[{"data":1,"prerenderedAt":813},["ShallowReactive",2],{"/en-us/blog/gitlab-security-hardening-documentation":3,"navigation-en-us":38,"banner-en-us":448,"footer-en-us":458,"blog-post-authors-en-us-Mark Loveless":697,"blog-related-posts-en-us-gitlab-security-hardening-documentation":711,"blog-promotions-en-us":751,"next-steps-en-us":803},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":25,"isFeatured":12,"meta":26,"navigation":27,"path":28,"publishedDate":20,"seo":29,"stem":33,"tagSlugs":34,"__hash__":37},"blogPosts/en-us/blog/gitlab-security-hardening-documentation.yml","Gitlab Security Hardening Documentation",[7],"mark-loveless",null,"security",{"slug":11,"featured":12,"template":13},"gitlab-security-hardening-documentation",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"The backstory on GitLab's security hardening documentation","GitLab has detailed documentation about how to harden your instance, now as a part of GitLab itself. Here's how it came to be.",[18],"Mark Loveless","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749665667/Blog/Hero%20Images/built-in-security.jpg","2023-08-01","\nRecently, my fellow Security team member [Ayoub Fandi](https://gitlab.com/ayofan) released an excellent blog post entitled “[How to harden your self-managed GitLab instance](https://about.gitlab.com/blog/how-to-harden-your-self-managed-gitlab-instance/),” which featured seven steps for helping to lock down your environment. Ayoub’s blog post was based, in part, on early drafts of research into hardening I had been working on. I had no idea how long it would take me to reach a point where I could finally say this, but those original drafts are now a [part of GitLab documentation](https://docs.gitlab.com/ee/security/hardening.html).\n\n## Hardening your GitLab instance\nThe goal of the hardening documentation is for DevSecOps teams to be able to apply security controls and make sure your data and your GitLab instance are protected.\n\nHere's what I will cover:\n- the origins of the hardening documentation\n- field research, including a few attack scenarios\n- bringing an instance online\n- insight into when to use hardening, specifically how to do a bit of threat modeling and get the basics sorted before diving deep into full hardening\n\n## Origins of the hardening documentation\nThe idea for creating extensive hardening documentation started with a blog post I wrote three years ago called “[GitLab instance: Security best practices](https://about.gitlab.com/blog/gitlab-instance-security-best-practices/).\" This became a rather popular reference for GitLab customers asking about securing their self-managed instance (and even a SaaS deployment).\n\nAs I participated in other security efforts around Gitlab, such as [FedRAMP certification](https://handbook.gitlab.com/handbook/security/security-assurance/security-compliance/fedramp-compliance/), [compliance requirements](https://handbook.gitlab.com/handbook/security/security-assurance/security-compliance/certifications/), and general [security concerns](https://handbook.gitlab.com/handbook/security/), I realized we needed more support materials focused on the \"Sec\" in DevSecOps.\n\nThe hardening project was born from this -  based largely off of an instance I had loaded up in 2020 and was using at home. During all of this time, from 2020 until now, I took notes, performed tests, had hacker friends and work colleagues poke and prod at this home system, and, then took even more notes. No doubt, the information I learned would be a huge benefit to GitLab users so I opted to create recommendations that could be updated frequently and accessible directly from a GitLab instance via the Help menu.\n\n## Field research\nI've been a security professional for well over a couple of decades and have had my own domain online since 1997, using five static IP addresses in my house. This deployment includes web services, a Mastodon instance, and a mail server. These systems have been used by a few close hacker friends during this time as a testbed, a place to converse and exchange ideas, and a great educational environment. A few years ago, I thought it would be fun for this group to have its own private GitLab instance called [Blackhole](https://blackhole.nmrc.org/). We could work on coding projects together, collaborate, and, since I worked at GitLab, I could use it for testing of a standalone instance for certain work-inspired issues.\n\nHaving live servers up with dedicated and static IP addresses means that, yes, these servers are under pretty much constant attack. Because of this clustering of security friends on these systems, we’ve even been targeted by more sophisticated attackers, up to and including nation states. A perfect test environment for real-world attack scenarios.