Sanction teardown · D. Nevada, USA · 2026-04-07
Sims v. Souily-Lefave (1)
What happened
In D. Nevada, 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:
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Fabricated (Case Law)Plaintiff cited Cruz v. Fox for the proposition regarding premature depositions; the Court found the citation to be AI-generated/misleading and not supporting the claimed proposition.
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Fabricated (Case Law)Plaintiff cited Green, Tweed of Delaware, Inc. v. DuPont Dow Elastomers, L.L.C. as addressing assertion of privilege; the Court treated the citation as AI-generated or otherwise unreliable.
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Fabricated (Case Law)Plaintiff cited Barrow v. Greenville Indep. Sch. Dist. as allegedly granting a protective order when a deposition was premature; the Court found the citation to be AI-generated/mischaracterized and not reliable for that proposition.
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Fabricated (Case Law)Plaintiff cited Pioneer Drive, LLC v. Nissan Diesel America, Inc. and characterized it as supporting prematurity arguments; the Court noted that the cited opinion says nothing about prematurity and treated Plaintiff's reliance as AI-generated/misleading (but acknowledged the opinion recognizes Rule 37's flexibility).
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
Warning
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/1942/Sims_v._Souilly-Lefave_USA_7_April_2026.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).