[{"data":1,"prerenderedAt":823},["ShallowReactive",2],{"/en-us/blog/the-ultimate-guide-to-sboms":3,"navigation-en-us":44,"banner-en-us":454,"footer-en-us":464,"blog-post-authors-en-us-Sandra Gittlen":704,"blog-related-posts-en-us-the-ultimate-guide-to-sboms":720,"blog-promotions-en-us":761,"next-steps-en-us":813},{"id":4,"title":5,"authorSlugs":6,"authors":8,"body":10,"category":11,"categorySlug":11,"config":12,"content":16,"date":20,"description":17,"extension":27,"externalUrl":28,"featured":14,"heroImage":19,"isFeatured":14,"meta":29,"navigation":30,"path":31,"publishedDate":20,"rawbody":32,"seo":33,"slug":13,"stem":37,"tagSlugs":38,"tags":42,"template":15,"updatedDate":26,"__hash__":43},"blogPosts/en-us/blog/the-ultimate-guide-to-sboms.yml","The ultimate guide to SBOMs",[7],"sandra-gittlen",[9],"Sandra Gittlen","In today's rapidly evolving digital landscape, the emphasis on application security within the software supply chain has never been more critical. The integration of upstream dependencies into software requires transparency and security measures that can be complex to implement and manage. This is where a software bill of materials (SBOM) becomes indispensable.\n\nServing as a comprehensive list of ingredients that make up software components, an SBOM illuminates the intricate web of libraries, tools, and processes used across the development lifecycle. Coupled with vulnerability management tools, an SBOM not only reveals potential vulnerabilities in software products but also paves the way for strategic risk mitigation. Our guide dives deep into SBOMs, their pivotal role in a multifaceted [DevSecOps](/topics/devsecops/) strategy, and strategies for improving your application's SBOM health — all aimed at fortifying your organization's cybersecurity posture in a landscape full of emerging threats.\n\nYou'll learn:\n- [What is an SBOM?](#what-is-an-sbom%3F)\n- [Why SBOMs are important](#why-sboms-are-important)\n- [Types of SBOM data exchange standards](#types-of-sbom-data-exchange-standards)\n- [Benefits of pairing SBOMs and software vulnerability management](#benefits-of-pairing-sboms-and-software-vulnerability-management)\n- [GitLab and dynamic SBOMs](#gitlab-and-dynamic-sboms)\n - [Scale SBOM generation and management](#scale-sbom-generation-and-management)\n - [Ingest and merge SBOMs](#ingest-and-merge-sboms)\n - [Accelerate mitigation for better SBOM health](#accelerate-mitigation-for-better-sbom-health)\n - [Continuous SBOM analysis](#continuous-sbom-analysis)\n - [Building trust in SBOMs](#building-trust-in-sboms)\n - [The future of GitLab SBOM functionality](#the-future-of-gitlab-sbom-functionality)\n - [Get started with SBOMs](#get-started-with-sboms)\n - [SBOM FAQ](#sbom-faq)\n\n## What is an SBOM?\n\nAn SBOM is a nested inventory or [list of ingredients that make up software components](https://www.cisa.gov/sbom#). In addition to the components themselves, SBOMs include critical information about the libraries, tools, and processes used to develop, build, and deploy a software artifact.\n\nThe SBOM concept has existed [for more than a decade](https://spdx.dev/about/). However, as part of an effort to implement the National Cyber Strategy that the White House released in 2023, [CISA’s Secure by Design framework](https://www.cisa.gov/securebydesign) is helping guide software manufacturers to adopt secure-by-design principles and integrate cybersecurity into their products. The U.S. government [issued best practices](/blog/comply-with-nist-secure-supply-chain-framework-with-gitlab/) that are driving application developers selling to the public sector to include SBOMs with their software packages. The private sector is not far behind, sending SBOMs on the path to ubiquity. \n\nAlthough SBOMs are often created with stand-alone software, platform companies like GitLab are integrating SBOM generation early and deep in the DevSecOps workflow.\n\n![supply chain security sdlc](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749673653/Blog/Content%20Images/supply_chain_security_sdlc.png)\n\n## Why SBOMs are important\n\nModern software development is laser-focused on delivering applications at a faster pace and in a more efficient manner. This can lead to developers incorporating code from open source repositories or proprietary packages into their applications. According to Synopsys’s 2024 Open Source Security and Risk Analysis report, which consolidated findings from more than 1,000 commercial codebases across 17 industries in 2023, 96% of the total codebases contained open source and 84% of codebases assessed for risk contained vulnerabilities.