\n\n### Attack scenarios\nLike many in the security field, over the years I’ve seen a number of attacks firsthand, so I made a list of things I needed for hardening against attacks. After doing some [threat modeling](https://handbook.gitlab.com/handbook/security/product-security/application-security/threat-modeling/), I noted the following three areas of concern:\n1. **Opportunistic intruders (okay, who am I kidding, [script kiddies](https://www.techtarget.com/searchsecurity/definition/script-kiddy-or-script-kiddie)).** These types of attacks are typically composed of easy-to-use scripts against known vulnerable applications. This has happened to me. Within five minutes of installation of an odd web-based application, while still reading the documentation and wondering if the apparently vulnerable software was actually working, it was compromised. So I had to assume immediate attacks would happen if I loaded this up on a live system exposed to the open internet.\n2. **Layered or chained attacks.** This is when an attacker takes advantage of a particular sub-component that is exposed to the internet, and while the sub-component might not allow for full system access, it could allow for access to another sub-component with access to data. I was determined to disable or secure as much as possible, leaving as few exposed ports or running services as possible.\n3. **Advanced persistent threat ([APT](https://en.wikipedia.org/wiki/Advanced_persistent_threat)) attackers.** They have repeatedly gone after my former employers, and as they learned who their employees were, home systems would become targets, and [mine were no exception](https://www.markloveless.net/blog/2021/6/8/advancing-persistently-against-apt). To this day, I receive an APT attack attempt every few months. Knowing that one tactic of APT attackers is supply chain attacks, having a DevSecOps platform shared by hackers could be seen as a delicious target, so security had to be top of mind.\n\n## Bringing an instance online\nAs I installed Blackhole, I first configured the firewall at the operating system level to close off all of the ports from public access, only allowing access from my internal network. As a rule, my perimeter router allows all traffic in for those five static IP addresses, with each system following strict firewall rules using the operating system’s firewall capabilities. Most of these five systems cannot even talk to each other, or only have the bare minimum connectivity configured to enable functionality. As I was monitoring traffic to my public systems via my perimeter router, in less than 10 minutes, I started seeing port scans against Blackhole’s IP address, well before it had even finished installation of the Linux operating system. I was glad the firewall was up and running from the start.\n\nAs GitLab was installed and Blackhole came up in its state as a GitLab instance, I started going through the various settings and making sure that things were locked down as tight as possible. Anything I wasn’t using was disabled. This applied to the underlying operating system as well as the GitLab software itself. When I felt good enough about it, I adjusted the firewall settings to open things up ever so slightly, and the system has been under near constant attack since.\n\n## When to use the hardening documentation\nGitLab is a comprehensive DevSecOps platform that can handle all kinds of security scenarios. GitLab the company uses the product to not only develop the platform, but we also run the company off of it. The feature-rich platform can be configured in many different ways. Keeping that in mind, note that one setup might be set up to be more secure than another simply because of the environment it needs to be included in. There are drastically different configuration choices for an environment that is publicly accessible vs. one that is only accessible from employee workstations, or  a large enterprise with employees located on multiple continents vs. a small business' single server deployment.\n\nHardening, therefore, is dependent on your unique environment, and requires you to understand the threats you need to mitigate against, and account for any regulatory and compliance requirements to which you must adhere. However, there are a few common steps that can lead you through the process.\n\n### Start with the basics\nThe first recommendation is to start with a few basics. Make sure you have some ground rules established in your organization such as password standards, software upgrade schedules, and compliance requirements. This will make it easier as you move through the process. Understand the threats your organization has faced in the past, and the potential threats you could face in the future. I wrote a blog post on [threat modeling](https://handbook.gitlab.com/handbook/security/product-security/application-security/threat-modeling/) and [we use it internally](https://handbook.gitlab.com/handbook/security/product-security/application-security/threat-modeling/howto.html) as well.