab-access-with-custom-roles/), which allow an organization to create user roles with the precise privileges and permissions required for that organization’s needs.\n\nFor example, a user could create a “Security Auditor” role with permissions to view security vulnerabilities in the system, but not be able to view source code, nor perform any changes within the repository. This granular set of permissions enables well-defined separation of duties.\n\n![Custom role creation](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/15-Custom-Roles.png)\n\nTo learn more see the [Custom Roles](https://docs.gitlab.com/ee/user/custom_roles.html) and [available Granular Permissions](https://docs.gitlab.com/ee/user/custom_roles/abilities.html) documentation.\n\n### Compliance Center\n\nThe Compliance Center is the central location for compliance teams to manage their compliance standards’ adherence reporting, violations reporting, and compliance frameworks for their group. The Compliance Center includes the following:\n\n- [Compliance standards adherence dashboard](https://docs.gitlab.com/ee/user/compliance/compliance_center/compliance_standards_adherence_dashboard.html) lists the adherence status of projects complying to the GitLab standard.\n- [Compliance violations report](https://docs.gitlab.com/ee/user/compliance/compliance_center/compliance_violations_report.html) shows a high-level view of merge request activity for all projects in the group.\n- [Compliance frameworks report](https://docs.gitlab.com/ee/user/compliance/compliance_center/compliance_frameworks_report.html) shows all the compliance frameworks in a group.\n- [Compliance projects report](https://docs.gitlab.com/ee/user/compliance/compliance_center/compliance_projects_report.html) shows the compliance frameworks that are applied to projects in a group.\n\n![Compliance Center](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674404/Blog/Content%20Images/16-Compliance-Center.png)\n\nThese dashboards assist with making sure separation of duties is being followed to optimize compliance within your organization. To learn more see the [Compliance Center documentation](https://docs.gitlab.com/ee/user/compliance/compliance_center/).\n\n## Read more\n\nThis article covers only a portion of the wide range of security features GitLab Ultimate offers. Check out these resources to learn more about how GitLab Ultimate can help enhance your organizational security and developer efficiency:\n\n- [Why GitLab Ultimate](https://about.gitlab.com/pricing/ultimate/)\n- [Getting Started with DevSecOps Tutorial](https://gitlab-da.gitlab.io/tutorials/security-and-governance/devsecops/simply-vulnerable-notes/)\n- [Getting Started with DevSecOps Sample Project](https://gitlab.com/gitlab-da/tutorials/security-and-governance/devsecops/simply-vulnerable-notes)\n- [Import your project from GitHub to GitLab documentation](https://docs.gitlab.com/ee/user/project/import/github.html)\n- [Migrating from GitHub Actions documentation](https://docs.gitlab.com/ee/ci/migration/github_actions.html)\n- [Tutorial: Create and run your first GitLab CI/CD pipeline](https://docs.gitlab.com/ee/ci/quick_start/)\n- [Tutorial: Create a complex pipeline](https://docs.gitlab.com/ee/ci/quick_start/tutorial.html)\n- [CI/CD YAML syntax 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statement",{"items":691},[692,695,698],{"text":693,"config":694},"Terms",{"href":520,"dataGaName":521,"dataGaLocation":468},{"text":696,"config":697},"Cookies",{"dataGaName":530,"dataGaLocation":468,"id":531,"isOneTrustButton":12},{"text":699,"config":700},"Privacy",{"href":525,"dataGaName":526,"dataGaLocation":468},[702],{"id":703,"title":18,"body":8,"config":704,"content":706,"description":8,"extension":27,"meta":710,"navigation":12,"path":711,"seo":712,"stem":713,"__hash__":714},"blogAuthors/en-us/blog/authors/fernando-diaz.yml",{"template":705},"BlogAuthor",{"name":18,"config":707},{"headshot":708,"ctfId":709},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749659556/Blog/Author%20Headshots/fern_diaz.png","fjdiaz",{},"/en-us/blog/authors/fernando-diaz",{},"en-us/blog/authors/fernando-diaz","lxRJIOydP4_yzYZvsPcuQevP9AYAKREF7i8QmmdnOWc",[716,729,743],{"content":717,"config":727},{"title":718,"description":719,"authors":720,"date":722,"body":723,"category":9,"tags":724,"heroImage":726},"Prepare your pipeline for AI-discovered zero-days","AI is finding vulnerabilities faster than teams can patch. Learn how pipeline enforcement, automated triage, and AI remediation close the gap.",[721],"Omer Azaria","2026-04-20","Anthropic's [Mythos Preview model](https://red.anthropic.com/2026/mythos-preview/) recently identified thousands of zero-day vulnerabilities across every major operating system and web browser, including an OpenBSD bug that went undetected for 27 years. In testing, Mythos autonomously chained four vulnerabilities into a working browser exploit that escaped its sandbox. Anthropic is restricting access to Mythos, but the company’s head of offensive cyber research expects threats to have comparable tooling within six to twelve months.