\n\nPulling in code from unknown repositories increases the potential for vulnerabilities that can be exploited by hackers. In fact, the [2020 SolarWinds attack](https://www.techtarget.com/whatis/feature/SolarWinds-hack-explained-Everything-you-need-to-know) was sparked by the activation of a malicious injection of code in a package used by SolarWinds’ Orion product. Customers across the software supply chain were significantly impacted. Other attacks, including the log4j vulnerability that impacted a number of commercial software vendors, cemented the need for a deep dive into application dependencies, including containers and infrastructure, to be able to assess [risk throughout the software supply chain](https://about.gitlab.com/blog/the-ultimate-guide-to-software-supply-chain-security/).\n\nThere is also a cost component to finding and remediating a software security vulnerability that levels up the need for SBOMs, as well as damage to a company’s reputation that a software supply chain attack can incur. SBOMs give you insight into your dependencies and can be used to look for vulnerabilities, and licenses that don’t comply with internal policies.\n\n## Types of SBOM data exchange standards\n\nSBOMs work best when their generation and interpretation of information such as name, version, packager, and more are able to be automated. This happens best if all parties use a standard data exchange format.\n\nThere are two main types of SBOM data exchange standards in use today:\n- [OWASP CycloneDX](https://cyclonedx.org/capabilities/sbom/)\n- [SPDX](https://spdx.dev/)\n\nGitLab uses CycloneDX for its SBOM generation because the standard is prescriptive and user-friendly, can simplify complex relationships, and is extensible to support specialized and future use cases. In addition, [cyclonedx-cli](https://github.com/CycloneDX/cyclonedx-cli#convert-command) and [cdx2spdx](https://github.com/spdx/cdx2spdx) are open source tools that can be used to convert CycloneDX files to SPDX if necessary.\n\n## Benefits of pairing SBOMs and software vulnerability management\n\nSBOMs are highly beneficial for DevSecOps teams and software consumers for several reasons:\n* They enable a standard approach to understanding what additional software components are in an application and where they are declared.\n* They provide ongoing visibility into the history of an application’s creation, including details about third-party code origins and host repositories.\n* They provide a deep level of security transparency into both first-party developed code and adopted open source software.\n* The details that SBOMs offer enable a DevOps team to identify vulnerabilities, assess the potential risks, and then mitigate them. \n* SBOMs can deliver the transparency that application purchasers now demand.\n\n## GitLab and dynamic SBOMs\n\nFor SBOMs to be fully impactful, organizations must be able to automatically generate them, connect them with application security scanning tools, integrate the vulnerabilities and licenses into a dashboard for easy comprehension and actionability, and update them continuously. GitLab supports all of these goals.\n\n![Dynamic SBOM management](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749673653/Blog/Content%20Images/Screenshot_2024-05-03_at_10.53.28_AM.png)\n\n### Scale SBOM generation and management\nTo comply with internal policies and regulations, it is key to have accurate and comprehensive SBOMs that cover open source, third-party, and proprietary software. To effectively manage SBOMs for each component and product version, a streamlined process is required for creating, merging, validating and approving SBOMs. GitLab’s [Dependency List feature](https://docs.gitlab.com/user/application_security/dependency_list/) aggregates known vulnerability and license data into a single view within the GitLab user interface. Dependency graph information is also generated as part of the dependency scanning report. This empowers users to gain comprehensive insights into dependencies and risk within their projects or across groups of projects. Additionally, a JSON CycloneDX formatted artifact can be produced in the CI pipeline. This API introduces a more nuanced and customizable approach to SBOM generation. SBOMs are exportable from the UI, a specific pipeline or project, or via the GitLab API. \n\n### Ingest and merge SBOMs\nGitLab can ingest third-party SBOMs, providing a deep level of security transparency into both third-party developed code and adopted open source software. With GitLab, you can use a [CI/CD](https://about.gitlab.com/topics/ci-cd/) job to seamlessly merge multiple CycloneDX SBOMs into a single SBOM. Using implementation-specific details in the CycloneDX metadata of each SBOM, such as the location of build and lock files, duplicate information is removed from the resulting merged file. This data is also augmented automatically with license and vulnerability information for the components inside the SBOM.