\n\n### Full hardening\nI’d recommend reading [Ayoub’s blog post](https://about.gitlab.com/blog/how-to-harden-your-self-managed-gitlab-instance/) and follow the seven steps he puts forward. In many cases, after you’ve finished Ayoub’s blog post you will have enough to meet your security needs right there. If you need more, delve into the [hardening recommendations documentation](https://docs.gitlab.com/ee/security/hardening.html). Adapt it as needed to meet your organization’s security demands, and explore the possibilities to increase the security of your environment. Note that these recommendations are not limited to just GitLab settings, but also includes a few recommendations for the underlying operating system itself.\n\n### Share your feedback\nIf you have ideas for more security tips and tricks or questions regarding the hardening documentation, please open an issue on GitLab. We’d love to hear from you and welcome feedback and contributions! And if you want to learn more about how we do security at GitLab, review the [security section](https://handbook.gitlab.com/handbook/security/) of the handbook.\n",[9,23,24],"cloud native","DevSecOps","yml",{},true,"/en-us/blog/gitlab-security-hardening-documentation",{"title":15,"description":16,"ogTitle":15,"ogDescription":16,"noIndex":12,"ogImage":19,"ogUrl":30,"ogSiteName":31,"ogType":32,"canonicalUrls":30},"https://about.gitlab.com/blog/gitlab-security-hardening-documentation","https://about.gitlab.com","article","en-us/blog/gitlab-security-hardening-documentation",[9,35,36],"cloud-native","devsecops","QQ01A071SLHGF3biZ2PJ2uytfCE1G6FdgmwKRzpB2Ew",{"data":39},{"logo":40,"freeTrial":45,"sales":50,"login":55,"items":60,"search":368,"minimal":399,"duo":418,"switchNav":427,"pricingDeployment":438},{"config":41},{"href":42,"dataGaName":43,"dataGaLocation":44},"/","gitlab logo","header",{"text":46,"config":47},"Get free 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statement",{"items":687},[688,691,694],{"text":689,"config":690},"Terms",{"href":518,"dataGaName":519,"dataGaLocation":466},{"text":692,"config":693},"Cookies",{"dataGaName":528,"dataGaLocation":466,"id":529,"isOneTrustButton":27},{"text":695,"config":696},"Privacy",{"href":523,"dataGaName":524,"dataGaLocation":466},[698],{"id":699,"title":18,"body":8,"config":700,"content":702,"description":8,"extension":25,"meta":706,"navigation":27,"path":707,"seo":708,"stem":709,"__hash__":710},"blogAuthors/en-us/blog/authors/mark-loveless.yml",{"template":701},"BlogAuthor",{"name":18,"config":703},{"headshot":704,"ctfId":705},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749664093/Blog/Author%20Headshots/mloveless-headshot.png","mloveless",{},"/en-us/blog/authors/mark-loveless",{},"en-us/blog/authors/mark-loveless","gYgzUdwKCnypExwE5MZ2RPPrl97ftdqEfuAoem8PmXM",[712,727,739],{"content":713,"config":725},{"title":714,"description":715,"authors":716,"heroImage":718,"date":719,"category":9,"tags":720,"body":724},"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.",[717],"Grant Hickman","https://res.cloudinary.com/about-gitlab-com/image/upload/v1774375772/kpaaaiqhokevxxeoxvu0.png","2026-03-25",[9,721,24,722,723],"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":726,"featured":27,"template":13},"auto-dismiss-vulnerability-management-policy",{"content":728,"config":737},{"title":729,"description":730,"authors":731,"heroImage":733,"date":734,"body":735,"category":9,"tags":736},"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.",[732],"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_).",[723,9,722],{"featured":12,"template":13,"slug":738},"gitlab-18-10-brings-ai-native-triage-and-remediation",{"content":740,"config":749},{"title":741,"description":742,"authors":743,"tags":745,"heroImage":746,"category":9,"date":747,"body":748},"A complete guide to GitLab Container Scanning","Explore GitLab's various container scanning methods and learn how to secure containers at every lifecycle stage.",[744],"Fernando Diaz",[9,721],"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772721753/frfsm1qfscwrmsyzj1qn.png","2026-03-05","Container vulnerabilities don't wait for your next deployment. They can emerge at any\npoint, including when you build an image or while containers run in production.\nGitLab addresses this reality with multiple container scanning approaches, each designed\nfor different stages of your container lifecycle.\n\nIn this guide, we'll explore the different types of container scanning GitLab offers,\nhow to enable each one, and common configurations to get you started.\n\n## Why container scanning matters\n\nSecurity vulnerabilities in container images create risk throughout your application\nlifecycle. Base images, OS packages, and application dependencies can all harbor\nvulnerabilities that attackers actively exploit. Container scanning detects these risks\nearly, before they reach production, and provides remediation paths when available.