{"id":147923,"date":"2025-11-10T23:11:54","date_gmt":"2025-11-10T21:11:56","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/ataka-whisper-leak-po-opredeleniyu-tematiki-obshheniya-s-ai-chatbotami-cherez-analiz-tls-trafika"},"modified":"2025-11-10T23:11:54","modified_gmt":"2025-11-10T21:11:56","slug":"ataka-whisper-leak-po-opredeleniyu-tematiki-obshheniya-s-ai-chatbotami-cherez-analiz-tls-trafika","status":"publish","type":"post","link":"https:\/\/prohoster.info\/pl\/blog\/news\/ataka-whisper-leak-po-opredeleniyu-tematiki-obshheniya-s-ai-chatbotami-cherez-analiz-tls-trafika","title":{"rendered":"Atak Whisper Leak dotycz\u0105ca okre\u015blenia tematyki rozm\u00f3w z AI chatbotami poprzez analiz\u0119 ruchu TLS.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Badacze bezpiecze\u0144stwa z firmy Microsoft opracowali technik\u0119 ataku za po\u015brednictwem zewn\u0119trznych kana\u0142\u00f3w Whisper Leak, kt\u00f3ra umo\u017cliwia klasyfikacj\u0119 temat\u00f3w zapyta\u0144 do serwis\u00f3w opartych na du\u017cych modelach j\u0119zykowych na podstawie pasywnej analizy szyfrowanego ruchu przesy\u0142anego przez po\u0142\u0105czenie TLS. Informacje o wielko\u015bci pakiet\u00f3w sieciowych i op\u00f3\u017anieniach mi\u0119dzy ich transmisj\u0105 okaza\u0142y si\u0119 wystarczaj\u0105ce do okre\u015blenia temat\u00f3w zapyta\u0144 do AI chatbot\u00f3w z dok\u0142adno\u015bci\u0105 przekraczaj\u0105c\u0105 98%. W praktyce proponowana metoda mo\u017ce by\u0107 stosowana do identyfikacji w ruchu tranzytowym u\u017cytkownika okre\u015blonych temat\u00f3w zapyta\u0144, na przyk\u0142ad pr\u00f3b uzyskania informacji o nielegalnych dzia\u0142aniach, bez odszyfrowania zawarto\u015bci. <\/p>\n

Narz\u0119dzia do pozyskiwania danych z zrzut\u00f3w ruchu, szkolenia modeli oraz testowania dzia\u0142ania metody s\u0105 dost\u0119pne na GitHubie. Mo\u017cliwo\u015b\u0107 przeprowadzenia ataku zosta\u0142a zaprezentowana dla 28 popularnych du\u017cych modeli j\u0119zykowych od najwi\u0119kszych producent\u00f3w. Na przyk\u0142ad, dok\u0142adno\u015b\u0107 okre\u015blania zapyta\u0144 na temat \u201epranie pieni\u0119dzy\u201d dla wielu us\u0142ug AI wynios\u0142a 100%, przy obecno\u015bci w analizowanym ruchu 1 poszukiwanego zapytania i 10000 zapyta\u0144 niezwi\u0105zanych z dan\u0105 tematyk\u0105.

\"Atak<\/center> <\/p>\n

Przyczyn\u0105 wycieku informacji jest to, \u017ce modele generuj\u0105 odpowied\u017a na zapytanie krok po kroku, token po tokenie, w ka\u017cdym kroku wykorzystuj\u0105c wcze\u015bniejszy token jako kontekst do okre\u015blenia nast\u0119pnego najbardziej prawdopodobnego s\u0142owa lub frazy. Odpowiednio, dla ka\u017cdego tokena wysy\u0142any jest oddzielny pakiet sieciowy, a op\u00f3\u017anienie mi\u0119dzy pakietami odpowiada op\u00f3\u017anieniu mi\u0119dzy okre\u015blaniem przez model nast\u0119pnego tokena. <\/p>\n

