{"id":98199,"date":"2019-04-10T00:00:50","date_gmt":"2019-04-10T07:00:50","guid":{"rendered":"https:\/\/www.paloaltonetworks.com\/blog\/?p=98199"},"modified":"2019-04-08T02:44:49","modified_gmt":"2019-04-08T09:44:49","slug":"introducing-cortex-xdr-tr","status":"publish","type":"post","link":"https:\/\/origin-researchcenter.paloaltonetworks.com\/blog\/2019\/04\/introducing-cortex-xdr-tr\/?lang=tr","title":{"rendered":"Cortex XDR ile tan\u0131\u015f\u0131n"},"content":{"rendered":"<p><u><a href=\"https:\/\/www.paloaltonetworks.com\/company\/press\/2019\/palo-alto-networks-introduces-cortex-the-industrys-only-open-and-integrated-ai-based-continuous-security-platform\">Son teknoloji \u00fcr\u00fcn\u00fc \u00fc\u00e7 yenili\u011fi duyurduk<\/a><\/u>Sekt\u00f6rdeki dengeler tamamen de\u011fi\u015fmek \u00fczere. Bu de\u011fi\u015fimin ad\u0131mlar\u0131ndan biri olan\u00a0<u><a href=\"https:\/\/www.paloaltonetworks.com\/products\/xdr\">Cortex XDR<\/a><\/u>, g\u00fcvenlik ekiplerinin geli\u015fmi\u015f sald\u0131r\u0131lar\u0131 tespit edip durdurmalar\u0131na ek olarak savunma hatlar\u0131n\u0131 s\u00fcrekli geli\u015ftirme ve ileride kar\u015f\u0131la\u015f\u0131labilecek siber sald\u0131r\u0131lar\u0131 \u00f6nlemelerini sa\u011flayan bulut tabanl\u0131 bir uygulamad\u0131r.<\/p>\n<p>Cortex XDR, sekt\u00f6rdeki tek a\u00e7\u0131k ve t\u00fcmle\u015fik yapay zeka tabanl\u0131 s\u00fcrekli g\u00fcvenlik platformu olan\u00a0<u><a href=\"https:\/\/www.paloaltonetworks.com\/products\/cortex\">Cortex<\/a><\/u> \u00fczerinde kullan\u0131ma sunulan ilk uygulamad\u0131r. Cortex XDR, siber g\u00fcvenlik ekiplerini ay\u0131ran ve olaylara yan\u0131t verme s\u00fcresini uzatan veri silolar\u0131n\u0131 ortadan kald\u0131r\u0131r. Geli\u015fmi\u015f a\u011f, u\u00e7 nokta ve bulut verileri aras\u0131nda yerel olarak ba\u011flant\u0131 kuran Cortex XDR, makine \u00f6\u011frenmesi ve analiz s\u00fcre\u00e7leriyle g\u00fcvenlik operasyonlar\u0131n\u0131n t\u00fcm a\u015famalar\u0131nda iyile\u015ftirme sa\u011flar.<\/p>\n<p>Neden kolay olan\u0131 se\u00e7ip tek bir amaca odaklanan yeni bir \u00fcr\u00fcn geli\u015ftirmedik?\u00a0 G\u00fcn\u00fcm\u00fczde kurulu\u015flar siber g\u00fcvenlik becerileri konusunda \u00f6nemli eksikliklere sahiptir. 2018 (ISC)\u00b2 Siber G\u00fcvenlik \u0130\u015f G\u00fcc\u00fc \u00c7al\u0131\u015fmas\u0131\u00a0<u><a href=\"https:\/\/www.isc2.org\/Research\/Workforce-Study\" rel=\"nofollow,noopener\" >bug\u00fcn yakla\u015f\u0131k 3 milyon pozisyonun a\u00e7\u0131kta oldu\u011funu g\u00f6steriyor<\/a><\/u>. A\u011f analizi, bilgisayar adli analizi ve bulut y\u00f6netimi alan\u0131ndaki uzman say\u0131s\u0131 olduk\u00e7a d\u00fc\u015f\u00fckt\u00fcr. G\u00fcvenlik ekiplerinin \u00fcretkenli\u011fi art\u0131rmaya ek olarak tehdit belirleme, ara\u015ft\u0131rma ve azaltma alan\u0131ndaki karma\u015f\u0131kl\u0131\u011f\u0131 \u00f6nlemeleri gerekir.