[{"data":1,"prerenderedAt":758},["ShallowReactive",2],{"/en-us/blog/how-gitlab-measures-red-team-impact-the-adoption-rate-metric":3,"navigation-en-us":35,"banner-en-us":463,"footer-en-us":480,"Chris Moberly":724,"next-steps-en-us":737,"footer-source-/en-us/blog/how-gitlab-measures-red-team-impact-the-adoption-rate-metric/":752},{"_path":4,"_dir":5,"_draft":6,"_partial":6,"_locale":7,"seo":8,"content":16,"config":25,"_id":28,"_type":29,"title":30,"_source":31,"_file":32,"_stem":33,"_extension":34},"/en-us/blog/how-gitlab-measures-red-team-impact-the-adoption-rate-metric","blog",false,"",{"title":9,"description":10,"ogTitle":9,"ogDescription":10,"noIndex":6,"ogImage":11,"ogUrl":12,"ogSiteName":13,"ogType":14,"canonicalUrls":12,"schema":15},"How GitLab measures Red Team impact: The adoption rate metric","Follow our journey to develop and implement better metrics, including how we used GitLab to track our results end-to-end. Also find out the lessons learned along the way.","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749663239/Blog/Hero%20Images/AdobeStock_1023776629.jpg","https://about.gitlab.com/blog/how-gitlab-measures-red-team-impact-the-adoption-rate-metric","https://about.gitlab.com","article","\n                        {\n        \"@context\": \"https://schema.org\",\n        \"@type\": \"Article\",\n        \"headline\": \"How GitLab measures Red Team impact: The adoption rate metric\",\n        \"author\": [{\"@type\":\"Person\",\"name\":\"Chris Moberly\"}],\n        \"datePublished\": \"2025-03-05\",\n      }",{"title":9,"description":10,"authors":17,"heroImage":11,"date":19,"body":20,"category":21,"tags":22},[18],"Chris Moberly","2025-03-05","In early 2024, we started a journey to implement better metrics for [our\ninternal Red\nTeam](https://handbook.gitlab.com/handbook/security/security-operations/red-team/).\nOur first iteration focused on what we now call the adoption rate metric,\nwhich measures how often the recommendations our team makes are accepted and\nimplemented.\n\n\nChoosing this metric was very deliberate. While there are many ways to\nmeasure a Red Team's impact, we wanted to start with something fundamental:\nAre we actually driving meaningful security improvements? The adoption rate\ndirectly ties our work to real security outcomes, and we could measure it\nusing tools and processes we already had in place.\n\n\nIn this article, you'll discover how we used GitLab to track these results\nend-to-end, some lessons we learned (including what we would have done\ndifferently), and our plans to tackle the next set of metrics.\n\n\n## How we implemented the adoption rate metric\n\n\nWe use GitLab extensively for our Red Team planning, execution, and\nreporting. Every operation wraps up with a report that's written in markdown\nin a dedicated GitLab project. Each report contains a section called\n\"Recommendations\" with a list of suggestions to make GitLab more secure.\n\n\nThose recommendations are always linked to a dedicated issue, which we open\nin the project closest to the team who can address it. If we're suggesting a\nproduct feature, it goes directly in that tracker. If it's a detection\ncapability, it goes into the detections as code repository. We always assign\na directly responsible individual (DRI) in the group that owns that space,\nand we use [this issue\ntemplate](https://gitlab.com/gitlab-com/gl-security/security-operations/redteam/redteam-public/resources/red-team-issue-templates/-/blob/main/.gitlab/issue_templates/recommendation.md?ref_type=heads)\nto ensure consistency in describing the problem, the risk, and potential\nsolutions.\n\n\n![Red team -\nrecommendation-example](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674984/Blog/Content%20Images/recommendation-example__1_.png)\n\n\nHere's where the tracking logistics come in. We use GitLab labels to\nclassify the recommendation across three categories:\n\n\n- Detections and alerts (`RTRec::Detection`)  \n\n- Security controls (`RTRec::Control`)  \n\n- Processes and procedures (`RTRec::Process`)\n\n\nWe then use another set of labels to follow the lifecycle of that\nrecommendation – from review all the way through adoption:\n\n\n- Under review (`RecOutcome::UnderReview`)  \n\n- Accepted and actively being worked on (`RecOutcome::InProgress`)  \n\n- Accepted but backlogged (`RecOutcome::Backlogged`)  \n\n- Accepted but blocked (`RecOutcome::Blocked`)  \n\n- Fully adopted and closed (`RecOutcome::Adopted`)  \n\n- Partially adopted and closed (`RecOutcome::PartiallyAdopted`)  \n\n- Not adopted and closed (`RecOutcome::NotAdopted`)\n\n\n## How we stay on top of recommendations\n\n\nWe use a new GitLab feature called [\"GitLab Query Language\"\n(GLQL)](https://docs.gitlab.com/ee/user/glql/) to build a dynamic Security\nRecommendations Dashboard inside a GitLab issue.\n\n\nThis issue allows us to quickly identify things like:\n\n\n- open recommendations that haven't been updated recently  \n\n- open recommendations that have been backlogged for an extended period of\ntime  \n\n- closed recommendations that weren't properly labeled with an adoption\noutcome\n\n\nWe've found this process encourages the Red Team to follow up on stale\nrecommendations, reaching out to the owners and seeing how we can help get\nthem adopted.