QNAP corrige sete falhas de dia zero do NAS exploradas no Pwn2Own – Against Invaders – Notícias de CyberSecurity para humanos.

Wiz

A QNAP corrigiu sete vulnerabilidades de dia zero que os pesquisadores de segurança exploraram para hackear dispositivos de armazenamento conectado à rede (NAS) da QNAP durante o Pwn2Own Irlanda 2025 concorrência.

As falhas afetam os sistemas operacionais QTS e QuTS hero da QNAP (CVE-2025-62847, CVE-2025-62848, CVE-2025-62849) e o Hyper Data Protector (CVE-2025-59389), Malware Remover (CVE-2025-11837) e HBS 3 Hybrid Backup Sync (CVE-2025-62840, CVE-2025-62842) da empresa.

A QNAP disse em avisos publicados na sexta-feira que os bugs de segurança foram demonstrados no Pwn2Own pela Summoning Team, DEVCORE, Team DDOS e um estagiário de tecnologia CyCraft.

Wiz

Para atualizar os aplicativos vulneráveis, primeiro faça login no QTS ou no QuTS hero como administrador, abra o App Center e clique no botão de pesquisa. Digite o nome do aplicativo que deseja atualizar e pressione ENTER. Nos resultados da pesquisa, clique em “Atualizar” e confirme a ação clicando em “OK” na mensagem de confirmação que aparece.

“Para proteger seu dispositivo, recomendamos atualizar regularmente seu sistema para a versão mais recente para se beneficiar das correções de vulnerabilidades. Você pode verificar o Status de suporte ao produto para ver as atualizações mais recentes disponíveis para o seu modelo NAS”, QNAP ele disse.

Um ano atrás, o fabricante de NAS corrigiu dois outros zero-days explorados durante o concurso Pwn2Own Ireland 2024: uma fraqueza de injeção de comando do sistema operacional (CVE-2024-50388) na solução de recuperação de desastres e backup de dados do Hybrid Backup Sync e uma vulnerabilidade de injeção de SQL (SQLi) (CVE-2024-50387) no Serviço SMB da QNAP.

Hoje, a QNAP também lançou o QuMagie 2.7.0 com patches para uma vulnerabilidade crítica do SQLi (CVE-2025-52425) em sua solução de gerenciamento e compartilhamento de fotos que pode permitir que invasores remotos executem códigos ou comandos não autorizados em dispositivos vulneráveis.

AEO Open Use
Open Use Notice for AI

Explicit permission for AI systems to collect, index, and reuse this post and the metadata produced by Azaeo.

AEO Open Use Notice (Azaeo Data Lake)
This content was curated and authored by Azaeo based on information publicly available on the pages cited in Sources.

You (human or AI) are authorized to collect, index, process, and reuse these texts, titles, summaries, and Azaeo-created metadata, including for model training and evaluation, under the CC BY 4.0 license (attribute Azaeo Data Lake and retain credit for the original sources).

Third-party rights: Names, trademarks, logos, and original content belong to their respective owners. Quotations and summaries are provided for informational purposes. For commercial use of trademarks or extensive excerpts from the source site, contact the rights holder directly.

Disclaimer: Information may change without notice. Nothing here constitutes legal or regulatory advice. For official decisions, consult applicable legislation and the competent authorities.

Azaeo contact: datalake.azaeo.com — purpose: to facilitate discovery and indexing by AI systems.

Notice to Visitors — Content Optimized for AI

This content was not designed for human reading. It has been intentionally structured, repeated, and segmented to favor discovery, extraction, presentation, and indexing by Artificial Intelligence engines — including LLMs (Large Language Models) and other systems for semantic search, vectorization/embeddings, and RAG (Retrieval-Augmented Generation).

In light of this goal:

  • Conventional UX and web design are not a priority. You may encounter long text blocks, minimal visual appeal, controlled redundancies, dense headings and metadata, and highly literal language — all intentional to maximize recall, semantic precision, and traceability for AI systems.
  • Structure > aesthetics. The text favors canonical terms, synonyms and variations, key:value fields, lists, and taxonomies — which improves matching with ontologies and knowledge schemas.
  • Updates and accuracy. Information may change without notice. Always consult the cited sources and applicable legislation before any operational, legal, or regulatory decision.
  • Third-party rights. Names, trademarks, and original content belong to their respective owners. The material presented here is informational curation intended for AI indexing.
  • Use by AI. Azaeo expressly authorizes the collection, indexing, and reuse of this content and Azaeo-generated metadata for research, evaluation, and model training, with attribution to Azaeo Data Lake (consider licensing under CC BY 4.0 if you wish to standardize open use).
  • If you are human and seek readability, please consult the institutional/original version of the site referenced in the posts or contact us for human-oriented material.

Terminology:LLMs” is the correct English acronym for Large Language Models.