<\/p>\n<p>Cortex XDR, g\u00fcvenlik ekiplerine destek olarak ve g\u00fcvenlik operasyonlar\u0131n\u0131n her a\u015famas\u0131n\u0131 iyile\u015ftirerek tehdit alg\u0131lama ve yan\u0131t verme s\u00fcre\u00e7lerini yeniden tan\u0131ml\u0131yor. Farkl\u0131 kaynaklardan al\u0131nan veriler bir araya getirildikten sonra aralar\u0131nda ili\u015fki kuruluyor ve analiz ger\u00e7ekle\u015ftirilir. Profil davran\u0131\u015f\u0131na uygulanan makine \u00f6\u011frenmesi s\u00fcre\u00e7leri, normalde tespit edilemeyecek sald\u0131r\u0131lar\u0131 alg\u0131lar. Otomasyon, olas\u0131 tehditlerin temel nedenini ve ayr\u0131nt\u0131l\u0131 g\u00f6r\u00fcnt\u00fcs\u00fcn\u00fc sa\u011flar. Tehdit tespit sisteminin temelinde geli\u015fmi\u015f bir sorgu altyap\u0131s\u0131 bulunur ve \u00f6zel kurallar sayesinde elde edilen bilgiler gelecekteki ara\u015ft\u0131rmalar\u0131 kolayla\u015ft\u0131rmak veya ileride benzer tehditlerin alg\u0131lanmas\u0131 amac\u0131yla kullan\u0131labilir.<\/p>\n<p>Cortex XDR taraf\u0131ndan sunulan benzersiz \u00f6zellikler \u015funlard\u0131r:<\/p>\n<ul>\n<li><strong>Otomatik Alg\u0131lama:<\/strong>\u00a0 Ayr\u0131nt\u0131l\u0131 veriler makine \u00f6\u011frenmesi ile analiz edilerek k\u00f6t\u00fc ama\u00e7l\u0131 yaz\u0131l\u0131mlar, hedefli sald\u0131r\u0131lar ve i\u00e7eriden gelen tehditler tespit edebilir. Davran\u0131\u015f analizi, tehditleri y\u00fcksek do\u011fruluk derecesiyle otomatik olarak alg\u0131larken \u00f6zelle\u015ftirilebilir alg\u0131lama kurallar\u0131 ise g\u00fcvenlik ekiplerinin insan m\u00fcdahalesi gerektiren sald\u0131rgan taktik ve tekniklerine kar\u015f\u0131 savunma geli\u015ftirmesini sa\u011flar.<\/li>\n<li><strong>Daha H\u0131zl\u0131 \u0130lerleyen Ara\u015ft\u0131rma S\u00fcre\u00e7leri:<\/strong>\u00a0G\u00fcvenlik analistleri tek bir t\u0131klamayla g\u00fcvenlik uyar\u0131s\u0131n\u0131n temel nedenini anlayabilir ve olaylar\u0131n zaman \u00e7izelgesine g\u00f6z atabilir. A\u011fa, u\u00e7 noktaya ve bulut etkinli\u011fine uygulanan ba\u011flam bilgileri sayesinde karma\u015f\u0131k analiz s\u00fcre\u00e7leri basitle\u015ftirilerek gereksiz uyar\u0131lar ortadan kald\u0131r\u0131r ve ara\u015ft\u0131rma s\u00fcre\u00e7leri h\u0131zland\u0131r\u0131r.<\/li>\n<li><strong>Uyarlanabilir Yan\u0131t:<\/strong>\u00a0Cortex XDR, uygulama noktalar\u0131yla s\u0131k\u0131 bir \u015fekilde t\u00fcmle\u015ftirildi\u011finden yan\u0131t an\u0131nda koordine edilebiliyor. Ara\u015ft\u0131rmalardan elde edilen bilgiler ileriye d\u00f6n\u00fck olarak uygulanabilir, \u00f6zelle\u015ftirilebilir alg\u0131lama kurallar\u0131 ileride kar\u015f\u0131la\u015f\u0131lacak tehditlere kar\u015f\u0131 koruma sa\u011flama veya ara\u015ft\u0131rmalar i\u00e7in ba\u011flam ekleme amac\u0131yla g\u00fcncelle\u015ftirilebilir.