\n\n\nGLQL is very cool, and allows us to turn a short code block like this:\n\n\n```yaml  \n\n---  \n\ndisplay: table  \n\nfields: title, labels(\"RTRec::*\"), labels(\"RecOutcome::*\"), created,\nupdated  \n\n---  \n\ngroup = \"gitlab-com\"  \n\nAND label = \"RTRec::*\"  \n\nAND opened = true  \n\n```\n\n\n... into a dynamic table like this:\n\n\n![Red Team - GLQL\ntable](https://res.cloudinary.com/about-gitlab-com/image/upload/v1749674984/Blog/Content%20Images/glql-table.png)\n\n\nThat table for us is very tactical and we use it to keep things moving.\nBeyond that, we also visualize the adoption rate trends over time. That\nallows us to look at things like quarterly adoption rate percentages, how\nlong different types of recommendations take to adopt and implement, and how\nthese figures vary across departments.\n\n\n## Lessons learned\n\n\n**1. Start with metrics in place; don't wait for your program to mature\nfirst.**\n\n\nEarly in our Red Team's development, we focused more on how we would execute\noperations and less on how we would measure them. The idea of using metrics\nto distill complex operations into simple numbers felt like it might\noversimplify our work. But we've learned that thoughtful metrics don't\nreduce the value of Red Team operations - they help demonstrate our impact\nand guide our program's growth. Starting with clear metrics earlier would\nhave accelerated this growth.\n\n\nImplementing these metrics later meant spending significant time\nreformatting years of historical recommendations to enable consistent\nanalysis. Had we planned for metrics from the start, we could have saved\nourselves a lot of time and effort.\n\n\nWe’re keeping this lesson in mind as we start on our next set of metrics,\nthreat resilience, which we talk about below.\n\n\n**2. Don't operate in a silo.**\n\n\nRed Teams aren't the only groups that provide recommendations in a security\norganization. At GitLab, we have our bug bounty program, our external\npentests, product security, security assurance, and security operations.\n\n\nOn the Red Team, we developed our own recommendations process from scratch.\nIt's been fairly effective, but we have noticed some areas for improvement,\nparticularly around prioritization, project management, and alignment with\nour organization's risk reporting process.\n\n\nWe also noticed that some other teams are really good at these areas such as\nour bug bounty program and the triaging of findings from our external\npentests. Those particular groups are very good at delivering product\nrecommendations, and we've been learning from their approach to improve our\nown delivery methods.\n\n\nSo we've taken our success with visualizing metrics and are integrating\nthese lessons to create a more standard format that can be used across\nteams. This will allow us to leverage things that are working well, like our\nadoption rate metric, and combine them with the more efficiently managed\nprocesses used by other groups to ultimately achieve a higher adoption rate\nand a more secure GitLab.\n\n\n## Next up: Measuring our threat resilience\n\n\nNext up for us is implementing metrics around threat resilience. We want to\nmeasure how well GitLab can prevent, detect, and respond to the threats most\nrelevant to our organization. We're building a dashboard that will help\nvisualize this data, showing our top threat actors and a series of scores\nthat measure how well we defend against their specific techniques.\n\n\nOur goal is to have this dashboard drive decisions around what Red Team\noperations to conduct, what defensive capabilities to improve, and in\ngeneral where we should be investing time and effort across our entire\nsecurity division.\n\n\nWe hope to consolidate our existing tools in this process and are currently\nevaluating solutions. We'll share more info when we've achieved some success\nhere.\n\n\n## Key takeaways and how to get started\n\n\nIf you're looking to measure your Red Team's impact, here's what we've\nlearned:\n\n\n1. Start tracking metrics early, even if they're not perfect.  \n\n2. Focus on actionable metrics first (like adoption rate).  \n\n3. Use your existing tools. We used GitLab and Tableau, but the approach\nworks with any tracking system.  \n\n4. Collaborate across security teams to leverage existing processes when\npossible.\n\n\nWe'd love to hear about your experience with metrics in security so drop a\ncomment below or open an issue in one of our [public\nprojects](https://gitlab.com/gitlab-com/gl-security/security-operations/redteam/redteam-public).\n\n\n## Read more from GitLab's Red Team  \n\n- [Stealth operations: The evolution of GitLab's Red\nTeam](https://about.gitlab.com/blog/stealth-operations-the-evolution-of-gitlabs-red-team/)  \n\n- [How GitLab's Red Team automates C2\ntesting](https://about.gitlab.com/blog/how-gitlabs-red-team-automates-c2-testing/)  \n\n- [How we run Red Team operations\nremotely](https://about.gitlab.com/blog/how-we-run-red-team-operations-remotely/)\n","security",[21,23,24],"DevSecOps","inside 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