[{"data":1,"prerenderedAt":812},["ShallowReactive",2],{"/en-us/blog/why-are-developers-vulnerable-to-driveby-attacks":3,"navigation-en-us":34,"banner-en-us":444,"footer-en-us":454,"blog-post-authors-en-us-Chris Moberly":696,"blog-related-posts-en-us-why-are-developers-vulnerable-to-driveby-attacks":710,"blog-promotions-en-us":750,"next-steps-en-us":802},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":23,"isFeatured":12,"meta":24,"navigation":25,"path":26,"publishedDate":20,"seo":27,"stem":31,"tagSlugs":32,"__hash__":33},"blogPosts/en-us/blog/why-are-developers-vulnerable-to-driveby-attacks.yml","Why Are Developers Vulnerable To Driveby Attacks",[7],"chris-moberly",null,"security",{"slug":11,"featured":12,"template":13},"why-are-developers-vulnerable-to-driveby-attacks",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"Why are developers so vulnerable to drive-by attacks?","The complexity of developer working environments make them more likely to be vulnerable to a drive-by attack. We talk about why and walk you through a real-life example from a recent disclosure here at GitLab, and provide tips to reduce the risk and impact of drive-by attacks.",[18],"Chris Moberly","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749682986/Blog/Hero%20Images/pexels-pixabay-434450.jpg","2021-09-07","\nAs someone who spends a lot of time working with computers, I know how easy it is to grow over-confident with regards to security. My systems are patched, my firewall rules are tight, and I’m vigilant when it comes to just about anything that looks out of the ordinary.\n\nNo one’s hacking their way into *my* workstation, that’s for sure.\n\nBut my experience working as a hacker myself has shown me that the opposite is often true. Those of us who are *more* technical are often *much more* vulnerable to an attack due to the complexity of our working environments.\n\nIn this blog, we’re going to dive into the anatomy of something called a “drive-by attack,” where malicious code hidden within a website uses your own browser to attack your computer.\n\nAs an example, I’ll show you how our own [Red Team](https://handbook.gitlab.com/handbook/security/security-operations/red-team/) was able to chain multiple vulnerabilities in the [GitLab Development Kit](https://gitlab.com/gitlab-org/gitlab-development-kit/-/blob/main/README.md) (GDK) to achieve remote code execution (RCE) on developer laptops. And lastly, we’ll discuss steps you can take to reduce the risk of this happening to you.\n\n## How drive-by attacks work\n\nDrive-by attacks come in many forms. Each type of attack starts the same way - you visit a website that contains some malicious code (typically JavaScript). That code will then target a specific type of vulnerability, either in your browser itself or in some other network service that your browser can access. In this blog, we will focus on the latter.\n\nWhat I find particularly fascinating about these attacks is that they completely bypass traditional protections like network firewalls and antivirus software. I think many are under the impression that a network service running on their localhost address cannot be targeted remotely. This is simply not true; in fact, this same technique can be used to target any service on your local network, even those without any outbound internet access at all!\n\nLet’s say you are running a test webserver on your laptop on port 8000. You can simulate this running a simple [netcat](https://en.wikipedia.org/wiki/Netcat) command:\n\n```text\nnc -lkp 8000\n```\n\nNow let’s say you are browsing the internet while that test server is running locally. You visit a site that has been compromised with malicious JavaScript. We’ve set up a site at [https://gitlab-com.gitlab.io/gl-security/security-operations/gl-redteam/simple-request](https://gitlab-com.gitlab.io/gl-security/security-operations/gl-redteam/simple-request) that mimics a basic attack. The site contains the following JavaScript:\n\n```xml\n\u003Cscript>\n\tfetch(\"http://localhost:8000\", {\n    \tmethod: 'post',\n    \tbody: 'you\\'re under attack!',\n\t})\n\u003C/script>\n```\n\nWhen you open the site in your browser, you should see that a POST request has been executed against your simulated server, like the screenshot below.\n\n![file name](https://about.gitlab.com/images/blogimages/drive-by/firefox.png)\nHelp, I’m under attack!\n\nWhen JavaScript attempts to interact with another website, the first thing your browser checks is whether or not the protocol, port, and domain all match between that other site and where the script was originally loaded from. This is called the [same-origin policy](https://developer.mozilla.org/en-US/docs/Web/Security/Same-origin_policy): it's your browser’s first line of defense when it comes to these types of attacks.