Reddit Flags New Research Showing LLMs Can Deanonymize Pseudonymous Users at Scale

Why This Reddit Post Drew Attention

A discussion in r/artificial highlighted a new privacy risk: LLM systems can identify people behind pseudonymous accounts with far less manual effort than older methods. The linked Ars Technica report cites a recent paper (ArXiv: 2602.16800) evaluating automated, text-driven deanonymization workflows.

Key Results Reported

According to the article, the researchers observed performance as high as 68% recall and up to 90% precision in specific setups. Those numbers indicate that modern LLM-based workflows can outperform classical re-identification pipelines that relied more heavily on hand-structured data and manual analyst effort.

The report describes multiple experiments:

Cross-platform matching using public text traces, including Hacker News and LinkedIn-linked profiles

Movie-community matching using r/movies and smaller related subreddits

A large Reddit test with 5,000 real targets plus 5,000 distractor identities

In the movie-community experiment cited by Ars, identification rates rose with richer behavioral traces. With more than 10 shared movie references, reported identification reached 48.1% at 90% precision and 17% at 99% precision.

Operational Privacy Implications

The important shift is economic: pseudonymity has historically been protected by attacker cost and effort. LLM agents reduce that cost by extracting identity signals from free text, searching the web, and iteratively ranking candidates. If this capability improves, it can affect activists, whistleblowers, researchers, and ordinary users who assume account separation is enough.

Mitigation Direction

The article summarizes mitigation ideas from the researchers: tighter API rate limits, better automated scraping detection, and stronger restrictions on bulk export of user traces. LLM providers are also urged to strengthen guardrails against explicit deanonymization use. For organizations, this is a signal to revisit privacy threat models and treat cross-platform text linkage as a practical near-term risk, not a theoretical edge case.

Sources: Ars Technica, ArXiv 2602.16800, Reddit thread