\n\nThe defender side of the equation hasn't kept pace. One third of exploited Common Vulnerabilities and Exposures (CVEs) in the first half of 2025 showed activity on or before disclosure day, before most teams even know there's something to patch. AI is compressing that window further, accelerating attackers and flooding teams with whitehat disclosures faster than they can triage. Defender tooling has improved, but most organizations can't operationalize it fast enough to close the gap between discovery and exploitation.\n\nWhen the window between disclosure and exploitation is measured in hours, the security team can't be the last line of defense. Security has to run where code enters the system: in the pipeline, on every merge request, enforced by policy. The fixes that can be automated should be. The ones that can't need to reach the right human faster than they do today.\n\n## Known vulnerabilities are already outpacing remediation\n\nThe bottleneck isn't detection, it's acting at scale on what teams already know. Sixty percent of breaches in the 2025 Verizon DBIR involved exploiting known vulnerabilities where a patch was already available. Teams couldn’t close them in time.\n\nThe backlog was untenable before Mythos. Developers spend [11 hours per month remediating vulnerabilities](https://about.gitlab.com/resources/developer-survey/) post-release instead of shipping new work. Over half of organizations have at least one open internet-facing vulnerability, and the median time to close half of those is 361 days. Exploitation takes hours, while remediation takes months.\n\nAI-assisted development is widening the gap, and stakeholders know it. By June 2025, AI-generated code was adding over 10,000 new security findings per month across Fortune 50 repositories, a 10x jump from six months earlier. Georgia Tech identified 34 [CVEs attributable to AI-generated code](https://research.gatech.edu/bad-vibes-ai-generated-code-vulnerable-researchers-warn) in March 2026, up from 6 in January, and that count reflects only the ones where AI authorship is clear. AI coding assistants hallucinate package names, reach for outdated patterns, and copy insecure examples from training data. More code, more dependencies, and more vulnerabilities per line are generated faster than security teams can review them.\n\nDefenders need to harness frontier AI models, too — not bolted onto the SDLC as external tooling, but running inside the same policies, approvals, and audit trail as the rest of the team. \n\n## Security at the speed of AI coding\n\nWhen a critical CVE drops, how quickly can your team confirm which projects are affected? How many tools does an alert cross before a developer can submit a fix?\n\nThe teams that benefit most from AI already have policies, enforcement, and controls embedded in their development workflows. AI amplifies that foundation. It doesn't replace it.\n\n**Enforcement at the point of change.** As exploitation windows compress, every line of code entering a repository needs to pass through a defined set of controls. Not a separate review, in a different tool, by a different team. Organizations need the ability to enforce security policies across every group and project, with the merge request as the enforcement point. Policies defined once, applied everywhere, with exceptions reviewed, approved, and logged.\n\n**Simple issues caught before the merge request, not during.** Hardcoded secrets, known-vulnerable imports, and deprecated API calls can be flagged in the IDE before a developer pushes a commit. Catching them at authoring time means fewer findings blocking the MR, so review cycles go to the findings that require cross-component context: reachability, exploitability, and architectural risk.\n\n**Triage automated by default, not by exception.