\n\n### Accelerate mitigation for better SBOM health\nBuilding high-quality products faster requires actionable security findings so developers can address the most critical weaknesses. GitLab helps secure your supply chain by [scanning for vulnerabilities](https://docs.gitlab.com/user/application_security/secure_your_application/) in source code, containers, dependencies, and running applications. GitLab offers full security scanner coverage from Static Application Security Testing (SAST), Dynamic Application Security Testing (DAST), container scanning, and software composition analysis (SCA) features to help you achieve full coverage against emerging threat vectors.\nTo help developers and security engineers better understand and remediate vulnerabilities more efficiently, [GitLab Duo](https://about.gitlab.com/gitlab-duo-agent-platform/) Vulnerability Explanation, an AI-powered feature, provides an explanation about a specific vulnerability, how it can be exploited, and, most importantly, a recommendation on how to fix the vulnerability. When combined with GitLab Duo Vulnerability Resolution, DevSecOps teams can intelligently identify, analyze, and fix vulnerabilities in just a matter of clicks.\n\nThe platform also supports creation of new policies (and [compliance enforcement](https://docs.gitlab.com/administration/compliance/)) based on newly detected vulnerabilities. \n\n### Continuous SBOM analysis \nGitLab Continuous Vulnerability Scanning triggers a scan on all projects where either container scanning, dependency scanning, or both, are enabled independent of a pipeline. When new Common Vulnerabilities and Exposures (CVEs) are reported to the National Vulnerability Database (NVD), users don’t need to re-run their pipelines to get the latest feeds. GitLab’s Vulnerability Research Team adds them to GitLab’s Advisory Database and those advisories are automatically reported up to GitLab as vulnerabilities. This makes GitLab’s SBOM truly dynamic in nature. \n\n### Building trust in SBOMs\nOrganizations that require [compliance functionality](https://about.gitlab.com/solutions/compliance/) can use GitLab to [generate attestation for all build artifacts](/blog/securing-the-software-supply-chain-through-automated-attestation/) produced by the GitLab Runner. The process is secure because it is produced by the GitLab Runner itself with no handoff of data to an external service.\n\n## The future of GitLab SBOM functionality\n\nSoftware supply chain security continues to be a critical topic in the cybersecurity and software industry due to frequent attacks on large software vendors and the focused efforts of attackers on the open source software ecosystem. And although the SBOM industry is evolving quickly, there are still concerns around how SBOMs are generated, the frequency of that generation, where they are stored, how to combine multiple SBOMs for complex applications, how to analyze them, and how to leverage them for application health.\n\nGitLab has made SBOMs an integral part of its software supply chain direction and continues to improve upon its SBOM capabilities within the DevSecOps platform, including planning new features and functionality. Recent enhancements to SBOM capabilities include the automation of attestation, digital signing for build artifacts, and support for externally generated SBOMs.\n\nGitLab has also established a robust [SBOM Maturity Model](https://handbook.gitlab.com/handbook/security/security-assurance/dedicated-compliance/sbom-plan/) within the platform that involves steps such as automatic SBOM generation, sourcing SBOMs from the development environment, analyzing SBOMs for artifacts, and advocating for the digital signing of SBOMs. GitLab also plans to add automatic digital signing of build artifacts in future releases. \n\n## Get started with SBOMs\n\nThe demand for SBOMs is already high. Government agencies increasingly recommend or require SBOM creation for software vendors, federal software developers, and even open source communities.\n\n> To get ahead of this requirement, check out the SBOM capabilities for GitLab Ultimate in [GitLab’s DevSecOps platform](https://gitlab.com/-/trials/new).\n\n## SBOM FAQ\n\n**What is an SBOM?**\n\nAn SBOM is a detailed inventory that lists all components, libraries, and tools used in creating, building, and deploying software. This comprehensive list goes beyond mere listings to include vital information about code origins, thus promoting a deeper understanding of an application's makeup and potential vulnerabilities.\n\n**Why are SBOMs important?**\n\nSBOMs are crucial for several reasons. They provide:\n- Insight into dependencies: Understanding what makes up your software helps identify and mitigate risks associated with third-party components.\n- Enhanced security: With detailed visibility into application components, organizations can pinpoint vulnerabilities quickly and take steps to address them.\n- Regulatory compliance: Increasingly, regulations and best practices recommend or require an SBOM for software packages, particularly for those in the public sector.