W TLS, je\u015bli nie u\u017cywa si\u0119 kompresji danych, d\u0142ugo\u015b\u0107 szyfrogramu jest r\u00f3wna rozmiarowi tekstu niezaszyfrowanego powi\u0119kszonemu o sta\u0142\u0105. Przy tworzeniu modelu, kt\u00f3ry kojarzy wyszukiwane zestawy token\u00f3w z rozmiarami pakiet\u00f3w i op\u00f3\u017anieniami mi\u0119dzy ich wysy\u0142k\u0105, mo\u017cna do\u015b\u0107 dok\u0142adnie okre\u015bli\u0107 obecno\u015b\u0107 poszukiwanych temat\u00f3w w ruchu. W ramach badania przygotowano trzy warianty takich modeli uczenia maszynowego, opartych na architekturach sieci neuronowych LightGBM, Bi-LSTM i BERT. Dla ka\u017cdego modelu przeprowadzono eksperymenty maj\u0105ce na celu okre\u015blenie poszukiwanej tematyki, analizuj\u0105c tylko rozmiary pakiet\u00f3w, tylko op\u00f3\u017anienia mi\u0119dzy pakietami oraz oba kryteria.

\"Atak<\/center> <\/p>\n

Aby zmniejszy\u0107 skuteczno\u015b\u0107 pasywnej analizy tematyki zapyta\u0144, programi\u015bci us\u0142ug AI zaproponowali do\u0142\u0105czanie losowych dodatk\u00f3w wype\u0142niaj\u0105cych, buforowanie przesy\u0142ania token\u00f3w lub zast\u0119powanie fikcyjnych pakiet\u00f3w.
\n
\u0179r\u00f3d\u0142o: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u0418\u0441\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u0442\u0435\u043b\u0438 \u0431\u0435\u0437\u043e\u043f\u0430\u0441\u043d\u043e\u0441\u0442\u0438 \u0438\u0437 \u043a\u043e\u043c\u043f\u0430\u043d\u0438\u0438 Microsoft \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u0430\u043b\u0438 \u0442\u0435\u0445\u043d\u0438\u043a\u0443 \u0430\u0442\u0430\u043a\u0438 \u043f\u043e \u0441\u0442\u043e\u0440\u043e\u043d\u043d\u0438\u043c \u043a\u0430\u043d\u0430\u043b\u0430\u043c Whisper Leak, \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u044e\u0449\u0443\u044e \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 \u043f\u0430\u0441\u0441\u0438\u0432\u043d\u043e\u0433\u043e \u0430\u043d\u0430\u043b\u0438\u0437\u0430 \u0448\u0438\u0444\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0433\u043e \u0442\u0440\u0430\u0444\u0438\u043a\u0430, \u043f\u0435\u0440\u0435\u0434\u0430\u0432\u0430\u0435\u043c\u043e\u0433\u043e \u0447\u0435\u0440\u0435\u0437 TLS-\u0441\u043e\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u0435, \u043a\u043b\u0430\u0441\u0441\u0438\u0444\u0438\u0446\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0442\u0435\u043c\u044b \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 \u043a \u0441\u0435\u0440\u0432\u0438\u0441\u0430\u043c \u043d\u0430 \u0431\u0430\u0437\u0435 \u0431\u043e\u043b\u044c\u0448\u0438\u0445 \u044f\u0437\u044b\u043a\u043e\u0432\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439. \u0418\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u0438 \u043e \u0440\u0430\u0437\u043c\u0435\u0440\u0435 \u0441\u0435\u0442\u0435\u0432\u044b\u0445 \u043f\u0430\u043a\u0435\u0442\u043e\u0432 \u0438 \u0437\u0430\u0434\u0435\u0440\u0436\u043a\u0430\u0445 \u043c\u0435\u0436\u0434\u0443 \u0438\u0445 \u043f\u0435\u0440\u0435\u0434\u0430\u0447\u0435\u0439 \u043e\u043a\u0430\u0437\u0430\u043b\u043e\u0441\u044c \u0434\u043e\u0441\u0442\u0430\u0442\u043e\u0447\u043d\u043e \u0434\u043b\u044f \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u0438\u044f \u0442\u0435\u043c \u0437\u0430\u043f\u0440\u043e\u0441\u043e\u0432 \u043a AI-\u0447\u0430\u0442\u0431\u043e\u0442\u0430\u043c \u0441 \u0442\u043e\u0447\u043d\u043e\u0441\u0442\u044c\u044e \u0431\u043e\u043b\u0435\u0435 98%. 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