[FOG] – Ransomware Victim: The 19 biggest gitlabs
![[FOG] - Ransomware Victim: The 19 biggest gitlabs 1 image](https://www.redpacketsecurity.com/wp-content/uploads/2024/09/image.png)
Ransomware Group: FOG
VICTIM NAME: The 19 biggest gitlabs
NOTE: No files or stolen information are [exfiltrated/downloaded/taken/hosted/seen/reposted/disclosed] by RedPacket Security. Any legal issues relating to the content of the files should be directed at the attackers directly, not RedPacket Security. This blog is simply posting an editorial news post informing that a company has fallen victim to a ransomware attack. RedPacket Security is in no way affiliated or aligned with any ransomware threat actors or groups and will not host infringing content. The information on this page is fully automated and redacted whilst being scraped directly from the FOG Onion Dark Web Tor Blog page.
AI Generated Summary of the Ransomware Leak Page
The ransomware leak page detailing the incident involving various entities presents a list of numerous organizations and their corresponding GitLab links. While the specific victim’s name is not identifiable from the provided data, the page includes various entries related to companies involved in technology, publishing, and education sectors. The data appears to be compilations of domain links to several corporate GitLab repositories, indicating potential areas of compromise or interest, though no explicit verbatim details are provided regarding any breaches.
This summary showcases the diversity in activities among the listed companies, with an emphasis on technological development and online resources. Notably, the leak page does not contain any downloadable links or images, which may suggest an absence of exposed sensitive documents or data at this time. The layout primarily lists names and corresponding URLs, indicating a structured collection of information associated with various organizations. This lack of additional graphic content also provides a sanitized overview, focusing solely on the organizational identities rather than explicit sensitive data.
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