\n\nContainer scanning is a critical component of Software Composition Analysis (SCA),\nhelping you understand and secure the external dependencies your containerized\napplications rely on.\n\n## The five types of GitLab Container Scanning\n\nGitLab offers five distinct container scanning approaches, each serving a specific\npurpose in your security strategy.\n\n\n### 1. Pipeline-based Container Scanning\n\n* What it does: Scans container images during your CI/CD pipeline execution,\ncatching vulnerabilities before deployment\n\n* Best for: Shift-left security, blocking vulnerable images from reaching production \n\n* Tier availability: Free, Premium, and Ultimate (with enhanced features in Ultimate)  \n\n* [Documentation](https://docs.gitlab.com/user/application_security/container_scanning/)\n\n\nGitLab uses the Trivy security scanner to analyze container images for\nknown vulnerabilities. When your pipeline runs, the scanner examines your images\nand generates a detailed report.\n\n\n#### How to enable pipeline-based Container Scanning \n\n**Option A: Preconfigured merge request**  \n\n* Navigate to **Secure > Security configuration** in your project.\n* Find the \"Container Scanning\" row.\n* Select **Configure with a merge request**.\n* This automatically creates a merge request with the necessary configuration.  \n\n**Option B: Manual configuration**  \n\n* Add the following to your `.gitlab-ci.yml`:\n\n```yaml\ninclude:\n  - template: Jobs/Container-Scanning.gitlab-ci.yml\n```  \n\n#### Common configurations\n\n**Scan a specific image:**\n\nTo scan a specific image, overwrite the `CS_IMAGE` variable in the `container_scanning` job.\n\n```yaml\ninclude:\n  - template: Jobs/Container-Scanning.gitlab-ci.yml\n\ncontainer_scanning:\n  variables:\n    CS_IMAGE: myregistry.com/myapp:latest\n```\n\n**Filter by severity threshold:**\n\nTo only find vulnerabilities with a certain severity criteria, overwrite the\n`CS_SEVERITY_THRESHOLD` variable in the `container_scanning` job. In the example\nbelow, only vulnerabilities with a severity of **High** or greater will be displayed.\n\n\n```yaml\ninclude:\n  - template: Jobs/Container-Scanning.gitlab-ci.yml\n\ncontainer_scanning:\n  variables:\n    CS_SEVERITY_THRESHOLD: \"HIGH\"\n```\n\n#### Viewing vulnerabilities in a merge request\n\nViewing Container Scanning vulnerabilities directly within merge requests makes security\nreviews seamless and efficient. Once Container Scanning is configured in your CI/CD\npipeline, GitLab automatically display detected vulnerabilities in the merge request's\n[Security widget](https://docs.gitlab.com/user/project/merge_requests/widgets/#application-security-scanning). \n\n\n![Container Scanning vulnerabilities displayed in MR](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772547514/lt6elcq6jexdhqatdy8l.png \"Container Scanning vulnerabilities displayed in MR\")\n\n\n\n* Navigate to any merge request and scroll to the \"Security Scanning\" section to see a summary of\nnewly introduced and existing vulnerabilities found in your container images.\n\n* Click on a **Vulnerability** to access detailed information about the finding, including severity level,\naffected packages, and available remediation guidance.\n\n\n![GitLab Security View details in MR](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772547514/hplihdlekc11uvpfih1p.png)\n\n\n\n![GitLab Security View details in MR](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772547513/jnxbe7uld8wfeezboifs.png \"Container Scanning vulnerability details in MR\")\n\n\nThis visibility enables developers and security teams to catch and address container\nvulnerabilities before they reach production, making security an integral part of your\ncode review process rather than a separate gate.\n\n\n#### Viewing vulnerabilities in Vulnerability Report\n\nBeyond merge request reviews, GitLab provides a centralized\n[Vulnerability Report](https://docs.gitlab.com/user/application_security/vulnerability_report/) that gives security teams comprehensive visibility across all Container Scanning findings in your project.\n\n\n![Vulnerability Report sorted by Container Scanning](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772547524/gagau279fzfgjpnvipm5.png \"Vulnerability Report sorted by Container Scanning\")\n\n\n* Access this report by navigating to **Security & Compliance > Vulnerability Report** in your\nproject sidebar.\n\n* Here you'll find an aggregated view of all container vulnerabilities detected across your branches, with powerful filtering options to sort by severity, status, scanner type, or specific container images.\n\n* You can click on a vulnerabilty to access its Vulnerablity page.