Pakistan National CERT Warn Gov.t, CII and Military On Serious Cyber Attacks – InfoSecBulletin

Pakistan National CERT Warn Gov.t, CII and Military On Serious Cyber Attacks – InfoSecBulletin

infosecbulletin

58 minutes ago
Alert

National Cyber Emergency Response Team of Pakistan (National CERT) has warned government agencies, military organizations, and critical infrastructure about a significant security vulnerability in Oracle E-Business Suite (EBS).

Hackers can fully control affected systems without needing a password. They can steal sensitive data and disrupt operations, causing significant damage.

According to the advisory, hackers are already using this vulnerability to run high-level commands on unpatched Oracle EBS systems. Unauthorized access, data theft, and extortion have targeted government and enterprise networks. National CERT warned that breaches in EBS, which manages finance, HR, and supply chain tasks, could cause serious operational and reputational issues.

CVE-2025-61882 is a critical vulnerability with a severity score of 9.8. It can be exploited without user action or special permissions. Hackers can target exposed EBS systems via regular web traffic (HTTP or HTTPS). Organizations with internet-connected systems or poor segmentation are particularly at risk. Any system lacking Oracle’s latest security patches is highly vulnerable.

National CERT warns that unpatched Oracle EBS systems are vulnerable, especially if accessible from untrusted networks or without multi-factor authentication for admin access. Government and military systems on shared or hybrid infrastructure are particularly high-risk due to their exposure.

The advisory outlines steps to enhance security. Organizations should quickly apply Oracle’s latest patches, secure EBS systems with firewalls, and restrict public access to management interfaces. The National CERT recommends monitoring logs for unusual activity and signs of attempted breaches, as well as enabling multi-factor authentication and updating privileged passwords.

Organizations must maintain updated offline backups of EBS databases, activate incident response plans if a breach is suspected, and preserve forensic evidence for investigation. National CERT cautioned that delaying patches or enhancing security could result in service outages, ransom demands, legal issues, and long-term damage to vital government operations.

National CERT has requested all departments and organizations to share the advisory broadly and take prompt action. It encouraged all stakeholders to incorporate this vulnerability into their risk management and to monitor their systems for potential attacks.

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.