With the federal hiring freeze lifting in mid-July, the Trump administration has rolled out a controversial federal hiring plan that critics warn will politicize and likely slow down the process rather than increase government efficiency.

De-emphasizing degree requirements and banning DEI initiatives—as well as any census tracking of gender, race, ethnicity, or religion to assess the composition of government—the plan requires every new hire to submit essays explaining which executive orders or policy initiatives they will help advance.

These essays must be limited to 200 words and cannot be generated by a chatbot, the guidance noted. While some applicants may point to policies enacted by prior presidents under their guidance, the president appears to be seeking to ensure that only Trump supporters are hired and that anyone who becomes disillusioned with Trump is weeded out over time. In addition to asking for a show of loyalty during the interview process, all federal workers will also be continuously vetted and must agree to submit to "checks for post-appointment conduct that may impact their continued trustworthiness," the guidance noted, referencing required patriotism repeatedly.

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An outdated Meta AI model was apparently at the center of the Department of Government Efficiency's initial ploy to purge parts of the federal government.

Wired reviewed materials showing that affiliates of Elon Musk's DOGE working in the Office of Personnel Management "tested and used Meta’s Llama 2 model to review and classify responses from federal workers to the infamous 'Fork in the Road' email that was sent across the government in late January."

The "Fork in the Road" memo seemed to copy a memo that Musk sent to Twitter employees, giving federal workers the choice to be "loyal"—and accept the government's return-to-office policy—or else resign. At the time, it was rumored that DOGE was feeding government employee data into AI, and Wired confirmed that records indicate Llama 2 was used to sort through responses and see how many employees had resigned.

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Login credentials belonging to an employee at both the Cybersecurity and Infrastructure Security Agency and the Department of Government Efficiency have appeared in multiple public leaks from info-stealer malware, a strong indication that devices belonging to him have been hacked in recent years.

Kyle Schutt is a 30-something-year-old software engineer who, according to Dropsite News, gained access in February to a “core financial management system” belonging to the Federal Emergency Management Agency. As an employee of DOGE, Schutt accessed FEMA’s proprietary software for managing both disaster and non-disaster funding grants. Under his role at CISA, he likely is privy to sensitive information regarding the security of civilian federal government networks and critical infrastructure throughout the US.

A steady stream of published credentials

According to journalist Micah Lee, user names and passwords for logging in to various accounts belonging to Schutt have been published at least four times since 2023 in logs from stealer malware. Stealer malware typically infects devices through trojanized apps, phishing, or software exploits. Besides pilfering login credentials, stealers can also log all keystrokes and capture or record screen output. The data is then sent to the attacker and, occasionally after that, can make its way into public credential dumps.

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The Department of Government Efficiency (DOGE) has reportedly overhauled a historically wonky Department of Defense-designed tool that automates layoffs of federal workers.

Expected to expedite DOGE's already rushed efforts to shrink the government, the redesigned software could make it easier for DOGE to quickly dismantle the biggest agencies in a blink, sources familiar with the revamp told Reuters.

Developed more than two decades ago, AutoRIF (short for automated reductions in force) was deemed too "clunky" to use across government, sources told Reuters. In a 2003 audit, the DOD's Office of the Inspector General noted, for example, that "specialized reduction-in-force procedures needed for the National Guard technicians made the module impractical." Basically, each department needed to weigh its cuts differently to avoid gutting essential personnel. Despite several software updates since then, Wired reported, the tool remained subject to errors, sources told Reuters, requiring most federal agencies to continue conducting firings manually rather than risk work stoppages or other negative outcomes from sloppy firings.

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