[{"data":1,"prerenderedAt":1040},["ShallowReactive",2],{"/de-de/the-source/ai/4-ways-ai-can-help-devops-teams-improve-security":3,"footer-de-de":53,"the-source-banner-de-de":360,"the-source-navigation-de-de":372,"the-source-newsletter-de-de":399,"footer-source-/de-de/the-source/ai/4-ways-ai-can-help-devops-teams-improve-security/":410,"article-site-categories-de-de":422,"4-ways-ai-can-help-devops-teams-improve-security-article-hero-category-de-de":424,"4-ways-ai-can-help-devops-teams-improve-security-the-source-source-cta-de-de":446,"4-ways-ai-can-help-devops-teams-improve-security-category-de-de":461,"4-ways-ai-can-help-devops-teams-improve-security-the-source-resources-de-de":473,"4-ways-ai-can-help-devops-teams-improve-security-article-hero-author-de-de":491},{"_path":4,"_dir":5,"_draft":6,"_partial":6,"_locale":7,"config":8,"seo":13,"content":19,"type":44,"category":5,"slug":45,"_id":46,"_type":47,"title":48,"_source":49,"_file":50,"_stem":51,"_extension":52},"/de-de/the-source/ai/4-ways-ai-can-help-devops-teams-improve-security","ai",false,"",{"layout":9,"template":10,"author":11,"featured":6,"sourceCTA":12},"the-source","TheSourceArticle","kristina-weis","source-lp-how-to-get-started-using-ai-in-software-development",{"title":14,"description":15,"ogImage":16,"config":17},"Wie KI DevOps-Teams helfen kann, die Sicherheit zu verbessern","Erfahre, wie DevOps-Teams KI und Machine Learning (ML) nutzen, um die Sicherheit zu verbessern, Risiken zu minimieren und sichereren Code bereitzustellen.","https://res.cloudinary.com/about-gitlab-com/image/upload/v1751463801/t2lucrovy8dadeimvk48.png",{"ignoreTitleCharLimit":18,"ignoreDescriptionCharLimit":18},true,{"title":14,"date":20,"description":21,"timeToRead":22,"heroImage":16,"keyTakeaways":23,"articleBody":27,"faq":28},"2023-12-05","Erfahre, wie DevOps-Teams künstliche Intelligenz und Machine Learning (ML) nutzen, um die Sicherheit zu verbessern, Risiken zu minimieren und sichereren Code bereitzustellen.","Lesezeit: 4 Min.",[24,25,26],"KI und ML in der Softwareentwicklung sind mehr als nur Codegenerierung: Sie können die Sicherheit verbessern, indem sie Sicherheitslücken schneller schließen, Code Reviews effizienter machen und relevante Tests für eine angemessene Abdeckung vorschlagen.","Fast ein Drittel der DevSecOps-Teams nutzt bereits KI für die automatisierte Testgenerierung. Allerdings denken 55 %, dass die Einführung von KI in den Software-Entwicklungsprozess riskant ist.","Unternehmen sollten KI-Tools bevorzugen, die Machine-Learning-Modelle nicht mit firmeneigenen Daten oder Quellcode trainieren und bei deren Entwicklung der Datenschutz im Vordergrund steht.","Bei künstlicher Intelligenz (KI) und Machine Learning (ML) in der Softwareentwicklung geht es nicht nur darum, DevOps-Teams dabei zu helfen, sich wiederholende Aufgaben zu reduzieren und Code effizienter bereitzustellen. KI und ML können Unternehmen dabei unterstützen, besseren und sichereren Code bereitzustellen und Sicherheitsrisiken für ihr Unternehmen und ihre Kund(inn)en zu minimieren.\n\nHier sind einige Möglichkeiten, wie KI die Sicherheit deines Unternehmens verbessern kann:\n\n## Sicherheitslücken schneller beheben\nUm eine Sicherheitslücke zu beheben, musst du sie als Erstes verstehen – und genau hier kommt KI ins Spiel. Bei herkömmlichen Methoden müssen Teams den Code manuell auf Sicherheitslücken überprüfen, was viel Zeit in Anspruch nehmen und zu menschlichen Fehlern führen kann. Mit KI können Entwickler(innen) und Sicherheitsteams jedoch Zusammenfassungen potenzieller Sicherheitslücken und der möglichen Ausnutzung durch Angreifer(innen) erstellen. Fortschrittlichere KI-gestützte Tools können sogar Vorschläge zur Behebung der Sicherheitslücke mit Beispielcode liefern und Teams so umsetzbare Erkenntnisse zur Reduzierung von Sicherheitsrisiken liefern.\n\n## Code Reviews effizienter und effektiver gestalten\nWenn ein(e) Entwickler(in) Code zur Überprüfung bereitstellt, gibt es ein paar Möglichkeiten, wie KI dabei helfen kann, den Prozess zu beschleunigen und potenzielle Probleme zu erkennen.