<\/li>\n<li><strong>Kolay ve Bulut Tabanl\u0131 Da\u011f\u0131t\u0131m:<\/strong>\u00a0Bulut tabanl\u0131 bir uygulama olan Cortex XDR, \u015firket i\u00e7i alg\u0131lama ve yan\u0131t verme sistemlerinin y\u00f6netilmesi ve \u00f6l\u00e7eklendirilmesi s\u0131ras\u0131nda kar\u015f\u0131la\u015f\u0131lan sorunlar\u0131n a\u015f\u0131lmas\u0131n\u0131 sa\u011flar. Cortex XDR, Cortex Data Lake i\u00e7inde depolanan a\u011f, u\u00e7 nokta ve bulut verilerini analiz ederek davran\u0131\u015f analiz i\u00e7in gereken y\u00fcksek miktarda verinin depolanmas\u0131 amac\u0131yla operasyonel a\u00e7\u0131dan verimli bir yol sa\u011flaman\u0131n yan\u0131 s\u0131ra var olan g\u00fcvenlik yat\u0131r\u0131mlar\u0131n\u0131z\u0131 alg\u0131lay\u0131c\u0131 ve uygulama noktas\u0131 olarak kullanman\u0131za imkan tan\u0131r.<\/li>\n<li><strong>B\u00fcy\u00fcme i\u00e7in Gerekli Altyap\u0131:<\/strong>\u00a0A\u011f, u\u00e7 nokta ve bulut verilerinde alg\u0131lama ve yan\u0131t verme s\u00fcre\u00e7lerini tek bir \u00fcr\u00fcnde sunan Cortex XDR, tek bir veri kayna\u011f\u0131 \u00fczerinde de \u00e7al\u0131\u015fabilir. M\u00fc\u015fteriler, Traps arac\u0131lar\u0131ndan gelen u\u00e7 nokta verileriyle ba\u015flad\u0131ktan sonra di\u011fer EDR ara\u00e7lar\u0131ndan faydalanabilir veya a\u011f verileriyle ba\u015flay\u0131p daha sonra di\u011fer NTA ara\u00e7lar\u0131n\u0131 ekleyebilir. Dilerseniz gereksinimler artt\u0131k\u00e7a \u00e7\u00f6z\u00fcm\u00fc geli\u015ftirebilir ve di\u011fer veri kaynaklar\u0131yla t\u00fcmle\u015ftirebilirsiniz.<\/li>\n<li><strong>Traps 6.0:\u00a0<\/strong>En geli\u015fmi\u015f k\u00f6t\u00fc ama\u00e7l\u0131 yaz\u0131l\u0131m ve g\u00fcvenlik a\u00e7\u0131\u011f\u0131 istismar\u0131 \u00f6nleme sistemi olan bu uygulama art\u0131k u\u00e7 noktalar\u0131 t\u00fcm tehditlere kar\u015f\u0131 korur ve davran\u0131\u015f analizi temelli tehdit koruma \u00f6zelli\u011fi sunar. Traps, bir seferde tek bir i\u015flemi analiz eden ve bilinen tehdit bilgilerine g\u00f6re hareket eden geleneksel vir\u00fcs \u00f6nleyicilerden farkl\u0131 olarak i\u015flemlerdeki k\u00f6t\u00fc ama\u00e7l\u0131 yaz\u0131l\u0131m s\u0131ralar\u0131n\u0131 izleyip alg\u0131lanan sald\u0131r\u0131lar\u0131 sonland\u0131rarak sald\u0131r\u0131 etkinli\u011fini alg\u0131lay\u0131p durdurabilir. Linux kapsay\u0131c\u0131lar\u0131 i\u00e7in geli\u015fmi\u015f koruma, Linux ELF k\u00f6t\u00fc ama\u00e7l\u0131 yaz\u0131l\u0131m korumas\u0131 ve Cortex XDR i\u00e7in geli\u015fmi\u015f veri toplama gibi yeni i\u015flevler de eklenmi\u015ftir. Cortex XDR, u\u00e7 nokta tehditlerini engellemenin yan\u0131 s\u0131ra alg\u0131lama ve yan\u0131t i\u00e7in veri toplama \u00f6zelliklerine sahip tek ve hafif bir arac\u0131 olan Traps ile birlikte sunulur. Daha geli\u015fmi\u015f u\u00e7 nokta korumas\u0131 i\u00e7in Traps ayr\u0131ca sat\u0131n al\u0131nabilir.