\n- Streamlined development: Developers can lean on an SBOM for insights into used libraries and components, saving time and reducing errors in the development cycle.\n\n**What standards are used for SBOM data exchange?**\n\nThere are two predominant standards:\n- CycloneDX: Known for its user-friendly approach, CycloneDX simplifies complex relationships between software components and supports specialized use cases.\n- SPDX: Another widely used framework for SBOM data exchange, providing detailed information about components within the software environment.\n\nGitLab specifically employs CycloneDX for its SBOM generation because of its prescriptive nature and extensibility to future needs.\n\n**What is GitLab’s approach to SBOMs?**\n\nGitLab emphasizes the creation of dynamic SBOMs that can be:\n- Automatically generated: Ensuring up-to-date information on software composition.\n- Integrated with tools: Connecting to vulnerability scanning tools for thorough risk assessment.\n- Easily managed: Supporting ingestion and merging of SBOMs for comprehensive analysis.\n- Continuously analyzed: Offering ongoing scanning of projects to detect new vulnerabilities as they emerge.\n\n**How can I start implementing SBOMs in my organization?**\n\nFor organizations ready to adopt SBOMs, GitLab’s Ultimate package provides a robust platform for generating and managing SBOMs within a DevSecOps workflow. By leveraging GitLab’s tools, teams can ensure compliance, enhance security, and optimize development practices.\n\nThe increasing demand for SBOMs reflects the growing emphasis on software security and supply chain integrity. By integrating SBOM capabilities, organizations can better protect themselves against vulnerabilities and comply with emerging regulations.\n\n> [Try GitLab Ultimate free today.](https://about.gitlab.com/free-trial/devsecops/)\n\n_Disclaimer This blog contains information related to upcoming products, features, and functionality. It is important to note that the information in this blog post is for informational purposes only. Please do not rely on this information for purchasing or planning purposes. As with all projects, the items mentioned in this blog and linked pages are subject to change or delay. The development, release, and timing of any products, features, or functionality remain at the sole discretion of GitLab._","security",{"slug":13,"featured":14,"template":15},"the-ultimate-guide-to-sboms",false,"BlogPost",{"title":5,"description":17,"authors":18,"heroImage":19,"date":20,"body":10,"category":11,"tags":21,"updatedDate":26},"Learn what a software bill of materials is and why it has become an integral part of modern software development.",[9],"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749664571/Blog/Hero%20Images/blog-image-template-1800x945__8_.png","2022-10-25",[11,22,23,24,25],"DevSecOps","performance","open source","public sector","2024-05-02","yml",null,{},true,"/en-us/blog/the-ultimate-guide-to-sboms","seo:\n title: The ultimate guide to SBOMs\n description: >-\n Learn what a software bill of materials is and why it has become an integral\n part of modern software development.\n ogTitle: The ultimate guide to SBOMs\n ogDescription: >-\n Learn what a software bill of materials is and why it has become an integral\n part of modern software development.\n noIndex: false\n ogImage: >-\n https://res.cloudinary.com/about-gitlab-com/image/upload/v1749664571/Blog/Hero%20Images/blog-image-template-1800x945__8_.png\n ogUrl: https://about.gitlab.com/blog/the-ultimate-guide-to-sboms\n ogSiteName: https://about.gitlab.com\n ogType: article\n canonicalUrls: https://about.gitlab.com/blog/the-ultimate-guide-to-sboms\ncontent:\n title: The ultimate guide to SBOMs\n description: >-\n Learn what a software bill of materials is and why it has become an integral\n part of modern software development.\n authors:\n - Sandra Gittlen\n heroImage: >-\n https://res.cloudinary.com/about-gitlab-com/image/upload/v1749664571/Blog/Hero%20Images/blog-image-template-1800x945__8_.png\n date: '2022-10-25'\n body: >-\n In today's rapidly evolving digital landscape, the emphasis on application\n security within the software supply chain has never been more critical. The\n integration of upstream dependencies into software requires transparency and\n security measures that can be complex to implement and manage. This is where\n a software bill of materials (SBOM) becomes indispensable.\n\n\n Serving as a comprehensive list of ingredients that make up software\n components, an SBOM illuminates the intricate web of libraries, tools, and\n processes used across the development lifecycle. Coupled with vulnerability\n management tools, an SBOM not only reveals potential vulnerabilities in\n software products but also paves the way for strategic risk mitigation. Our\n guide dives deep into SBOMs, their pivotal role in a multifaceted\n [DevSecOps](/topics/devsecops/) strategy, and strategies for improving your\n application's SBOM health — all aimed at fortifying your organization's\n cybersecurity posture in a landscape full of emerging threats.