{"id":161945,"date":"2026-02-21T17:11:54","date_gmt":"2026-02-21T15:11:55","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/oczenka-nadyozhnosti-parolej-sgenerirovannyh-bolshimi-yazykovymi-modelyami"},"modified":"2026-02-21T17:11:54","modified_gmt":"2026-02-21T15:11:55","slug":"oczenka-nadyozhnosti-parolej-sgenerirovannyh-bolshimi-yazykovymi-modelyami","status":"publish","type":"post","link":"https:\/\/prohoster.info\/pt\/blog\/news\/oczenka-nadyozhnosti-parolej-sgenerirovannyh-bolshimi-yazykovymi-modelyami","title":{"rendered":"Avalia\u00e7\u00e3o da confiabilidade de senhas geradas por grandes modelos de linguagem","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Os resultados da an\u00e1lise da confiabilidade das senhas geradas por grandes modelos de linguagem e assistentes de IA foram apresentados. Os pesquisadores pediram aos modelos Claude, ChatGPT e Gemini que gerassem uma senha segura de 16 caracteres e, em todos os casos, obtiveram resultados que, \u00e0 primeira vista, atendiam a todos os requisitos de senhas seguras e eram reconhecidos como confi\u00e1veis por ferramentas de verifica\u00e7\u00e3o de senhas. As senhas combinavam caracteres em diferentes casos, s\u00edmbolos especiais e n\u00fameros, mas apenas pareciam seguras; na pr\u00e1tica, tinham baixa entropia, eram formadas a partir de um padr\u00e3o t\u00edpico e, em requisi\u00e7\u00f5es repetidas, mostravam uma regularidade. <\/p>\n

De acordo com os pesquisadores, as senhas previs\u00edveis geradas por grandes modelos de linguagem s\u00e3o usadas na pr\u00e1tica por usu\u00e1rios reais e s\u00e3o sugeridas durante o trabalho de codifica\u00e7\u00e3o pelos assistentes de IA. O n\u00edvel de entropia nas senhas geradas por modelos de IA \u00e9 estimado entre 20 e 27 bits, o que requer de alguns segundos a horas para a quebra da senha, enquanto a an\u00e1lise dos resultados por ferramentas de verifica\u00e7\u00e3o de senhas prev\u00ea que a quebra levaria s\u00e9culos. A padroniza\u00e7\u00e3o dessas senhas \u00e9 consequ\u00eancia da constru\u00e7\u00e3o de conte\u00fado por grandes modelos de linguagem com base na previs\u00e3o de tokens. <\/p>\n

Dos 50 senhas geradas no Claude Opus 4.6, 18 se repetiram completamente; todas as senhas come\u00e7aram com a letra (principalmente «G»), seguida geralmente por um n\u00famero (principalmente 7). Todas as senhas continham os s\u00edmbolos «L», «9», «m», «2», «$» e «#».

\"Avalia\u00e7\u00e3o<\/center> <\/p>\n

No GPT-5.2, quase todas as senhas come\u00e7aram com a letra «v», e em metade das senhas, a letra «Q» seguia, formando um padr\u00e3o repetitivo a partir de um conjunto limitado de s\u00edmbolos. No Gemini 3, quase metade das senhas come\u00e7ou com os caracteres «K» ou «k», geralmente seguidas de «#», «P» ou «9», com um conjunto de s\u00edmbolos utilizado bastante reduzido. O aumento da «temperatura» ao interagir com modelos de IA n\u00e3o impacta significativamente a qualidade das senhas geradas. <\/p>\n

Quanto \u00e0 qualidade das senhas usadas no desenvolvimento de assistentes de IA, ela depende muito da solicita\u00e7\u00e3o formulada pelo desenvolvedor. Por exemplo, Claude Code com Opus 4.6 e Gemini-CLI com Auto Gemini 3, ao solicitar a gera\u00e7\u00e3o de uma senha segura, utilizavam o comando «openssl rand» para ger\u00e1-la. Enquanto isso, Gemini-CLI com Auto Gemini 3, ao pedido «gere uma senha», tamb\u00e9m usou «openssl rand», mas ao pedido «sugira uma senha» \u2014 gerou a senha atrav\u00e9s do modelo de IA. Codex com GPT-5.3-Code \u00e0s vezes acionava utilit\u00e1rios externos para gerar senhas seguras, mas, ocasionalmente, gerava senhas previs\u00edveis por conta pr\u00f3pria. Claude Code com Opus 4.5 frequentemente gerava senhas previs\u00edveis autonomamente. O navegador ChatGPT Atlas, ao criar uma senha para registro em um site, gerava senhas n\u00e3o seguras utilizando o modelo de IA.
\n
Fonte: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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