DOGE Worker's Code Supports NLRB Whistleblower -- Brian Krebs
https://krebsonsecurity.com/2025/04/doge-workers-code-supports-nlrb-whistleblower/
Lots of technical details in Brian's post. Basically this supports the accusation that Musk's doge boys were subverting internal systems to support exfiltration of data without security controls.
A whistleblower at the National Labor Relations Board (NLRB) alleged last week that denizens of Elon Musks Department of Government Efficiency (DOGE) siphoned gigabytes of data from the agencys sensitive case files in early March. The whistleblower said accounts created for DOGE at the NLRB downloaded three code repositories from GitHub. Further investigation into one of those code bundles shows it is remarkably similar to a program published in January 2025 by Marko Elez, a 25-year-old DOGE employee who has worked at a number of Musks companies.
According to a whistleblower complaint filed last week by Daniel J. Berulis, a 38-year-old security architect at the NLRB, officials from DOGE met with NLRB leaders on March 3 and demanded the creation of several all-powerful tenant admin accounts that were to be exempted from network logging activity that would otherwise keep a detailed record of all actions taken by those accounts.
Berulis said the new DOGE accounts had unrestricted permission to read, copy, and alter information contained in NLRB databases. The new accounts also could restrict log visibility, delay retention, route logs elsewhere, or even remove them entirely top-tier user privileges that neither Berulis nor his boss possessed.
Berulis said he discovered one of the DOGE accounts had downloaded three external code libraries from GitHub that neither NLRB nor its contractors ever used. A readme file in one of the code bundles explained it was created to rotate connections through a large pool of cloud Internet addresses that serve as a proxy to generate pseudo-infinite IPs for web scraping and brute forcing. Brute force attacks involve automated login attempts that try many credential combinations in rapid sequence.
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