** Embedding security into every merge request creates a volume problem. More scans, more findings, more noise reaching developers who aren’t trained to distinguish a reachable critical from a theoretical one. AI must handle false positive detection, reachability, exploitability context, and severity assessment before a developer sees the finding, so the findings they see actually warrant their time.\n\n**Remediation governed like any other change.** AI-based remediation compresses the timeline for closing vulnerabilities, but every generated fix must move through the same governance as a human-authored change: policies enforce scans, the right reviewers approve, and evidence is recorded. GitLab’s automated remediation capability proposes each fix in a merge request with a confidence score. The MR records which policy applied, which scans ran, what they found, and who approved. Human code and AI-generated code move through the same process, with the same audit trail.\n\n## What a ready pipeline looks like\n\nHere's how these pieces work together when a high-severity vulnerability is discovered and the clock is running.\n\nA proof-of-concept exploit for a vulnerability in a popular open-source package appears on a security mailing list. There’s no CVE, no National Vulnerability Database (NVD) entry, and no scanner signature yet. The security team finds out the usual way: someone shares it in Slack.\n\nA security engineer asks the security agent if the package is in use, which projects have affected versions, and whether any vulnerable call paths are reachable in production. The agent checks the dependency graph for every project, matches the affected versions and entry points from the disclosure, and returns a ranked list of exposed projects with details about reachability. There’s no need to search through repositories by hand or wait for a scanner update. The question, \"Are we exposed?\" is answered in minutes.\n\nThe engineer starts a remediation campaign for every exposed project. The remediation agent suggests fixes: version updates where a patched release is available, and targeted call-path patches where it is not. Scan execution policies are already in place for projects tagged SOC 2. The engineer hardens the rules to block merges on any merge request that introduces or keeps the affected dependency, and an approval policy now requires security sign-off on every fix. The agent's first proposed patch fails the pipeline when an integration test catches a regression. The agent revises the patch based on the test failure, and the second attempt passes. Developers review the changes, security signs off under the stricter policy, and merges proceed across the campaign.\n\nAt the next audit review, the security team presents a report showing how policies were enforced and risks were reduced during the campaign. It includes scan results, policies applied, approvers, and merge timestamps for every MR in every affected project. The evidence was automatically generated in flight, not assembled after the fact.\n\n## Close the gaps now\n\nMythos exists today, and comparable models will be in attacker hands within a year. Every month between now and then is a chance to strengthen your software supply chain.\n\nAsk these questions about your pipeline:\n\n* How do you enforce that security scans run on every merge request, not just the projects where teams configured them?\n\n* If a compromised package entered your dependency tree today, would your pipeline catch it before build?\n\n* When a scanner flags a critical finding, how many tool boundaries does it cross before a developer starts the fix?\n\n* If an AI agent proposed a code fix for a vulnerability, what process would that fix go through before reaching production, and is that process auditable?\n\n* When auditors ask for evidence that a specific policy was enforced on a specific change, how long does it take to produce?\n\nIf the answers expose gaps, address them now. [Talk to a GitLab solutions architect](https://about.gitlab.com/sales/) about the role of security governance in your development lifecycle.",[725,9,25],"AI/ML","https://res.cloudinary.com/about-gitlab-com/image/upload/v1772195014/ooezwusxjl1f7ijfmbvj.png",{"featured":12,"template":13,"slug":728},"prepare-your-pipeline-for-ai-discovered-zero-days",{"content":730,"config":741},{"title":731,"description":732,"authors":733,"heroImage":735,"date":736,"category":9,"tags":737,"body":740},"Manage vulnerability noise at scale with auto-dismiss policies","Learn how to cut through scanner noise and focus on the vulnerabilities that matter most with GitLab security, including use cases and templates.",[734],"Grant Hickman","https://res.cloudinary.com/about-gitlab-com/image/upload/v1774375772/kpaaaiqhokevxxeoxvu0.png","2026-03-25",[9,23,566,738,739],"features","product","Security scanners are essential, but not every finding requires action. Test code, vendored dependencies, generated files, and known false positives create noise that buries the vulnerabilities that actually matter. Security teams waste hours manually dismissing the same irrelevant findings across projects and pipelines. They experience slower triage, alert fatigue, and developer friction that undermines adoption of security scanning itself.