{"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\/pl\/blog\/news\/github-vnedril-sistemu-mashinnogo-obucheniya-dlya-poiska-uyazvimostej-v-kode","title":{"rendered":"GitHub wdro\u017cy\u0142 system uczenia maszynowego do wykrywania luk w kodzie","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

GitHub og\u0142osi\u0142 wdro\u017cenie eksperymentalnego systemu uczenia maszynowego w us\u0142udze Code scanning, kt\u00f3ry ma na celu identyfikowanie powszechnych typ\u00f3w podatno\u015bci w kodzie. Na etapie test\u00f3w nowa funkcjonalno\u015b\u0107 jest dost\u0119pna tylko dla repozytori\u00f3w z kodem w j\u0119zykach JavaScript i TypeScript. Zaznacza si\u0119, \u017ce zastosowanie systemu uczenia maszynowego znacznie zwi\u0119kszy\u0142o zakres wykrywanych problem\u00f3w, poniewa\u017c teraz analiza nie ogranicza si\u0119 do sprawdzania typowych wzorc\u00f3w i nie jest zwi\u0105zana z znanymi frameworkami. W\u015br\u00f3d problem\u00f3w wykrywanych przez nowy system wymienia si\u0119 b\u0142\u0119dy prowadz\u0105ce do atak\u00f3w typu cross-site scripting (XSS), zniekszta\u0142cenie \u015bcie\u017cek plik\u00f3w (na przyk\u0142ad poprzez wskazanie «\\\/..») oraz podstawienie zapyta\u0144 SQL i NoSQL. <\/p>\n

Us\u0142uga Code scanning umo\u017cliwia wykrywanie podatno\u015bci na wczesnym etapie rozwoju, skanuj\u0105c ka\u017cd\u0105 operacj\u0119 «git push» pod k\u0105tem potencjalnych problem\u00f3w. Wynik jest bezpo\u015brednio do\u0142\u0105czany do pull requestu. Wcze\u015bniej sprawdzanie odbywa\u0142o si\u0119 przy u\u017cyciu silnika CodeQL, kt\u00f3ry analizowa\u0142 wzorce na podstawie typowych przyk\u0142ad\u00f3w podatnego kodu (CodeQL pozwala\u0142 na utworzenie wzoru podatnego kodu w celu wykrycia podobnej podatno\u015bci w kodzie innych projekt\u00f3w). Nowy silnik, wykorzystuj\u0105cy uczenie maszynowe, mo\u017ce identyfikowa\u0107 wcze\u015bniej nieznane podatno\u015bci, poniewa\u017c nie jest powi\u0105zany z przeszukiwaniem wzorc\u00f3w kodu opisuj\u0105cych konkretne podatno\u015bci. Cen\u0105 za t\u0119 mo\u017cliwo\u015b\u0107 jest zwi\u0119kszona liczba fa\u0142szywych alert\u00f3w w por\u00f3wnaniu do sprawdze\u0144 opartych na CodeQL.
\n
\u0179r\u00f3d\u0142o: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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 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