[{"data":1,"prerenderedAt":1062},["ShallowReactive",2],{"/ja-jp/blog/event-report-gartner-security-risk-management-2025":3,"navigation-ja-jp":286,"banner-ja-jp":714,"footer-ja-jp":722,"blog-post-authors-ja-jp-GitLab Japan Team":962,"blog-related-posts-ja-jp-event-report-gartner-security-risk-management-2025":978,"blog-promotions-ja-jp":1000,"next-steps-ja-jp":1053},{"id":4,"title":5,"authors":6,"body":8,"category":264,"date":265,"description":266,"extension":267,"externalUrl":268,"faq":268,"featured":269,"heroImage":270,"meta":271,"navigation":269,"path":272,"seo":273,"slug":276,"stem":277,"tags":278,"template":284,"updatedDate":268,"__hash__":285},"blogPosts/ja-jp/blog/event-report-gartner-security-risk-management-2025.md","コード生成AIのリスクを管理し、ポテンシャルを最大限に引き出す【イベントレポート】",[7],"GitLab Japan Team",{"type":9,"value":10,"toc":257},"minimark",[11,15,22,28,31,34,40,44,48,51,57,68,71,77,87,90,94,99,103,106,116,122,131,136,140,149,152,155,161,190,193,198,202,205,214,218,223,227,230,233,236,242,246,252],[12,13,14],"p",{},"GitLabは2025年7月23～25日の3日間、都内ホテルで開催された「ガートナー セキュリティ ＆ リスク・マネジメント サミット2025」に出展しました。本記事では、GitLabシニア・ソリューション・アーキテクト 吉瀬 淳一が登壇したセッションの模様についてレポートします。",[12,16,17],{},[18,19],"img",{"alt":20,"src":21},"ガートナー セキュリティ ＆ リスク・マネジメント サミット2025","https://res.cloudinary.com/about-gitlab-com/image/upload/v1757480502/dy6lgmfb1oihyvrjcxqx.jpg",[12,23,24],{},[25,26,27],"em",{},"会場の様子",[12,29,30],{},"この日の講演は、コード生成AIの話が中心です。まずは会社の話から入ったのですが、吉瀬は比較的社歴の浅いエンジニアで、働き方の紹介もユニークでした。GitLabは、全世界の全従業員がリモートで働いていることで知られています。実際に、GitLab社員の多くは、お客様やパートナー様から「よく聞くけれど、本当にそうなの？」と尋ねられた経験をしています。",[12,32,33],{},"吉瀬は、「GitLabには本社がありません。世界中のどこを探しても、オフィスすらありません。私の場合も、入社が決まると会社のPCが送られてきて、GitLabでの生活が始まりました。入社した当日から、いきなり1人ぼっちです」と話して、会場の空気を和ませました。",[12,35,36],{},[18,37],{"alt":38,"src":39},"GitLab合同会社 ソリューションアーキテクト本部 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“組織”ですよ。個人のレベルになるとどうでしょう。組織としては、人が書いていると思っているけれど、実はその人がAIを使っているケースは多いでしょう。なにしろ、生産性が桁違いですから」。",[12,107,108,109,115],{},"一方、GitLabの調査をまとめた『",[110,111,114],"a",{"href":112,"rel":113},"https://about.gitlab.com/resources/developer-survey/",[],"2024グローバルDevSecOpsレポート","』によると、ソフトウェアエンジニアがコードを書く時間は、全就業時間の21%にとどまっています。残りの79%は脆弱性の対応やテスト、トラブルシューティング、打ち合わせなど。ここに、生成AIを導入してる企業の開発生産性が2割程度しか上がらない原因があります。全体の21%を占める部分の生産性が10倍になっても、残りの79%がボトルネックになり、全体的な生産性は上がらないのです。",[12,117,118],{},[18,119],{"alt":120,"src":121},"スライド：AI生成コードの脆弱性とセキュリティリスクの急増","https://res.cloudinary.com/about-gitlab-com/image/upload/v1757386736/syfahxrakeeqlpyurjlv.png",[12,123,124,126,128,130],{},[25,125,120],{},[63,127],{},[63,129],{},"\nさらに、生成AIのはらむセキュリティリスクに注意が必要です。上図に示したように、懸念点は大きく3つ。まず、AIが生成するコードには脆弱性が含まれがちです。次に、エンジニアは脆弱性が含まれていることは認識できるものの、その発見や対処法に自信を持っていません。最後に、マネジメントは、社内でAIがどういう扱われ方をしていて、どんなリスクが発生しているかをつかみきれていません。",[12,132,133],{},[18,134],{"alt":38,"src":135},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1757480496/zs5kufi2hwvlvchjhiws.jpg",[12,137,138],{},[25,139,38],{},[12,141,142,143,148],{},"さらに問題を大きくしているのが、AIのサイロ化です。ソフトウェア開発プロセスでは、さまざまなツールが使用されます。そしていま、各ツールの裏でAIが動くようになりました。これらのAIが、IssueやEpic、マージリクエストの議論、過去の変更履歴といった開発の全体的なコンテキストを把握できないことが問題なのです。プロセスの中には、特定の脆弱性を修正する目的のIssueがあります。しかし、コード生成AIはその背景を知りません。",[110,144,147],{"href":145,"rel":146},"https://about.gitlab.com/ja-jp/topics/ci-cd/",[],"CI/CD","のAIは単にテストの成否だけを見ます。この状況では、「脆弱性を修正する」という本来の修正意図が反映されているかどうかを判断できません。“開発の文脈”を理解しないまま、各ツール上だけで動くAIが部分的な判断を下すことで、本質的な問題が見過ごされてしまうリスクが高まってしまうのです。",[45,150,151],{"id":151},"単一のプラットフォームでソフトウェア開発ライフサイクル全体を管理する",[12,153,154],{},"こうした状況を抜本的に解決するために、 GitLabは単一のプラットフォームでソフトウェア開発ライフサイクル全体を管理するというアプローチを採ります。企画、開発、運用にまたがるセキュリティ対策全体を鳥瞰する包括的な解決策であり、コードの脆弱性、開発者の信頼性、ガバナンスという3つの懸念点もクリアできます。",[12,156,157],{},[18,158],{"alt":159,"src":160},"スライド：セキュアなAI活用を実現するDevSecOpsプラットフォーム","https://res.cloudinary.com/about-gitlab-com/image/upload/v1757386735/rhpuem4bdeja6c2hr7iv.png",[12,162,163,165,167,169,170,175,176,181,182,185,186,189],{},[25,164,159],{},[63,166],{},[63,168],{},"\nGitLabのソリューションにおいて、生成AIを活用した開発プロジェクトのシフトレフトを支える中心になるのが、",[110,171,174],{"href":172,"rel":173},"https://about.gitlab.com/ja-jp/gitlab-duo-agent-platform/",[],"GitLab 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