\n\n\n![Vulnerability page - 1st view](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772547520/e1woxupyoajhrpzrlylj.png)\n\n\n![Vulnerability page - 2nd view](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772547521/idzcftcgjc8eryixnbjn.png)\n\n\n![Vulnerability page - 3rd view](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772547522/mbbwbbprtf9anqqola10.png \"Vunerability Details for a Container Scanning vulnerability\")\n\n\n[Vulnerability Details](https://docs.gitlab.com/user/application_security/vulnerabilities/)\nshows exactly which container images and layers are impacted, making it easier to trace the\nvulnerability back to its source. You can assign vulnerabilities to team members, change\ntheir status (detected, confirmed, resolved, dismissed), add comments for collaboration,\nand link related issues for tracking remediation work.\n\nThis workflow transforms vulnerability management from a spreadsheet exercise into an integrated part of your development process, ensuring that container security findings are tracked, prioritized, and resolved systematically.\n\n#### View the Dependency List\n\nGitLab's [Dependency List](https://docs.gitlab.com/user/application_security/dependency_list/)\nprovides a comprehensive software bill of materials (SBOM) that catalogs every component within\nyour container images, giving you complete transparency into your software supply chain.\n\n* Navigate to **Security & Compliance > Dependency List** to access an inventory of all packages,\nlibraries, and dependencies detected by Container Scanning across your project.\n\n* This view is invaluable for understanding what's actually running inside your containers, from base OS\npackages to application-level dependencies.\n\n\n![GitLab Dependency List](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772547513/vjg6dk3nhajqamplroji.png \"GitLab Dependency List (SBOM)\")\n\n\nYou can filter the list by package manager, license type, or vulnerability status to quickly\nidentify which components pose security risks or compliance concerns. Each dependency entry\nshows associated vulnerabilities, allowing you to understand security issues in the context\nof your actual software components rather than as isolated findings.\n\n\n### 2. Container Scanning for Registry\n\n* What it does: Automatically scans images pushed to your GitLab Container Registry\nwith the `latest` tag\n\n* Best for: Continuous monitoring of registry images without manual pipeline triggers  \n\n* Tier availability: Ultimate only \n\n* [Documentation](https://docs.gitlab.com/user/application_security/container_scanning/#container-scanning-for-registry) \n\n\nWhen you push a container image tagged `latest`, GitLab's security policy bot\nautomatically triggers a scan against the default branch. Unlike pipeline-based\nscanning, this approach works with Continuous Vulnerability Scanning to monitor\nfor newly published advisories.\n\n#### How to enable Container Scanning for Registry\n\n1. Navigate to **Secure > Security configuration**.\n2. Scroll to the **Container Scanning For Registry** section.\n3. Toggle the feature on.\n\n![Container Scanning for Registry](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772547512/vntrlhtmsh1ecnwni5ji.png \"Toggle for Container Scanning for Registry\")\n\n#### Prerequisites\n\n- Maintainer role or higher in the project\n- Project must not be empty (requires at least one commit on the default branch)\n- Container Registry notifications must be configured\n- Package Metadata Database must be configured (enabled by default on GitLab.com)\n\nVulnerabilities appear under the **Container Registry vulnerabilities** tab in your\nVulnerability Report.\n\n\n### 3. Multi-Container Scanning\n\n* What it does: Scans multiple container images in parallel within a single pipeline \n* Best for: Microservices architectures and projects with multiple container images  \n* Tier availability: Free, Premium, and Ultimate (currently in Beta)  \n* [Documentation](https://docs.gitlab.com/user/application_security/container_scanning/multi_container_scanning/) \n\nMulti-Container Scanning uses dynamic child pipelines to run scans concurrently, significantly reducing overall pipeline execution time when you need to scan multiple images.\n\n#### How to enable Multi-Container scanning\n\n1. Create a `.gitlab-multi-image.yml` file in your repository root:\n\n```yaml\nscanTargets:\n  - name: alpine\n    tag: \"3.19\"\n  - name: python\n    tag: \"3.9-slim\"\n  - name: nginx\n    tag: \"1.25\"\n```\n\n2. Include the template in your `.gitlab-ci.yml`:\n\n```yaml\ninclude:\n  - template: Jobs/Multi-Container-Scanning.latest.gitlab-ci.yml\n```\n\n#### Advanced configuration\n\n**Scan images from private registries:**\n\n```yaml\nauths:\n  registry.gitlab.com:\n    username: ${CI_REGISTRY_USER}\n    password: ${CI_REGISTRY_PASSWORD}\n\nscanTargets:\n  - name: registry.gitlab.com/private/image\n    tag: latest\n```\n\n**Include license information:**\n\n```yaml\nincludeLicenses: true\n\nscanTargets:\n  - name: postgres\n    tag: \"15-alpine\"\n```\n\n\n### 4. Continuous Vulnerability Scanning\n\n* What it does: Automatically creates vulnerabilities when new security advisories are published, no pipeline required \n\n* Best for: Proactive security monitoring between deployments\n\n* Tier availability: Ultimate only\n\n* [Documentation](https://docs.gitlab.com/user/application_security/continuous_vulnerability_scanning/)  \n\nTraditional scanning only catches vulnerabilities at scan time. But what happens\nwhen a new CVE is published tomorrow for a package you scanned yesterday? Continuous\nVulnerability Scanning solves this by monitoring the GitLab Advisory Database and\nautomatically creating vulnerability records when new advisories affect your components.