\n\n\n You'll learn:\n\n - [What is an SBOM?](#what-is-an-sbom%3F)\n\n - [Why SBOMs are important](#why-sboms-are-important)\n\n - [Types of SBOM data exchange\n standards](#types-of-sbom-data-exchange-standards)\n\n - [Benefits of pairing SBOMs and software vulnerability\n management](#benefits-of-pairing-sboms-and-software-vulnerability-management)\n\n - [GitLab and dynamic SBOMs](#gitlab-and-dynamic-sboms)\n - [Scale SBOM generation and management](#scale-sbom-generation-and-management)\n - [Ingest and merge SBOMs](#ingest-and-merge-sboms)\n - [Accelerate mitigation for better SBOM health](#accelerate-mitigation-for-better-sbom-health)\n - [Continuous SBOM analysis](#continuous-sbom-analysis)\n - [Building trust in SBOMs](#building-trust-in-sboms)\n - [The future of GitLab SBOM functionality](#the-future-of-gitlab-sbom-functionality)\n - [Get started with SBOMs](#get-started-with-sboms)\n - [SBOM FAQ](#sbom-faq)\n\n ## What is an SBOM?\n\n\n An SBOM is a nested inventory or [list of ingredients that make up software\n components](https://www.cisa.gov/sbom#). In addition to the components\n themselves, SBOMs include critical information about the libraries, tools,\n and processes used to develop, build, and deploy a software artifact.\n\n\n The SBOM concept has existed [for more than a\n decade](https://spdx.dev/about/). However, as part of an effort to implement\n the National Cyber Strategy that the White House released in 2023, [CISA’s\n Secure by Design framework](https://www.cisa.gov/securebydesign) is helping\n guide software manufacturers to adopt secure-by-design principles and\n integrate cybersecurity into their products. The U.S. government [issued\n best\n practices](/blog/comply-with-nist-secure-supply-chain-framework-with-gitlab/)\n that are driving application developers selling to the public sector to\n include SBOMs with their software packages. The private sector is not far\n behind, sending SBOMs on the path to ubiquity. \n\n\n Although SBOMs are often created with stand-alone software, platform\n companies like GitLab are integrating SBOM generation early and deep in the\n DevSecOps workflow.\n\n\n ![supply chain security\n sdlc](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749673653/Blog/Content%20Images/supply_chain_security_sdlc.png)\n\n\n ## Why SBOMs are important\n\n\n Modern software development is laser-focused on delivering applications at a\n faster pace and in a more efficient manner. This can lead to developers\n incorporating code from open source repositories or proprietary packages\n into their applications. According to Synopsys’s 2024 Open Source Security\n and Risk Analysis report, which consolidated findings from more than 1,000\n commercial codebases across 17 industries in 2023, 96% of the total\n codebases contained open source and 84% of codebases assessed for risk\n contained vulnerabilities.\n\n\n Pulling in code from unknown repositories increases the potential for\n vulnerabilities that can be exploited by hackers. In fact, the [2020\n SolarWinds\n attack](https://www.techtarget.com/whatis/feature/SolarWinds-hack-explained-Everything-you-need-to-know)\n was sparked by the activation of a malicious injection of code in a package\n used by SolarWinds’ Orion product. Customers across the software supply\n chain were significantly impacted. Other attacks, including the log4j\n vulnerability that impacted a number of commercial software vendors,\n cemented the need for a deep dive into application dependencies, including\n containers and infrastructure, to be able to assess [risk throughout the\n software supply\n chain](https://about.gitlab.com/blog/the-ultimate-guide-to-software-supply-chain-security/).\n\n\n There is also a cost component to finding and remediating a software\n security vulnerability that levels up the need for SBOMs, as well as damage\n to a company’s reputation that a software supply chain attack can incur.\n SBOMs give you insight into your dependencies and can be used to look for\n vulnerabilities, and licenses that don’t comply with internal policies.\n\n\n ## Types of SBOM data exchange standards\n\n\n SBOMs work best when their generation and interpretation of information such\n as name, version, packager, and more are able to be automated. This happens\n best if all parties use a standard data exchange format.