{"id":103375,"date":"2022-02-18T09:36:49","date_gmt":"2022-02-18T07:36:49","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/github-vnedril-sistemu-mashinnogo-obucheniya-dlya-poiska-uyazvimostej-v-kode"},"modified":"2022-02-18T09:36:49","modified_gmt":"2022-02-18T07:36:49","slug":"github-vnedril-sistemu-mashinnogo-obucheniya-dlya-poiska-uyazvimostej-v-kode","status":"publish","type":"post","link":"https:\/\/prohoster.info\/fr\/blog\/news\/github-vnedril-sistemu-mashinnogo-obucheniya-dlya-poiska-uyazvimostej-v-kode","title":{"rendered":"GitHub int\u00e8gre un syst\u00e8me d'apprentissage automatique pour d\u00e9tecter les vuln\u00e9rabilit\u00e9s dans le code","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>GitHub a annonc\u00e9 l'ajout \u00e0 son service de Code scanning d'un syst\u00e8me exp\u00e9rimental de machine learning pour d\u00e9tecter des types courants de vuln\u00e9rabilit\u00e9s dans le code. \u00c0 ce stade des tests, cette nouvelle fonctionnalit\u00e9 est pour l'instant disponible uniquement pour les d\u00e9p\u00f4ts contenant du code \u00e9crit en JavaScript et TypeScript. Il est not\u00e9 que l'application du syst\u00e8me de machine learning a consid\u00e9rablement \u00e9largi le champ des probl\u00e8mes d\u00e9tect\u00e9s, car l'analyse ne se limite plus \u00e0 la v\u00e9rification de mod\u00e8les standard et n'est plus li\u00e9e \u00e0 des frameworks connus. Parmi les probl\u00e8mes identifi\u00e9s par le nouveau syst\u00e8me, on mentionne les erreurs entra\u00eenant des attaques par script inter-sites (XSS) et la falsification de chemins de fichiers (par exemple, via la r\u00e9f\u00e9rence \u00ab \/.. \u00bb).      <\/p>\n<p>Le service Code scanning permet de d\u00e9tecter les vuln\u00e9rabilit\u00e9s \u00e0 un stade pr\u00e9coce du d\u00e9veloppement en scannant chaque op\u00e9ration \u00ab git push \u00bb \u00e0 la recherche de probl\u00e8mes potentiels. Le r\u00e9sultat est directement attach\u00e9 \u00e0 la demande de fusion. Auparavant, la v\u00e9rification \u00e9tait effectu\u00e9e \u00e0 l'aide du moteur CodeQL, qui analyse des mod\u00e8les avec des exemples standards de code vuln\u00e9rable (CodeQL permet de cr\u00e9er un mod\u00e8le de code vuln\u00e9rable pour identifier la pr\u00e9sence d'une vuln\u00e9rabilit\u00e9 similaire dans le code d'autres projets). Le nouveau moteur, utilisant le machine learning, peut identifier des vuln\u00e9rabilit\u00e9s inconnues auparavant, car il n'est pas li\u00e9 \u00e0 une recherche de mod\u00e8les de code d\u00e9crivant des vuln\u00e9rabilit\u00e9s sp\u00e9cifiques. Le co\u00fbt de cette capacit\u00e9 est une augmentation du nombre de faux positifs par rapport aux v\u00e9rifications bas\u00e9es sur CodeQL.<br \/>\n<br \/>Source : <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=56719\">opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>GitHub \u043e\u0431\u044a\u044f\u0432\u0438\u043b \u043e \u0434\u043e\u0431\u0430\u0432\u043b\u0435\u043d\u0438\u0438 \u0432 \u0441\u0435\u0440\u0432\u0438\u0441 Code scanning \u044d\u043a\u0441\u043f\u0435\u0440\u0438\u043c\u0435\u043d\u0442\u0430\u043b\u044c\u043d\u043e\u0439 \u0441\u0438\u0441\u0442\u0435\u043c\u044b \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0434\u043b\u044f \u0432\u044b\u044f\u0432\u043b\u0435\u043d\u0438\u044f \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0451\u043d\u043d\u044b\u0445 \u0442\u0438\u043f\u043e\u0432 \u044f\u0437\u0432\u0438\u043c\u043e\u0441\u0442\u0435\u0439 \u0432 \u043a\u043e\u0434\u0435. \u041d\u0430 \u044d\u0442\u0430\u043f\u0435 \u0442\u0435\u0441\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u043d\u043e\u0432\u0430\u044f \u0444\u0443\u043d\u043a\u0446\u0438\u043e\u043d\u0430\u043b\u044c\u043d\u043e\u0441\u0442\u044c \u043f\u043e\u043a\u0430 \u0434\u043e\u0441\u0442\u0443\u043f\u043d\u0430 \u0442\u043e\u043b\u044c\u043a\u043e \u0434\u043b\u044f \u0440\u0435\u043f\u043e\u0437\u0438\u0442\u043e\u0440\u0438\u0435\u0432 \u0441 \u043a\u043e\u0434\u043e\u043c \u043d\u0430 \u044f\u0437\u044b\u043a\u0430\u0445 JavaScript \u0438 TypeScript. \u041e\u0442\u043c\u0435\u0447\u0430\u0435\u0442\u0441\u044f, \u0447\u0442\u043e \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u0435 \u0441\u0438\u0441\u0442\u0435\u043c\u044b \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u043f\u043e\u0437\u0432\u043e\u043b\u0438\u043b\u043e \u0437\u0430\u043c\u0435\u0442\u043d\u043e \u0440\u0430\u0441\u0448\u0438\u0440\u0438\u0442\u044c \u0441\u043f\u0435\u043a\u0442\u0440 \u0432\u044b\u044f\u0432\u043b\u044f\u0435\u043c\u044b\u0445 \u043f\u0440\u043e\u0431\u043b\u0435\u043c, \u043f\u0440\u0438 \u0430\u043d\u0430\u043b\u0438\u0437\u0435 \u043a\u043e\u0442\u043e\u0440\u044b\u0445 \u0441\u0438\u0441\u0442\u0435\u043c\u0430 \u0442\u0435\u043f\u0435\u0440\u044c \u043d\u0435 \u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0438\u0432\u0430\u0435\u0442\u0441\u044f [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-103375","post","type-post","status-publish","format-standard","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.2 - aioseo.com -->\n\t<meta name=\"description\" content=\"GitHub \u043e\u0431\u044a\u044f\u0432\u0438\u043b \u043e \u0434\u043e\u0431\u0430\u0432\u043b\u0435\u043d\u0438\u0438 \u0432 \u0441\u0435\u0440\u0432\u0438\u0441 Code scanning \u044d\u043a\u0441\u043f\u0435\u0440\u0438\u043c\u0435\u043d\u0442\u0430\u043b\u044c\u043d\u043e\u0439 \u0441\u0438\u0441\u0442\u0435\u043c\u044b \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0434\u043b\u044f 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