LLMs can unmask pseudonymous users at scale with surprising accuracy

March 4, 2026

Here’s something that might make you think twice about your online pseudonym — research shows that AI can now de-anonymize burner accounts with shocking accuracy. According to Dan Goodin at Ars Technica, researchers used large language models to match social media posts across platforms, achieving a recall of up to 68% and precision of 90%. That means they can reliably identify who’s behind a pseudonymous account far more than traditional methods. And here’s the kicker — this tech could seriously weaken online privacy, making it easier for stalkers, doxxers, or savvy marketers to pinpoint your real identity. So, what does this mean? Well, that ‘anonymous’ account might not be so anonymous anymore. As Goodin points out, the days of hiding behind a burner are getting tougher, and your online footprint might be bigger than you think. Keep an eye on this — because the way we protect our privacy could be about to change, big time.

Burner accounts on social media sites can increasingly be analyzed to identify the pseudonymous users who post to them using AI in research that has far-reaching consequences for privacy on the Internet, researchers said.

The finding, from a recently published research paper, is based on results of experiments correlating specific individuals with accounts or posts across more than one social media platform. The success rate was far greater than existing classical deanonymization work that relied on humans assembling structured data sets suitable for algorithmic matching or manual work by skilled investigators. Recall—that is, how many users were successfully deanonymized—was as high as 68 percent. Precision—meaning the rate of guesses that correctly identify the user—was up to 90 percent.

I know what you posted last year

The findings have the potential to upend pseudonymity, an imperfect but often sufficient privacy measure used by many people to post queries and participate in sometimes sensitive public discussions while making it hard for others to positively identify the speakers. The ability to cheaply and quickly identify the people behind such obscured accounts opens them up to doxxing, stalking, and the assembly of detailed marketing profiles that track where speakers live, what they do for a living, and other personal information. This pseudonymity measure no longer holds.

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Audio Transcript

Burner accounts on social media sites can increasingly be analyzed to identify the pseudonymous users who post to them using AI in research that has far-reaching consequences for privacy on the Internet, researchers said.

The finding, from a recently published research paper, is based on results of experiments correlating specific individuals with accounts or posts across more than one social media platform. The success rate was far greater than existing classical deanonymization work that relied on humans assembling structured data sets suitable for algorithmic matching or manual work by skilled investigators. Recall—that is, how many users were successfully deanonymized—was as high as 68 percent. Precision—meaning the rate of guesses that correctly identify the user—was up to 90 percent.

I know what you posted last year

The findings have the potential to upend pseudonymity, an imperfect but often sufficient privacy measure used by many people to post queries and participate in sometimes sensitive public discussions while making it hard for others to positively identify the speakers. The ability to cheaply and quickly identify the people behind such obscured accounts opens them up to doxxing, stalking, and the assembly of detailed marketing profiles that track where speakers live, what they do for a living, and other personal information. This pseudonymity measure no longer holds.

Read full article

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LLMs can unmask pseudonymous users at scale with surprising accuracy | Speasy