What was hallucinated

Fabricated: Case Law | Brief contained numerous citation errors, including internally inconsistent and unverifiable citations; District Court concluded some citations were AI-generated and could not be verified. || Misrepresented: Case Law | Brief repeatedly misrepresented case law for propositions those cases did not support; District Court found ChatGPT described at least one cited case in the same erroneous manner.

Details

Respondent filed an opposition brief in federal litigation containing numerous citation errors and misstatements of law. The District Court found the brief AI-generated, noting ChatGPT described at least one cited case in the same erroneous manner, and admonished counsel; this Court imposed reciprocal discipline in the form of a public censure for failure to supervise and for filing an unreviewed AI-drafted brief.

Sanction teardown · SC New York, USA · 2026-02-10

Matter of Zareh

What happened

In SC New York, USA, a filing relied on ChatGPT to help draft legal argument. The court identified the following problems with the citations in that filing:

Fabricated (Case Law)

Brief contained numerous citation errors, including internally inconsistent and unverifiable citations; District Court concluded some citations were AI-generated and could not be verified.
Misrepresented (Case Law)

Brief repeatedly misrepresented case law for propositions those cases did not support; District Court found ChatGPT described at least one cited case in the same erroneous manner.

Which AI tool

ChatGPT. Note: Charlotin's public database records tool attribution only where a court order, brief, or reporting on the matter states it explicitly; "unidentified" or "implied" means the record indicates AI use but does not name a specific product — we do not guess.

Outcome

Respondent publicly censured

Additional detail

How Citation Safe would have caught this

Citation Safe runs three deterministic layers before a brief is filed: (1) does the citation exist against CourtListener's database of published opinions, (2) if quoted, does that exact language appear in the source, (3) does the cited case actually support the proposition it is cited for. Fabricated case citations fail Layer 1. Fabricated or misattributed quotations fail Layer 2 even when the underlying case is real. Misrepresented holdings — a real case cited for a proposition it does not support — are the target of Layer 3. None of these checks involve asking another language model whether the citation looks right; they are lookups and text-matches against the actual source, which is why a hallucinated citation has to survive a direct lookup against the authoritative source — not another model's opinion — to earn a VERIFIED stamp; our measured false-verify rate is published live at /quality.

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Source: https://www.damiencharlotin.com/documents/1816/Matter_of_Zareh.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).

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