Sanction teardown · SC New York, USA · 2026-06-01
Sharei Torah v. Hendel
What happened
In SC New York, USA, a filing relied on an unnamed/unconfirmed AI tool to help draft legal argument. The court identified the following problems with the citations in that filing:
-
Fabricated (Case Law)Cited a non-existent case caption and citation; court could not find any case titled 'Ennis v. Lessing' at the cited reporter.
-
False Quotes (Case Law)Attributed a non-existent holding/quote to Mullane; the quoted language does not appear in the Mullane opinion at the cited pin cite.
-
Misrepresented (Case Law)Overstated and mischaracterized the holding of Waco by asserting state court proceedings are 'void' after removal; the court found the offered pin cite and characterization inaccurate.
-
Misrepresented (Case Law)Misstated the Things Remembered holding to suggest only a federal court may determine procedural defects in removal; the pin cite did not support that sweeping proposition.
-
Fabricated (Exhibits & Submissions)Referenced a 'Standing Order of Reference' (12 Misc. 00032) and an involuntary bankruptcy petition but provided no supporting court order or petition; the court found these documentary assertions unsupported/absent from the filing.
Which AI tool
an unnamed/unconfirmed AI tool. 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
Brief Struck; Adverse Costs Order (monetary penalty: 1 .)
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.
Check a brief before you file it → · See our live false-verify rate
Source: https://www.damiencharlotin.com/documents/2588/Sharei_Torah_v_Hendel_USA_1_June_2026.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).