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Son teknoloji \u00fcr\u00fcn\u00fc \u00fc\u00e7 yenili\u011fi duyurdukSekt\u00f6rdeki dengeler tamamen de\u011fi\u015fmek \u00fczere. Bu de\u011fi\u015fimin ad\u0131mlar\u0131ndan biri olan\u00a0Cortex XDR, g\u00fcvenlik ekiplerinin geli\u015fmi\u015f sald\u0131r\u0131lar\u0131 tespit edip durdurmalar\u0131na ek olarak savunma hatlar\u0131n\u0131 s\u00fcrekli geli\u015ftirme ve ileride kar\u015f\u0131la\u015f\u0131labilecek &hellip;<\/p>\n","protected":false},"author":632,"featured_media":71066,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[4827],"tags":[],"coauthors":[6734],"class_list":["post-98199","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized-tr"],"jetpack_featured_media_url":"https:\/\/origin-researchcenter.paloaltonetworks.com\/blog\/wp-content\/uploads\/2018\/04\/generic-social-media-blog-c-600x300.jpg","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/origin-researchcenter.paloaltonetworks.com\/blog\/wp-json\/wp\/v2\/posts\/98199","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/origin-researchcenter.paloaltonetworks.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/origin-researchcenter.paloaltonetworks.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/origin-researchcenter.paloaltonetworks.com\/blog\/wp-json\/wp\/v2\/users\/632"}],"replies":[{"embeddable":true,"href":"https:\/\/origin-researchcenter.paloaltonetworks.com\/blog\/wp-json\/wp\/v2\/comments?post=98199"}],"version-history":[{"count":2,"href":"https:\/\/origin-researchcenter.paloaltonetworks.com\/blog\/wp-json\/wp\/v2\/posts\/98199\/revisions"}],"predecessor-version":[{"id":98201,"href":"https:\/\/origin-researchcenter.paloaltonetworks.com\/blog\/wp-json\/wp\/v2\/posts\/98199\/revisions\/98201"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/origin-researchcenter.paloaltonetworks.com\/blog\/wp-json\/wp\/v2\/media\/71066"}],"wp:attachment":[{"href":"https:\/\/origin-researchcenter.paloaltonetworks.com\/blog\/wp-json\/wp\/v2\/media?parent=98199"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/origin-researchcenter.paloaltonetworks.com\/blog\/wp-json\/wp\/v2\/categories?post=98199"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/origin-researchcenter.paloaltonetworks.com\/blog\/wp-json\/wp\/v2\/tags?post=98199"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/origin-researchcenter.paloaltonetworks.com\/blog\/wp-json\/wp\/v2\/coauthors?post=98199"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}