\n\n\n#### How it works\n\n1. Your Container Scanning or Dependency Scanning job generates a CycloneDX SBOM.\n\n2. GitLab registers your project's components from this SBOM.\n\n3. When new advisories are published, GitLab checks if your components are affected.\n\n4. Vulnerabilities are automatically created in your vulnerability report.\n\n\n#### Key considerations\n\n- Scans run via background jobs (Sidekiq), not CI pipelines.\n\n- Only advisories published within the last 14 days are considered for new component detection.\n\n- Vulnerabilities use \"GitLab SBoM Vulnerability Scanner\" as the scanner name.\n\n- To mark vulnerabilities as resolved, you still need to run a pipeline-based scan.\n\n\n### 5. Operational Container Scanning\n\n* What it does: Scans running containers in your Kubernetes cluster on a\nscheduled cadence\n\n* Best for: Post-deployment security monitoring and runtime vulnerability detection  \n\n* Tier availability: Ultimate only\n\n* [Documentation](https://docs.gitlab.com/user/clusters/agent/vulnerabilities/)\n\n\nOperational Container Scanning bridges the gap between build-time security and\nruntime security. Using the GitLab Agent for Kubernetes, it scans containers\nactually running in your clusters—catching vulnerabilities that emerge after\ndeployment.\n\n#### How to enable Operational Container Scanning\n\nIf you are using the [GitLab Kubernetes Agent](https://docs.gitlab.com/user/clusters/agent/install/), you can add the following to your agent configuration file:\n\n```yaml\ncontainer_scanning:\n  cadence: '0 0 * * *'  # Daily at midnight\n  vulnerability_report:\n    namespaces:\n      include:\n        - production\n        - staging\n```\n\n\nYou can also create a [scan execution policy](https://docs.gitlab.com/user/clusters/agent/vulnerabilities/#enable-via-scan-execution-policies) that enforces scanning on a schedule by the GitLab Kubernetes Agent.\n\n\n![Scan execution policy - Operational Container Scanning](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772547515/gsgvjcq4sas4dfc8ciqk.png \"Scan execution policy conditions for Operational Container Scanning\")\n\n#### Viewing results\n\n* Navigate to **Operate > Kubernetes clusters**.\n\n* Select the **Agent** tab, and choose your agent.\n\n* Then select the **Security** tab to view cluster vulnerabilities.\n\n* Results also appear under the **Operational Vulnerabilities** tab in the **Vulnerability Report**.\n\n\n## Enhancing posture with GitLab Security Policies\n\nGitLab Security Policies enable you to enforce consistent security standards across your container workflows through automated, policy-driven controls. These policies shift security left by embedding requirements directly into your development pipeline, ensuring vulnerabilities are caught and addressed before code reaches production.\n\n#### Scan execution and pipeline policies\n\n[Scan execution policies](https://docs.gitlab.com/user/application_security/policies/scan_execution_policies/) automate when and how Container Scanning runs across your projects. Define policies that trigger container scans on every merge request, schedule recurring scans of your main branch, and more. These policies ensure comprehensive coverage without relying on developers to manually configure scanning in each project's CI/CD pipeline.\n\nYou can specify which scanner versions to use and configure scanning parameters centrally, maintaining consistency across your organization while adapting to new container security threats.\n\n![Scan execution policy configuration](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772547517/z36dntxslqem9udrynvx.png \"Scan execution policy configuration\")\n\n\n[Pipeline execution policies](https://docs.gitlab.com/user/application_security/policies/pipeline_execution_policies/) provide flexible controls for injecting (or overriding) custom jobs into a pipeline based on your compliance needs.\n\nUse these policies to automatically inject Container Scanning jobs into your pipeline, fail builds when container vulnerabilities exceed your risk tolerance, trigger additional security checks for specific branches or tags, or enforce compliance requirements for container images destined for production environments. Pipeline execution policies act as automated guardrails, ensuring your security standards are consistently applied across all container deployments without manual intervention.