\n\n\n There are two main types of SBOM data exchange standards in use today:\n\n - [OWASP CycloneDX](https://cyclonedx.org/capabilities/sbom/)\n\n - [SPDX](https://spdx.dev/)\n\n\n GitLab uses CycloneDX for its SBOM generation because the standard is\n prescriptive and user-friendly, can simplify complex relationships, and is\n extensible to support specialized and future use cases. In addition,\n [cyclonedx-cli](https://github.com/CycloneDX/cyclonedx-cli#convert-command)\n and [cdx2spdx](https://github.com/spdx/cdx2spdx) are open source tools that\n can be used to convert CycloneDX files to SPDX if necessary.\n\n\n ## Benefits of pairing SBOMs and software vulnerability management\n\n\n SBOMs are highly beneficial for DevSecOps teams and software consumers for\n several reasons:\n\n * They enable a standard approach to understanding what additional software\n components are in an application and where they are declared.\n\n * They provide ongoing visibility into the history of an application’s\n creation, including details about third-party code origins and host\n repositories.\n\n * They provide a deep level of security transparency into both first-party\n developed code and adopted open source software.\n\n * The details that SBOMs offer enable a DevOps team to identify\n vulnerabilities, assess the potential risks, and then mitigate them. \n\n * SBOMs can deliver the transparency that application purchasers now demand.\n\n\n ## GitLab and dynamic SBOMs\n\n\n For SBOMs to be fully impactful, organizations must be able to automatically\n generate them, connect them with application security scanning tools,\n integrate the vulnerabilities and licenses into a dashboard for easy\n comprehension and actionability, and update them continuously. GitLab\n supports all of these goals.\n\n\n ![Dynamic SBOM\n management](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749673653/Blog/Content%20Images/Screenshot_2024-05-03_at_10.53.28_AM.png)\n\n\n ### Scale SBOM generation and management\n\n To comply with internal policies and regulations, it is key to have accurate\n and comprehensive SBOMs that cover open source, third-party, and proprietary\n software. To effectively manage SBOMs for each component and product\n version, a streamlined process is required for creating, merging, validating\n and approving SBOMs. GitLab’s [Dependency List\n feature](https://docs.gitlab.com/user/application_security/dependency_list/)\n aggregates known vulnerability and license data into a single view within\n the GitLab user interface. Dependency graph information is also generated as\n part of the dependency scanning report. This empowers users to gain\n comprehensive insights into dependencies and risk within their projects or\n across groups of projects. Additionally, a JSON CycloneDX formatted artifact\n can be produced in the CI pipeline. This API introduces a more nuanced and\n customizable approach to SBOM generation. SBOMs are exportable from the UI,\n a specific pipeline or project, or via the GitLab API. \n\n\n ### Ingest and merge SBOMs\n\n GitLab can ingest third-party SBOMs, providing a deep level of security\n transparency into both third-party developed code and adopted open source\n software. With GitLab, you can use a\n [CI/CD](https://about.gitlab.com/topics/ci-cd/) job to seamlessly merge\n multiple CycloneDX SBOMs into a single SBOM. Using implementation-specific\n details in the CycloneDX metadata of each SBOM, such as the location of\n build and lock files, duplicate information is removed from the resulting\n merged file. This data is also augmented automatically with license and\n vulnerability information for the components inside the SBOM.\n\n\n ### Accelerate mitigation for better SBOM health\n\n Building high-quality products faster requires actionable security findings\n so developers can address the most critical weaknesses. GitLab helps secure\n your supply chain by [scanning for\n vulnerabilities](https://docs.gitlab.com/user/application_security/secure_your_application/)\n in source code, containers, dependencies, and running applications. GitLab\n offers full security scanner coverage from Static Application Security\n Testing (SAST), Dynamic Application Security Testing (DAST), container\n scanning, and software composition analysis (SCA) features to help you\n achieve full coverage against emerging threat vectors.\n\n To help developers and security engineers better understand and remediate\n vulnerabilities more efficiently, [GitLab\n Duo](https://about.gitlab.com/gitlab-duo-agent-platform/) Vulnerability Explanation, an\n AI-powered feature, provides an explanation about a specific vulnerability,\n how it can be exploited, and, most importantly, a recommendation on how to\n fix the vulnerability. When combined with GitLab Duo Vulnerability\n Resolution, DevSecOps teams can intelligently identify, analyze, and fix\n vulnerabilities in just a matter of clicks.