LLM researchers put the price of unmasking a Hacker News pseudonym at $1 to $4

On the source's own counts, 226 correct calls against 25 wrong ones is 226 out of 251 answers, or 90.0% ^[10]. Against the full 338 it is 66.9% ^[11], and the difference is the 86 accounts the pipeline declined to name ^[2]. The Calibrate stage is built to abstain when the model is not certain, to keep false positives down ^[5]. (The three outcomes Cryptopolitan reported sum to 337, one short of the test group ^[20].)

At the top of the quoted price range, running all 338 profiles would cost $1,352, and at the bottom $338 ^[18]. Both fit within the under-$2,000 total the researchers reported for all their experiments ^[4]. Spread across 226 correct names, that is between $1.50 and about $6 a name ^[19]. The inputs are web search, embeddings and a reasoning model such as GPT-5.2, with no breached data involved ^[6]. "The combination is often a unique fingerprint," Lermen wrote in a February 24 blog post ^[13]. He added, according to Cryptopolitan, that the cost is only going down ^[14].

The hit rate is less solid than the price. The paper says its results show "the practical obscurity protecting pseudonymous users online no longer holds" ^[8]. Every one of the 338, though, had a bio pointing to a LinkedIn page, and the researchers stripped the identifying details before the agent searched, according to Decrypt ^[3]. The published tests do not show a two-in-three rate on accounts whose owners never tied a handle to a real profile. On transcripts from Anthropic's interviews with 125 scientists, the agent identified at least 9 ^[12], or about 7% ^[21].

There are three ways to read the distance between 67% and 7%. One is that the Hacker News figure is near a ceiling, set by people who keep a LinkedIn page and post about their work. Another is that any rate belongs to the authors' own build, since they withheld code and prompts ^[7], and a copycat starts from a written description. The third, or rather the one that matters to anyone pricing the risk, is that at $1 to $4 an attempt even the interview test's rate puts a correct name at roughly $14 to $56 ^[22].

I think the third reading holds. The authors name governments targeting journalists and activists, and scammers building dossiers for social-engineering pitches, among the likely users ^[17]. For either, $56 a name is small. The researchers also argue there is no single switch a model provider can disable, only a chain of individually harmless-looking tasks ^[16]. Classical non-LLM baselines came close to zero in the larger matching tests ^[15], and the 2008 Netflix re-identification needed structured ratings data ^[9]. This pipeline works from comments.

I would be wrong if a replication on accounts with no self-link finds hit rates near zero. At a 1% rate and $4 an attempt, a correct name costs $400 ^[23].