\n\nGitLab's auto-dismiss vulnerability policies let you codify your triage decisions once and apply them automatically on every default-branch pipeline. Define criteria based on file path, directory, or vulnerability identifier (CVE, CWE), choose a dismissal reason, and let GitLab handle the rest.\n\n## Why auto-dismiss?\nAuto-dismiss vulnerability policies enable security teams to:\n- **Eliminate triage noise**: Automatically dismiss findings in test code, vendored dependencies, and generated files.\n- **Enforce decisions at scale**: Apply policies centrally to dismiss known false positives across your entire organization.\n- **Maintain audit transparency**: Every auto-dismissed finding includes a documented reason and links back to the policy that triggered it.\n- **Preserve the record**: Unlike scanner exclusions, dismissed vulnerabilities remain in your report, so you can revisit decisions if conditions change.\n\n## How auto-dismiss policies work\n\n1. **Define your policy** in a vulnerability management policy YAML file. Specify match criteria (file path, directory, or identifier) and a dismissal reason.\n\n2. **Merge and activate.** Create the policy via **Secure > Policies > New  policy > Vulnerability management policy**. Merge the MR to enable it.\n3. **Run your pipeline.** On every default-branch pipeline, matching vulnerabilities are automatically set to \"Dismissed\" with the specified reason. Up to 1,000 vulnerabilities are processed per run.\n4. **Measure the impact.** Filter your vulnerability report by status \"Dismissed\" to see exactly what was cleaned up and validate that the right findings are being handled.\n\n## Use cases with ready-to-use configurations\n\nEach example below includes a policy configuration you can copy, customize, and apply immediately.\n\n### 1. Dismiss test code vulnerabilities\n\nSAST and dependency scanners flag hardcoded credentials, insecure fixtures, and dev-only dependencies in test directories. These are not production risks.\n\n```yaml\nvulnerability_management_policy:\n  - name: \"Dismiss test code vulnerabilities\"\n    description: \"Auto-dismiss findings in test directories\"\n    enabled: true\n    rules:\n      - type: detected\n        criteria:\n          - type: file_path\n            value: \"test/**/*\"\n      - type: detected\n        criteria:\n          - type: file_path\n            value: \"tests/**/*\"\n      - type: detected\n        criteria:\n          - type: file_path\n            value: \"spec/**/*\"\n      - type: detected\n        criteria:\n          - type: directory\n            value: \"__tests__/*\"\n    actions:\n      - type: auto_dismiss\n        dismissal_reason: used_in_tests\n\n```\n\n### 2. Dismiss vendored and third-party code\n\nVulnerabilities in `vendor/`, `third_party/`, or checked-in `node_modules` are managed upstream and not actionable for your team.\n\n```yaml\nvulnerability_management_policy:\n  - name: \"Dismiss vendored dependency findings\"\n    description: \"Findings in vendored code are managed upstream\"\n    enabled: true\n    rules:\n      - type: detected\n        criteria:\n          - type: directory\n            value: \"vendor/*\"\n      - type: detected\n        criteria:\n          - type: directory\n            value: \"third_party/*\"\n      - type: detected\n        criteria:\n          - type: directory\n            value: \"vendored/*\"\n    actions:\n      - type: auto_dismiss\n        dismissal_reason: not_applicable\n\n```\n\n### 3. Dismiss known false positive CVEs\n\nCertain CVEs are repeatedly flagged but don't apply to your usage context. Teams dismiss these manually every time they appear. Replace the example CVEs below with your own.