\n\n\n The platform also supports creation of new policies (and [compliance\n enforcement](https://docs.gitlab.com/administration/compliance/))\n based on newly detected vulnerabilities. \n\n\n ### Continuous SBOM analysis \n\n GitLab Continuous Vulnerability Scanning triggers a scan on all projects\n where either container scanning, dependency scanning, or both, are enabled\n independent of a pipeline. When new Common Vulnerabilities and Exposures\n (CVEs) are reported to the National Vulnerability Database (NVD), users\n don’t need to re-run their pipelines to get the latest feeds. GitLab’s\n Vulnerability Research Team adds them to GitLab’s Advisory Database and\n those advisories are automatically reported up to GitLab as vulnerabilities.\n This makes GitLab’s SBOM truly dynamic in nature. \n\n\n ### Building trust in SBOMs\n\n Organizations that require [compliance\n functionality](https://about.gitlab.com/solutions/compliance/) can use\n GitLab to [generate attestation for all build\n artifacts](/blog/securing-the-software-supply-chain-through-automated-attestation/)\n produced by the GitLab Runner. The process is secure because it is produced\n by the GitLab Runner itself with no handoff of data to an external service.\n\n\n ## The future of GitLab SBOM functionality\n\n\n Software supply chain security continues to be a critical topic in the\n cybersecurity and software industry due to frequent attacks on large\n software vendors and the focused efforts of attackers on the open source\n software ecosystem. And although the SBOM industry is evolving quickly,\n there are still concerns around how SBOMs are generated, the frequency of\n that generation, where they are stored, how to combine multiple SBOMs for\n complex applications, how to analyze them, and how to leverage them for\n application health.\n\n\n GitLab has made SBOMs an integral part of its software supply chain direction and continues\n to improve upon its SBOM capabilities within the DevSecOps platform,\n including planning new features and functionality. Recent enhancements to\n SBOM capabilities include the automation of attestation, digital signing for\n build artifacts, and support for externally generated SBOMs.\n\n\n GitLab has also established a robust [SBOM Maturity\n Model](https://handbook.gitlab.com/handbook/security/security-assurance/dedicated-compliance/sbom-plan/)\n within the platform that involves steps such as automatic SBOM generation,\n sourcing SBOMs from the development environment, analyzing SBOMs for\n artifacts, and advocating for the digital signing of SBOMs. GitLab also\n plans to add automatic digital signing of build artifacts in future\n releases. \n\n\n ## Get started with SBOMs\n\n\n The demand for SBOMs is already high. Government agencies increasingly\n recommend or require SBOM creation for software vendors, federal software\n developers, and even open source communities.\n\n\n > To get ahead of this requirement, check out the SBOM capabilities for\n GitLab Ultimate in [GitLab’s DevSecOps\n platform](https://gitlab.com/-/trials/new).\n\n\n ## SBOM FAQ\n\n\n **What is an SBOM?**\n\n\n An SBOM is a detailed inventory that lists all components, libraries, and\n tools used in creating, building, and deploying software. This comprehensive\n list goes beyond mere listings to include vital information about code\n origins, thus promoting a deeper understanding of an application's makeup\n and potential vulnerabilities.\n\n\n **Why are SBOMs important?**\n\n\n SBOMs are crucial for several reasons. They provide:\n\n - Insight into dependencies: Understanding what makes up your software helps\n identify and mitigate risks associated with third-party components.\n\n - Enhanced security: With detailed visibility into application components,\n organizations can pinpoint vulnerabilities quickly and take steps to address\n them.\n\n - Regulatory compliance: Increasingly, regulations and best practices\n recommend or require an SBOM for software packages, particularly for those\n in the public sector.\n\n - Streamlined development: Developers can lean on an SBOM for insights into\n used libraries and components, saving time and reducing errors in the\n development cycle.\n\n\n **What standards are used for SBOM data exchange?**\n\n\n There are two predominant standards:\n\n - CycloneDX: Known for its user-friendly approach, CycloneDX simplifies\n complex relationships between software components and supports specialized\n use cases.\n\n - SPDX: Another widely used framework for SBOM data exchange, providing\n detailed information about components within the software environment.\n\n\n GitLab specifically employs CycloneDX for its SBOM generation because of its\n prescriptive nature and extensibility to future needs.\n\n\n **What is GitLab’s approach to SBOMs?**\n\n\n GitLab emphasizes the creation of dynamic SBOMs that can be:\n\n - Automatically generated: Ensuring up-to-date information on software\n composition.\n\n - Integrated with tools: Connecting to vulnerability scanning tools for\n thorough risk assessment.\n\n - Easily managed: Supporting ingestion and merging of SBOMs for\n comprehensive analysis.