\n\nIn our example above, none of these items matched. That makes this a cross-origin request. Luckily, modern browsers have some mechanisms to restrict exactly what these types of requests can do.\n\nOne of these is called a “[CORS preflight request](https://developer.mozilla.org/en-US/docs/Glossary/Preflight_request).” When some JavaScript asks your browser to perform complex actions on a cross-origin request, your browser will first send an HTTP OPTIONS request to the target. The target will respond with various HTTP headers that tell the browser what is allowed. The most common of these is the “[Access-Control-Allow-Origin](https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/Access-Control-Allow-Origin)” header.\n\nIf this header is set to `*` or to the website containing the malicious code, then your browser will let the code perform complex HTTP requests and access the responses. This would include shipping results off to a remote server, or performing complex multi-step actions like logging in to a service or gaining access to the session token; basically the code will be interacting with it as if it were a human user.\n\nAnother header you may encounter is [Access-Control-Allow-Credentials](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS#requests_with_credentials). When set to `true`, the origin specified in `Access-Control-Allow-Origin` can perform credentialed requests utilizing the browser’s active sessions. When origin validation is not done properly and the requesting origin is blindly reflected in `Access-Control-Allow-Origin`, drive-by attacks against authenticated services become much more likely to succeed as they do not need to first guess the password and mimic a logon.\n\nFrom my experience, the first example (`Access-Control-Allow-Origin: *`) is enabled quite often in development software and open-source projects. Even production-ready applications may intentionally set this header to `*` when started with certain flags that tell them they are running in development mode.\n\nWhat makes matters worse is that software run in development mode tends to have other relaxed security measures: verbose error logging, default passwords or even debuggers that allow web requests to execute commands on the host operating system. This makes it very easy for malicious JavaScript to turn basic cross-origin requests into full-on drive-by exploits that completely compromise your machine.\n\n**To be very clear, if you are running a web server on your workstation with this header set, you are granting permission to any website you visit to fully interact with your application. If that application has the ability to run commands on your laptop, you could be granting any website you visit permission to run commands on your laptop.**\n\n“*Well, that’s fine*,” you might think. “*I’ll just remove that header and be good to go*”.\n\nUnfortunately, it’s not that simple. The preflight check has a pretty big loophole via something called a “[simple request](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS#simple_requests).” Remote JavaScript is allowed to completely bypass the check if it follows some simple rules, like:\n\n- Must be only GET, HEAD, or POST\n- Must be one of three content types (`application/x-www-form-urlencoded`, `multipart/form-data` or `text/plain`)\n- Must use only a specific set of HTTP headers\n- Cannot read the response from the target service\n\nThis is why we had no issues running the “you’re under attack!” example above. It followed the rules and was a simple request.\n\nSo, to reiterate:\n\n* Any website on the internet can use your browser to attack any service you have access to as long as the attack follows certain rules.\n* Services that implement strong protections against Cross-Site Request Forgery (CSRF) can be more resilient to these attacks.\n* Services that specifically reduce these protections (like with the `Access-Control-Allow-Origin` header) are vulnerable to any attack, whether they follow the rules or not.\n\nHow confident are you that every service you run and test locally has implemented strong CSRF protections and has not removed them while in development mode? And even if they have, how confident are you that they cannot still be exploited via the simple requests described above?\n\n## Example: Drive-by RCE in the GitLab GDK\n\nThe GitLab GDK is a tool that helps GitLab contributors install a fully-functioning GitLab instance for development purposes.\n\nIn September of 2020, our Red Team was researching how our developers could be targeted by sophisticated attackers. We were able to chain multiple vulnerabilities in the GDK to conduct the exact type of attack described in this blog, demonstrating how developer workstations could be remotely compromised.\n\n**These vulnerabilities were quickly patched, the community was asked to upgrade, and this specific risk no longer exists. Read on below about the specific issues and their fixes.