\n\n```yaml\nvulnerability_management_policy:\n  - name: \"Dismiss known false positive CVEs\"\n    description: \"CVEs confirmed as false positives for our environment\"\n    enabled: true\n    rules:\n      - type: detected\n        criteria:\n          - type: identifier\n            value: \"CVE-2023-44487\"\n      - type: detected\n        criteria:\n          - type: identifier\n            value: \"CVE-2024-29041\"\n      - type: detected\n        criteria:\n          - type: identifier\n            value: \"CVE-2023-26136\"\n    actions:\n      - type: auto_dismiss\n        dismissal_reason: false_positive\n\n```\n\n### 4. Dismiss generated and auto-created code\n\nProtobuf, gRPC, OpenAPI generators, and ORM scaffolding tools produce files with flagged patterns that cannot be patched by your team.\n\n```yaml\nvulnerability_management_policy:\n  - name: \"Dismiss generated code findings\"\n    description: \"Generated files are not authored by us\"\n    enabled: true\n    rules:\n      - type: detected\n        criteria:\n          - type: directory\n            value: \"generated/*\"\n      - type: detected\n        criteria:\n          - type: file_path\n            value: \"**/*.pb.go\"\n      - type: detected\n        criteria:\n          - type: file_path\n            value: \"**/*.generated.*\"\n    actions:\n      - type: auto_dismiss\n        dismissal_reason: not_applicable\n\n```\n\n### 5. Dismiss infrastructure-mitigated vulnerabilities\n\nVulnerability classes like XSS (CWE-79) or SQL injection (CWE-89) that are already addressed by WAF rules or runtime protection. Only use this when mitigating controls are verified and consistently enforced.\n\n```yaml\nvulnerability_management_policy:\n  - name: \"Dismiss CWEs mitigated by WAF\"\n    description: \"XSS and SQLi mitigated by WAF rules\"\n    enabled: true\n    rules:\n      - type: detected\n        criteria:\n          - type: identifier\n            value: \"CWE-79\"\n      - type: detected\n        criteria:\n          - type: identifier\n            value: \"CWE-89\"\n    actions:\n      - type: auto_dismiss\n        dismissal_reason: mitigating_control\n\n```\n\n### 6. Dismiss CVE families across your organization\n\nA wave of related CVEs for a widely-used library your team has assessed? Apply at the group level to dismiss them across dozens of projects. The wildcard pattern (e.g., `CVE-2021-44*`) matches all CVEs with that prefix.\n\n```yaml\nvulnerability_management_policy:\n  - name: \"Accept risk for log4j CVE family\"\n    description: \"Log4j CVEs mitigated by version pinning and WAF\"\n    enabled: true\n    rules:\n      - type: detected\n        criteria:\n          - type: identifier\n            value: \"CVE-2021-44*\"\n    actions:\n      - type: auto_dismiss\n        dismissal_reason: acceptable_risk\n\n```\n\n## Quick reference\n\n| Parameter | Details |\n|-----------|---------|\n| **Criteria types** | `file_path` (glob patterns, e.g., `test/**/*`), `directory` (e.g., `vendor/*`), `identifier` (CVE/CWE with wildcards, e.g., `CVE-2023-*`) |\n| **Dismissal reasons** | `acceptable_risk`, `false_positive`, `mitigating_control`, `used_in_tests`, `not_applicable` |\n| **Criteria logic** | Multiple criteria within a rule = AND (must match all). Multiple rules within a policy = OR (match any). |\n| **Limits** | 3 criteria per rule, 5 rules per policy, 5 policies per security policy project. Vulnerabilty management policy actions process 1000 vulnerabilities per pipeline run in the target project, until all matching vulnerabilities are processed. |\n| **Affected statuses** | Needs triage, Confirmed |\n| **Scope** | Project-level or group-level (group-level applies across all projects) |\n\n## Getting started\nHere's how to get started with auto-dismiss policies:\n\n1. **Identify the noise.** Open your vulnerability report and sort by \"Needs triage.\" Look for patterns: test files, vendored code, the same CVE across projects.\n\n2. **Pick a scenario.** Start with whichever use case above accounts for the most findings.\n\n3. **Record your baseline.** Note the number of \"Needs triage\" vulnerabilities before creating a policy.\n\n4. **Create and enable.** Navigate to **Secure > Policies > New policy > Vulnerability management policy**. Paste the configuration from the use case above, then merge the MR.\n\n5. **Validate results.** After the next default-branch pipeline, filter by status \"Dismissed\" to confirm the right findings were handled.\n\nFor full configuration details, see the [vulnerability management policy documentation](https://docs.gitlab.com/user/application_security/policies/vulnerability_management_policy/#auto-dismiss-policies).\n\n> Ready to take control of vulnerability noise? [Start a free GitLab Ultimate trial](https://about.gitlab.com/free-trial/) and configure your first auto-dismiss policy today.