\n\n - Continuously analyzed: Offering ongoing scanning of projects to detect new\n vulnerabilities as they emerge.\n\n\n **How can I start implementing SBOMs in my organization?**\n\n\n For organizations ready to adopt SBOMs, GitLab’s Ultimate package provides a\n robust platform for generating and managing SBOMs within a DevSecOps\n workflow. By leveraging GitLab’s tools, teams can ensure compliance, enhance\n security, and optimize development practices.\n\n\n The increasing demand for SBOMs reflects the growing emphasis on software\n security and supply chain integrity. By integrating SBOM capabilities,\n organizations can better protect themselves against vulnerabilities and\n comply with emerging regulations.\n\n\n > [Try GitLab Ultimate free\n today.](https://about.gitlab.com/free-trial/devsecops/)\n\n\n _Disclaimer This blog contains information related to upcoming products,\n features, and functionality. It is important to note that the information in\n this blog post is for informational purposes only. Please do not rely on\n this information for purchasing or planning purposes. As with all projects,\n the items mentioned in this blog and linked pages are subject to change or\n delay. 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Blog",{"headshot":712,"linkedin":713,"ctfId":714},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749659648/Blog/Author%20Headshots/Sgittlen-headshot.jpg","https://www.linkedin.com/in/sandra-gittlen-48557a294/","sgittlen",{},"/en-us/blog/authors/sandra-gittlen",{},"en-us/blog/authors/sandra-gittlen","Y1hpWIa-4iLRjGVQU7Rsuo7D3zGggeSoWHEaLRZQ104",[721,734,749],{"content":722,"config":732},{"title":723,"description":724,"authors":725,"date":727,"body":728,"category":11,"tags":729,"heroImage":731},"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.",[726],"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.",[730,11,539],"AI/ML","https://res.cloudinary.com/about-gitlab-com/image/upload/v1772195014/ooezwusxjl1f7ijfmbvj.png",{"featured":30,"template":15,"slug":733},"prepare-your-pipeline-for-ai-discovered-zero-days",{"content":735,"config":747},{"title":736,"description":737,"authors":738,"heroImage":740,"date":741,"category":11,"tags":742,"body":746},"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.",[739],"Grant Hickman","https://res.cloudinary.com/about-gitlab-com/image/upload/v1774375772/kpaaaiqhokevxxeoxvu0.png","2026-03-25",[11,743,22,744,745],"tutorial","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":748,"featured":30,"template":15},"auto-dismiss-vulnerability-management-policy",{"content":750,"config":759},{"title":751,"description":752,"authors":753,"heroImage":755,"date":756,"body":757,"category":11,"tags":758},"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.",[754],"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_).",[745,11,744],{"featured":14,"template":15,"slug":760},"gitlab-18-10-brings-ai-native-triage-and-remediation",{"promotions":762},[763,777,788,799],{"id":764,"categories":765,"header":767,"text":768,"button":769,"image":774},"ai-modernization",[766],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":770,"config":771},"Get your AI maturity score",{"href":772,"dataGaName":773,"dataGaLocation":247},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":775},{"src":776},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":778,"categories":779,"header":780,"text":768,"button":781,"image":785},"devops-modernization",[745,39],"Are you just managing tools or shipping innovation?",{"text":782,"config":783},"Get your DevOps maturity score",{"href":784,"dataGaName":773,"dataGaLocation":247},"/assessments/devops-modernization-assessment/",{"config":786},{"src":787},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":789,"categories":790,"header":791,"text":768,"button":792,"image":796},"security-modernization",[11],"Are you trading speed for security?",{"text":793,"config":794},"Get your security maturity score",{"href":795,"dataGaName":773,"dataGaLocation":247},"/assessments/security-modernization-assessment/",{"config":797},{"src":798},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"id":800,"paths":801,"header":804,"text":805,"button":806,"image":811},"github-azure-migration",[802,803],"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":807,"config":808},"See how GitLab compares to GitHub",{"href":809,"dataGaName":810,"dataGaLocation":247},"/compare/gitlab-vs-github/github-azure-migration/","github azure migration",{"config":812},{"src":787},{"header":814,"blurb":815,"button":816,"secondaryButton":821},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":817,"config":818},"Get your free trial",{"href":819,"dataGaName":55,"dataGaLocation":820},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":510,"config":822},{"href":59,"dataGaName":60,"dataGaLocation":820},1777493607679]