\n\nKI kann bei der Auswahl einer geeigneten Person für die Überprüfung helfen, die mit der Codebase vertraut ist und wichtige Probleme eher erkennt und weniger wahrscheinlich die Anfrage zur Code Review ignoriert, die Überprüfung an jemand anderen weiterleitet oder unzureichendes Feedback gibt. Während die Auswahl der am besten geeigneten Person für einen Menschen eine komplexe Aufgabe sein kann, kann ein Machine-Learning-Algorithmus die Änderungen und das Mitarbeiterdiagramm des Projekts analysieren, um bei der Identifizierung von Prüfer(inne)n zu helfen.\n\nKI kann auch eine Zusammenfassung des Merge Requests erstellen, damit die Person, die den Code überprüfen soll, schnell versteht, was sie überprüfen soll, und um den Übergabeprozess der Code Review zu vereinfachen.\n\n## Tests erstellen, um eine gute Testabdeckung sicherzustellen\nDas gründliche Testen von Codeänderungen ist eine der wichtigsten Methoden, um sicherzustellen, dass der Code wie erwartet funktioniert und keine Sicherheitsprobleme verursacht. Das Schreiben von Tests kann aber viel Zeit in Anspruch nehmen und schwierig sein, sodass Code oft ohne angemessene Testabdeckung in die Produktivumgebung gelangt.\n\nKI kann Codeänderungen überprüfen und relevante Tests zusammen mit Testdateien vorschlagen, sodass Entwickler(innen) weniger Zeit mit dem Überlegen und Schreiben von Tests verbringen und sich [mehr auf die Programmierung konzentrieren können](https://about.gitlab.com/the-source/ai/how-ai-helps-devsecops-teams-improve-productivity/).\n\nTatsächlich nutzen viele DevOps-Teams bereits KI zur Generierung von Tests. In unserer [Umfrage unter mehr als 5 000 DevSecOps-Fachleuten weltweit im Jahr 2024](https://about.gitlab.com/de-de/developer-survey/2024/ai) gab fast ein Drittel (32 %) der Befragten an, dass ihre Unternehmen KI für die automatisierte Testgenerierung verwenden.\n\n## Unternehmenseigene Daten bei Verwendung von KI schützen\nFür viele Unternehmen ist es wichtig, dass die Effizienzsteigerungen durch den Einsatz von KI und ML nicht auf Kosten der Privatsphäre, Sicherheit oder Compliance erzielt werden. Mehr als die Hälfte der Befragten (55 %) gaben an, dass sie die Einführung von KI in den Softwareentwicklungsprozess für riskant halten. Bedenken hinsichtlich Datenschutz und Datensicherheit waren die von den Befragten am häufigsten genannten Hindernisse im Zusammenhang mit KI.\n\nBevor du KI in deine Software-Entwicklungsprozesse einbaust, solltest du genau wissen, wie deine Daten zum Trainieren der KI-Modelle verwendet werden. Wenn DevOps-Teams das falsche KI-Tool verwenden, kann das zu unangenehmen und teuren [Verlusten von streng geheimen Daten und Quellcode führen](https://www.techradar.com/news/samsung-workers-leaked-company-secrets-by-using-chatgpt).\n\n> Finde heraus, was dein DevSecOps-Team tun kann, um die [Auswirkungen generativer KI](https://about.gitlab.com/de-de/the-source/ai/how-to-put-generative-ai-to-work-in-your-devsecops-environment/) zu verstehen und zu messen.\n\n### Sicherheit mit KI-basierten DevSecOps-Workflows verbessern \n\nKI-Lösungen wie [GitLab Duo](https://about.gitlab.com/de-de/gitlab-duo/) können DevOps-Teams dabei helfen, KI zu nutzen, um die Sicherheit während des gesamten Software-Entwicklungsprozess zu verbessern, zum Beispiel durch die [Funktionen](https://docs.gitlab.com/ee/user/ai_features.html) für Zusammenfassungen von Sicherheitslücken, vorgeschlagene Tests, vorgeschlagene Prüfer(innen) und Zusammenfassungen von Merge Requests.\n\nGitLab Duo trainiert ML-Modelle nicht mit den firmeneigenen Daten oder dem Quellcode von Kund(inn)en und wurde mit einem datenschutzorientierten Ansatz entwickelt, um Unternehmen und regulierte Organisationen bei der Einführung KI-basierter Workflows zu unterstützen.",[29,32,35,38,41],{"header":30,"content":31},"Wie kann KI DevOps-Teams helfen, Sicherheitslücken zu erkennen und zu schließen?","KI kann das Aufspüren und Beheben von Sicherheitslücken beschleunigen, indem sie Zusammenfassungen von Sicherheitsrisiken erstellt und umsetzbare Korrekturen vorschlägt. Anstatt den Code manuell auf Sicherheitslücken zu überprüfen, können DevOps-Teams KI-basierte Sicherheitstools einsetzen, um den Code zu analysieren, Schwachstellen zu identifizieren und Vorschläge zur Behebung zu liefern, wodurch die Zeit für die Beseitigung von Sicherheitsbedrohungen verkürzt wird.",{"header":33,"content":34},"Wie verbessert KI die Effizienz von Code Reviews?","KI macht Code Reviews effizienter, indem sie basierend auf deren bisheriger Arbeit und Fachwissen die besten