\n\n![Pipeline execution policy](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772547517/ddhhugzcr2swptgodof2.png \"Pipeline execution policy actions\")\n\n#### Merge request approval policies\n\n[Merge request approval policies](https://docs.gitlab.com/user/application_security/policies/merge_request_approval_policies/) enforce security gates by requiring designated approvers to review and sign off on merge requests containing container vulnerabilities.\n\nConfigure policies that block merge when critical or high-severity vulnerabilities are detected, or require security team approval for any merge request introducing new container findings. These policies prevent vulnerable container images from advancing through your pipeline while maintaining development velocity for low-risk changes.\n\n![Merge request approval policy performing block in MR](https://res.cloudinary.com/about-gitlab-com/image/upload/v1772547513/hgnbc1vl4ssqafqcyuzg.png \"Merge request approval policy performing block in MR\")\n\n\n## Choosing the right approach\n\n| Scanning Type | When to Use | Key Benefit |\n|--------------|-------------|-------------|\n| Pipeline-based | Every build | Shift-left security, blocks vulnerable builds |\n| Registry scanning | Continuous monitoring | Catches new CVEs in stored images |\n| Multi-container | Microservices | Parallel scanning, faster pipelines |\n| Continuous vulnerability | Between deployments | Proactive advisory monitoring |\n| Operational | Production monitoring | Runtime vulnerability detection |\n\n\n\nFor comprehensive security, consider combining multiple approaches. Use\npipeline-based scanning to catch issues during development, container\nscanning for registry for continuous monitoring, and operational scanning\nfor production visibility.\n\n## Get started today\n\nThe fastest path to container security is enabling pipeline-based scanning:\n\n1. Navigate to your project's **Secure > Security configuration**.\n2. Click **Configure with a merge request** for Container Scanning.\n3. Merge the resulting merge request.\n4. Your next pipeline will include vulnerability scanning.\n\nFrom there, layer in additional scanning types based on your security requirements\nand GitLab tier.\n\nContainer security isn't a one-time activity, it's an ongoing process.\nWith GitLab's comprehensive container scanning capabilities, you can detect\nvulnerabilities at every stage of your container lifecycle, from build to runtime.\n\n> For more information on how GitLab can help enhance your security posture, visit the [GitLab Security and Governance Solutions Page](https://about.gitlab.com/solutions/application-security-testing/).\n",{"slug":750,"featured":27,"template":13},"complete-guide-to-gitlab-container-scanning",{"promotions":752},[753,767,778,789],{"id":754,"categories":755,"header":757,"text":758,"button":759,"image":764},"ai-modernization",[756],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":760,"config":761},"Get your AI maturity score",{"href":762,"dataGaName":763,"dataGaLocation":242},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":765},{"src":766},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":768,"categories":769,"header":770,"text":758,"button":771,"image":775},"devops-modernization",[723,36],"Are you just managing tools or shipping innovation?",{"text":772,"config":773},"Get your DevOps maturity score",{"href":774,"dataGaName":763,"dataGaLocation":242},"/assessments/devops-modernization-assessment/",{"config":776},{"src":777},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":779,"categories":780,"header":781,"text":758,"button":782,"image":786},"security-modernization",[9],"Are you trading speed for security?",{"text":783,"config":784},"Get your security maturity score",{"href":785,"dataGaName":763,"dataGaLocation":242},"/assessments/security-modernization-assessment/",{"config":787},{"src":788},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"id":790,"paths":791,"header":794,"text":795,"button":796,"image":801},"github-azure-migration",[792,793],"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":797,"config":798},"See how GitLab compares to GitHub",{"href":799,"dataGaName":800,"dataGaLocation":242},"/compare/gitlab-vs-github/github-azure-migration/","github azure migration",{"config":802},{"src":777},{"header":804,"blurb":805,"button":806,"secondaryButton":811},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":807,"config":808},"Get your free trial",{"href":809,"dataGaName":49,"dataGaLocation":810},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":504,"config":812},{"href":53,"dataGaName":54,"dataGaLocation":810},1776447718133]