**\n\nThe attack targeted two components bundled with the GDK:\n\n* [Better Errors](https://github.com/BetterErrors/better_errors): a Rails error debugging tool\n* [webpack-dev-server](https://github.com/webpack/webpack-dev-server): a development web server that provides static file access\n\nWhen visited, the first thing the malicious website would do was to load the better_errors console in an invisible iframe. The result of this was a simple `GET` request from the browser to `http://localhost:3000/__better_errors`.\nWhen this URL was loaded, the better_errors application would generate a unique error code (this is important later on) and then send an HTTP redirect code back to the browser inside the iframe. The URL that it redirected to would include the unique error code, like this:\n\n```text\nhttp://localhost:3000/__better_errors/[ERROR CODE]/eval\n```\n\nBecause better_errors did not have the dangerous `Access-Control-Allow-Origin: *` header set, the malicious site could not actually view that response. However, the GDK keeps a lot of log files, including a record of every URL that has been accessed. This meant that the unique error code generated by better_errors was now stored in a log file on the workstation’s filesystem.\n\nThe next step targeted the webpack-dev-server. This ran on localhost on port 3808 and was configured with the overly-permissive CORS header `Access-Control-Allow-Origin: *`.  As discussed earlier in the blog, this header tells your browser that any website can interact freely with this service.\n\nwebpack-dev-server was configured to serve the contents of the log directory, so our malicious JavaScript could literally download and parse the current log file to extract the unique error code generated above.\n\nUsing this error code, the script would then create a specially-crafted HTTP POST request to instruct better_errors to evaluate arbitrary Ruby code. And, of course, with Ruby we can encapsulate operating system commands in backticks to execute any command we wanted to on the host. That request looked like this:\n\n```text\nPOST http://localhost:3000/__better_errors/[ERROR CODE]/eval\nContent-Type: text/plain\nAccept: text/html\n\n{\"index\":\"0\",\"source\":\"`touch /tmp/itworked`\"}\n```\n\nIt is worth noting that better_errors actually **did not** have an overly-permissive CORS header. So, technically, we should not have been able to send the above command. Because the content being sent was actually JSON, it would not have qualified as a “simple request” and would have had to pass a CORS preflight check, which would have failed.\n\nHowever, the `Content-type` header was not being validated properly. We were able to bypass the preflight check by incorrectly setting the content type to `text/plain` while still providing a JSON payload in the request body.\n\nWhen the malicious website instructed the browser to send that final request, the command would be executed and the host would be compromised.\n\n![file name](https://about.gitlab.com/images/blogimages/drive-by/driveby.png)\nThe original PoC in action.\n\nTo summarize the issues that made this possible:\n\n* Better Errors:\n     * Improper validation of content type header\n     * Lack of robust cross-site request forgery protection (CSRF tokens)  * webpack-dev-server:\n     * Was configured to serve the entire GitLab directory (via `contentBase: true`)\n     * Overly-permissive CORS header (`Access-Control-Allow-Origin: *`)\n\nWhile GitLab ended up completely removing Better Errors from the GDK, we did reach out to its author who was incredibly responsive and very quickly [implemented robust protection](https://github.com/BetterErrors/better_errors/pull/474) for the issues we disclosed.\n\nThe GDK still uses webpack-dev-server, but it has been configured to [stop serving the installation directory](https://gitlab.com/gitlab-org/gitlab/-/merge_requests/41841) and to [stop sending the overly-permissive CORS header](https://gitlab.com/gitlab-org/gitlab/-/merge_requests/46459).\n\nYou can view the source code for the original PoC exploit at [https://gitlab.com/gitlab-com/gl-security/security-operations/gl-redteam/gdk-driveby-poc-public](https://gitlab.com/gitlab-com/gl-security/security-operations/gl-redteam/gdk-driveby-poc-public).\n\n## How to protect yourself from drive-by attacks\n\n### Secure your code from cross-origin attacks\n\nIf you are a developer looking to strengthen your own application, here are two great resources to get you started:\n\n* [OWASP Cross-Site Request Forgery Prevention Cheat Sheet](https://cheatsheetseries.owasp.org/cheatsheets/Cross-Site_Request_Forgery_Prevention_Cheat_Sheet.html)\n* [Portswigger: What is CORS?](https://portswigger.net/web-security/cors)\n\nDo not make the mistake of thinking that your application does not require protection just because it is never exposed to the internet. Any application that listens for requests on a network port can be attacked, even if it only ever runs on localhost for testing purposes.