\n",{"slug":742,"featured":12,"template":13},"auto-dismiss-vulnerability-management-policy",{"content":744,"config":753},{"title":745,"description":746,"authors":747,"heroImage":749,"date":750,"body":751,"category":9,"tags":752},"GitLab 18.10 brings AI-native triage and remediation ","Learn about GitLab Duo Agent Platform capabilities that cut noise, surface real vulnerabilities, and turn findings into proposed fixes.",[748],"Alisa Ho","https://res.cloudinary.com/about-gitlab-com/image/upload/v1773843921/rm35fx4gylrsu9alf2fx.png","2026-03-19","GitLab 18.10 introduces new AI-powered security capabilities focused on improving the quality and speed of vulnerability management. Together, these features can help reduce the time developers spend investigating false positives and bring automated remediation directly into their workflow, so they can fix vulnerabilities without needing to be security experts.\n\nHere is what’s new:\n\n* [**Static Application Security Testing (SAST) false positive detection**](https://docs.gitlab.com/user/application_security/vulnerabilities/false_positive_detection/) **is now generally available.** This flow uses an LLM for agentic reasoning to determine the likelihood that a vulnerability is a false positive or not, so security and development teams can focus on remediating critical vulnerabilities first.  \n* [**Agentic SAST vulnerability resolution**](https://docs.gitlab.com/user/application_security/vulnerabilities/agentic_vulnerability_resolution/) **is now in beta.** Agentic SAST vulnerability resolution automatically creates a merge request with a proposed fix for verified SAST vulnerabilities, which can shorten time to remediation and reduce the need for deep security expertise.  \n* [**Secret false positive detection**](https://docs.gitlab.com/user/application_security/vulnerabilities/secret_false_positive_detection/) **is now in beta.** This flow brings the same AI-powered noise reduction to secret detection, flagging dummy and test secrets to save review effort.\n\nThese flows are available to GitLab Ultimate customers using GitLab Duo Agent Platform. \n\n## Cut triage time with SAST false positive detection\n\nTraditional SAST scanners flag every suspicious code pattern they find, regardless of whether code paths are reachable or frameworks already handle the risk. Without runtime context, they cannot distinguish a real vulnerability from safe code that just looks dangerous.\n\nThis means developers could spend hours investigating findings that turn out to be false positives. Over time, that can erode confidence in the report and slow down the teams responsible for fixing real risks.\n\nAfter each SAST scan, GitLab Duo Agent Platform automatically analyzes new critical and high severity findings and attaches:\n\n* A confidence score indicating how likely the finding is to be a false positive  \n* An AI-generated explanation describing the reasoning  \n* A visual badge that makes “Likely false positive” versus “Likely real” easy to scan in the UI\n\nThese findings appear in the [Vulnerability Report](https://docs.gitlab.com/user/application_security/vulnerability_report/), as shown below. You can filter the report to focus on findings marked as “Not false positive” so teams can spend their time addressing real vulnerabilities instead of sifting through noise.\n\n![Vulnerability report](https://res.cloudinary.com/about-gitlab-com/image/upload/v1773844787/i0eod01p7gawflllkgsr.png)\n\n\nGitLab Duo Agent Platform's assessment is a recommendation. You stay in control of every false positive to determine if it is valid, and you can audit the agent's reasoning at any time to build confidence in the model. \n\n\n## Turn vulnerabilities into automated fixes\n\nKnowing that a vulnerability is real is only half the work.  Remediation still requires understanding the code path, writing a safe patch, and making sure nothing else breaks.\n\nIf the vulnerability is identified as likely not be a false positive by the SAST false positive detection flow, the Agentic SAST vulnerability resolution flow automatically:\n\n1. Reads the vulnerable code and surrounding context from your repository  \n2. Generates high-quality proposed fixes  \n3. Validates fixes through automated testing   \n4. Opens a merge request with a proposed fix that includes:  \n   * Concrete code changes  \n   * A confidence score  \n   * An explanation of what changed and why\n\nIn this demo, you’ll see how GitLab can automatically take a SAST vulnerability all the way from detection to a ready-to-review merge request. Watch how the agent reads the code, generates and validates a fix, and opens an MR with clear, explainable changes so developers can remediate faster without being security experts.