Prüfer(innen) vorschlägt. Außerdem kann sie Zusammenfassungen von Merge Requests erstellen, damit die Prüfer(innen) die Änderungen schnell verstehen und sich auf die wichtigsten Sicherheitsrisiken konzentrieren können. Das verringert Engpässe beim Review-Prozess und sorgt für bessere Sicherheitsbewertungen.",{"header":36,"content":37},"Kann KI bei der Testgenerierung helfen, um die Sicherheit zu verbessern?","Ja, KI kann automatisch Tests generieren, um eine ordnungsgemäße Testabdeckung sicherzustellen und die Wahrscheinlichkeit zu verringern, dass Sicherheitslücken unentdeckt bleiben. Durch die Analyse von Codeänderungen schlagen KI-Tools relevante Unit-, Integrations- und Sicherheitstests vor und helfen DevOps-Teams dabei, Software zu validieren, ohne jeden Testfall manuell schreiben zu müssen.",{"header":39,"content":40},"Welche Sicherheitsrisiken sind mit dem Einsatz von KI in der Softwareentwicklung verbunden?","Zu den größten Risiken beim Einsatz von KI in DevOps gehören Datenschutzbedenken, Compliance-Probleme und mögliche Datenlecks. Unternehmen sollten KI-Tools genau überprüfen, um sicherzugehen, dass diese beim Training von Machine-Learning-Modellen keinen firmeneigenen Quellcode verwenden. KI-Lösungen wie GitLab Duo legen Wert auf Datenschutz und sorgen dafür, dass vertrauliche Daten geschützt bleiben.",{"header":42,"content":43},"Wie können KI-basierte DevSecOps-Workflows die Softwaresicherheit verbessern?","KI-basierte DevSecOps-Workflows integrieren Sicherheit in jede Phase der Entwicklung, indem sie Sicherheitslücken erkennen, Risiken analysieren, automatisierte Tests durchführen und Empfehlungen für sicheren Code geben. Mit einem KI-gestützten Einblick in den Sicherheitsstatus können Teams sicherere Software schneller liefern und gleichzeitig die manuelle Workload und menschliche Fehler reduzieren.","article","4-ways-ai-can-help-devops-teams-improve-security","content:de-de:the-source:ai:4-ways-ai-can-help-devops-teams-improve-security.yml","yaml","4 Ways Ai Can Help Devops Teams Improve Security","content","de-de/the-source/ai/4-ways-ai-can-help-devops-teams-improve-security.yml","de-de/the-source/ai/4-ways-ai-can-help-devops-teams-improve-security","yml",{"_path":54,"_dir":55,"_draft":6,"_partial":6,"_locale":7,"data":56,"_id":356,"_type":47,"title":357,"_source":49,"_file":358,"_stem":359,"_extension":52},"/shared/de-de/main-footer","de-de",{"text":57,"source":58,"edit":64,"contribute":69,"config":74,"items":79,"minimal":348},"Git ist eine Marke von Software Freedom Conservancy und unsere Verwendung von „GitLab“ erfolgt unter Lizenz.",{"text":59,"config":60},"Quelltext der Seite 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Seine Expertise wird regelmäßig sowohl von der Industrie als auch Behörden bei Fragen der Politik für Kommentare und Reaktionen in Anspruch genommen.",{"altText":825,"config":835},{"src":836},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1751463423/mkmdhuxsjggfvokdmdv7.jpg",{"componentName":509},"joel-krooswyk","content:de-de:the-source:authors:joel-krooswyk.yml","de-de/the-source/authors/joel-krooswyk.yml","de-de/the-source/authors/joel-krooswyk",{"_path":843,"_dir":494,"_draft":6,"_partial":6,"_locale":7,"config":844,"seo":845,"content":847,"type":510,"slug":859,"_id":860,"_type":47,"title":846,"_source":49,"_file":861,"_stem":862,"_extension":52},"/de-de/the-source/authors/josh-lemos",{"layout":9},{"title":846},"Josh Lemos",[848,858],{"componentName":500,"componentContent":849},{"config":850,"name":846,"role":853,"bio":854,"headshot":855},{"gitlabHandle":851,"linkedInProfileUrl":852},"joshlemos","https://www.linkedin.com/in/joshlemos/","Chief Information Security Officer","Josh Lemos ist Chief Information Security Officer bei GitLab Inc. und bringt 20 Jahre Erfahrung in der Leitung von Informationssicherheitsteams in seine Rolle ein. 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Bevor er zu GitLab kam, war er bei Indeed, Duo Security und WP Engine tätig.",{"altText":1022,"config":1032},{"src":1033},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1751463427/trfasilaeasosxfcxmsm.jpg",{"componentName":509},"taylor-mccaslin","content:de-de:the-source:authors:taylor-mccaslin.yml","Taylor Mccaslin","de-de/the-source/authors/taylor-mccaslin.yml","de-de/the-source/authors/taylor-mccaslin",1761814390643]