\n\n### Inspect your own network\n\nAs users of software in general, we need to be aware of the increased attack surface that comes with every piece of software we install.\n\n**How many network services do you have running locally on your workstation right now?** Try one of the following commands, you might be surprised by the results:\n\n```shell\n# Linux systems\nsudo ss -tlpa\n\n# MacOS systems\nsudo lsof -i -P | grep -i \"listen\"\n```\n\nHow about on your home network? Those are also potential targets for a drive-by attack. If your browser can access them, it can be used to attack them. You can get a quick view using [nmap](https://nmap.org/) like this:\n\n```text\n# Assuming your LAN is 192.168.1.0/24. Change as needed.\nnmap -sV 192.168.1.0/24\n```\n\nIf you uncover anything that looks like a web service, try to inspect the default HTTP response headers with a command like this:\n\n```shell\ncurl -vv -H \"Origin: http://attacker.com\" http://[IP ADDRESS]\n```\n\nIf the response headers include something like `Access-Control-Allow-Origin: *` or `Access-Control-Allow-Origin: http://attacker.com`, then you know right away that there is a high chance it is vulnerable to a drive-by attack.\n\nHowever, as demonstrated in our example above, even services with properly configured CORS headers can be targeted by drive-by attacks under the right conditions.\n\n### Reducing potential impact and risk\n\nWhen testing and developing software, we end up executing a lot of code via libraries and dependencies. It’s unlikely that we have the time and resources to personally audit every single line of that code. To make matters worse, we often run local environments with intentionally relaxed security controls because it is just too cumbersome to emulate full production environments on our workstations.\n\nEliminating these risks totally might be unrealistic, but we can at least make an effort to reduce the potential impact should one of these environments be compromised.\n\nIf you were to fall victim to a drive-by attack while running an insecure server on your workstation, you would be in for a very bad day. An attacker with a shell on your system can take over every authenticated web session you have, access all of your local data, and potentially compromise any other remote system you have access to.\n\nThe most obvious way to reduce risk would be to not run potentially risky software directly on your workstation. Some easy ways to do this would be:\n\n* Use temporary virtual machines (in the cloud or with local virtualization software) that are reverted to “known good” snapshots often. Ensure these machines contain no sensitive data.\n* Use container technology (LXD, Docker, etc) for launching temporary test environments. Follow best practices to make container escapes more difficult.\n\nNeither of the above are iron-clad protections. Attackers can still target VMs and containers using your workstation’s browser. Sophisticated attackers may even find their way out of that restricted environment and back onto your workstation. But these methods do add another layer between potentially insecure code and your sensitive data.\n\n### Secure your browser\n\nAdditional layers of security can also be implemented around the browser, by segmenting it or restricting what it can do. Remember, your browser is what a drive-by attack abuses to gain access to local services. Here are some ideas to consider:\n\n* Use the [Tor Browser](https://www.torproject.org/). Besides coming with enhanced security features enabled by default, it literally [cannot access localhost](https://gitlab.torproject.org/legacy/trac/-/issues/10419) or your LAN.\n* In your normal browser, plugins like [uBlock Origin](https://github.com/gorhill/uBlock) can limit the ability of JavaScript to execute (see [blocking modes](https://github.com/gorhill/uBlock/wiki/Blocking-mode)) and block sites from accessing local IP addresses (enable the \"block access to LAN\" [filter-list](https://github.com/gorhill/uBlock/wiki/Dashboard:-Filter-lists)).\n* Some attacks may use a DNS name that resolves to a local IP address, which would bypass the filter list described above. See if your provider supports something called \"DNS rebind protection\" (available in dnsmasq, pihole, and services like NextDNS).\n* You can run a web browser inside a virtual machine with limited access to your workstation and/or your LAN. This can be done manually or via products like [QubesOS](https://www.qubes-os.org/) and/or [Whonix](https://www.whonix.org/). Use this segmented browser when accessing sites that you do not trust completely. Revert the browser VMs back to a known good state often.