\n\n\u003Ciframe src=\"https://player.vimeo.com/video/1174573325?badge=0&autopause=0&player_id=0&app_id=58479\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" style=\"position:absolute;top:0;left:0;width:100%;height:100%;\" title=\"GitLab 18.10 AI SAST False Positive Auto Remediation\">\u003C/iframe>\u003Cscript src=\"https://player.vimeo.com/api/player.js\">\u003C/script>\n\nAs with any AI-generated suggestion, you should review the proposed merge request carefully before merging.\n\n## Surface real secrets\n\nSecret detection is only useful if teams trust the results. When reports are full of test credentials, placeholder values, and example tokens, developers may waste time reviewing noise instead of fixing real exposures. That can slow remediation and decrease confidence in the scan.\n\nSecret false positive detection helps teams focus on the secrets that matter so they can reduce risk faster. When it runs on the default branch, it will automatically:\n\n1. Analyze each finding to spot likely test credentials, example values, and dummy secrets  \n2. Assign a confidence score for whether the finding is a real risk or a likely false positive  \n3. Generate an explanation for why the secret is being treated as real or noise  \n4. Add a badge in the Vulnerability Report so developers can see the status at a glance\n\nDevelopers can also trigger this analysis manually from the Vulnerability Report by selecting **“Check for false positive”** on any secret detection finding, helping them clear out findings that do not pose risk and focus on real secrets sooner.\n\n## Try AI-powered security today\n\nGitLab 18.10 introduces capabilities that cover the full vulnerability workflow, from cutting false positive noise in SAST and secret detection to automatically generating merge requests with proposed fixes.\n\nTo see how AI-powered security can help cut review time and turn findings into ready-to-merge fixes, [start a free trial of GitLab Duo Agent Platform today](https://about.gitlab.com/gitlab-duo-agent-platform/?utm_medium=blog&utm_source=blog&utm_campaign=eg_global_x_x_security_en_).",[739,9,738],{"featured":31,"template":13,"slug":754},"gitlab-18-10-brings-ai-native-triage-and-remediation",{"promotions":756},[757,771,782,793],{"id":758,"categories":759,"header":761,"text":762,"button":763,"image":768},"ai-modernization",[760],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":764,"config":765},"Get your AI maturity score",{"href":766,"dataGaName":767,"dataGaLocation":244},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":769},{"src":770},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":772,"categories":773,"header":774,"text":762,"button":775,"image":779},"devops-modernization",[739,569],"Are you just managing tools or shipping innovation?",{"text":776,"config":777},"Get your DevOps maturity score",{"href":778,"dataGaName":767,"dataGaLocation":244},"/assessments/devops-modernization-assessment/",{"config":780},{"src":781},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":783,"categories":784,"header":785,"text":762,"button":786,"image":790},"security-modernization",[9],"Are you trading speed for security?",{"text":787,"config":788},"Get your security maturity score",{"href":789,"dataGaName":767,"dataGaLocation":244},"/assessments/security-modernization-assessment/",{"config":791},{"src":792},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"id":794,"paths":795,"header":798,"text":799,"button":800,"image":805},"github-azure-migration",[796,797],"migration-from-azure-devops-to-gitlab","integrating-azure-devops-scm-and-gitlab","Is your team ready for GitHub's Azure move?","GitHub is already rebuilding around Azure. Find out what it means for you.",{"text":801,"config":802},"See how GitLab compares to GitHub",{"href":803,"dataGaName":804,"dataGaLocation":244},"/compare/gitlab-vs-github/github-azure-migration/","github azure migration",{"config":806},{"src":781},{"header":808,"blurb":809,"button":810,"secondaryButton":815},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":811,"config":812},"Get your free trial",{"href":813,"dataGaName":51,"dataGaLocation":814},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":506,"config":816},{"href":55,"dataGaName":56,"dataGaLocation":814},1777302617202]