\n\nSome of the ideas above, such as using the Tor Browser or a virtual machine, may not be particularly convenient for 100% of your tasks. You can use them selectively when accessing sites that you have specific concerns with (like while conducting incident response or security research).\n\n![file name](https://about.gitlab.com/images/blogimages/drive-by/tor-browser.png)\nTor Browser to the rescue!\n\n## Understand and protect your attack surface\n\nIf you are running software on your computer that listens on a local network port, you are running a server. That server can be accessed and attacked by any website you visit. Because software developers frequently test less-secure services on their local machines, they are at an increased risk of compromise by these types of attacks.\n\nUnderstanding this attack surface is important, as it lets you make decisions about what additional layers of security you can use to protect yourself. If you have any tips of your own to share, please do so in the comments below.\n\nThanks for reading!\n\nCover image by [Pixabay](https://www.pexels.com/@pixabay) on [Pexels](https://www.pexels.com/photo/action-asphalt-back-light-cars-434450/)\n",[9],"yml",{},true,"/en-us/blog/why-are-developers-vulnerable-to-driveby-attacks",{"title":15,"description":16,"ogTitle":15,"ogDescription":16,"noIndex":12,"ogImage":19,"ogUrl":28,"ogSiteName":29,"ogType":30,"canonicalUrls":28},"https://about.gitlab.com/blog/why-are-developers-vulnerable-to-driveby-attacks","https://about.gitlab.com","article","en-us/blog/why-are-developers-vulnerable-to-driveby-attacks",[9],"UD1NRx0QyFbRL08OHafJEhVrNpBDK8Is6NzsaL5L93k",{"data":35},{"logo":36,"freeTrial":41,"sales":46,"login":51,"items":56,"search":364,"minimal":395,"duo":414,"switchNav":423,"pricingDeployment":434},{"config":37},{"href":38,"dataGaName":39,"dataGaLocation":40},"/","gitlab logo","header",{"text":42,"config":43},"Get free 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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.",[716],"Grant Hickman","https://res.cloudinary.com/about-gitlab-com/image/upload/v1774375772/kpaaaiqhokevxxeoxvu0.png","2026-03-25",[9,720,561,721,722],"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":725,"featured":25,"template":13},"auto-dismiss-vulnerability-management-policy",{"content":727,"config":736},{"title":728,"description":729,"authors":730,"heroImage":732,"date":733,"body":734,"category":9,"tags":735},"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.",[731],"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_).",[722,9,721],{"featured":12,"template":13,"slug":737},"gitlab-18-10-brings-ai-native-triage-and-remediation",{"content":739,"config":748},{"title":740,"description":741,"authors":742,"tags":744,"heroImage":745,"category":9,"date":746,"body":747},"A complete guide to GitLab Container Scanning","Explore GitLab's various container scanning methods and learn how to secure containers at every lifecycle stage.",[743],"Fernando Diaz",[9,720],"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":749,"featured":25,"template":13},"complete-guide-to-gitlab-container-scanning",{"promotions":751},[752,766,777,788],{"id":753,"categories":754,"header":756,"text":757,"button":758,"image":763},"ai-modernization",[755],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":759,"config":760},"Get your AI maturity score",{"href":761,"dataGaName":762,"dataGaLocation":238},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":764},{"src":765},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":767,"categories":768,"header":769,"text":757,"button":770,"image":774},"devops-modernization",[722,564],"Are you just managing tools or shipping innovation?",{"text":771,"config":772},"Get your DevOps maturity score",{"href":773,"dataGaName":762,"dataGaLocation":238},"/assessments/devops-modernization-assessment/",{"config":775},{"src":776},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":778,"categories":779,"header":780,"text":757,"button":781,"image":785},"security-modernization",[9],"Are you trading speed for security?",{"text":782,"config":783},"Get your security maturity score",{"href":784,"dataGaName":762,"dataGaLocation":238},"/assessments/security-modernization-assessment/",{"config":786},{"src":787},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"id":789,"paths":790,"header":793,"text":794,"button":795,"image":800},"github-azure-migration",[791,792],"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":796,"config":797},"See how GitLab compares to GitHub",{"href":798,"dataGaName":799,"dataGaLocation":238},"/compare/gitlab-vs-github/github-azure-migration/","github azure migration",{"config":801},{"src":776},{"header":803,"blurb":804,"button":805,"secondaryButton":810},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":806,"config":807},"Get your free trial",{"href":808,"dataGaName":45,"dataGaLocation":809},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":500,"config":811},{"href":49,"dataGaName":50,"dataGaLocation":809},1776458701519]