Sanction teardown · S.D. California, USA · 2025-12-05
In re: Nupeutics Natural, Inc.; Gladstone v. Peatross
What happened
In S.D. California, 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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Misrepresented (Legal Norm)Motion paraphrased Rule 9006(b)(1) inaccurately regarding the court's authority to extend time for excusable neglect; Court noted the wording differed from the actual rule.
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Fabricated (Case Law)AI generated a nonexistent case cited in the motion; Court could not locate any authority and counsel admitted AI produced it.
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Misrepresented (Case Law)Counsel cited In re Caneva for a Pioneer/ excusable-neglect proposition; Court found Caneva does not discuss Pioneer and the citation was misapplied.
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Misrepresented (Legal Norm)Local Bankruptcy Rule 1001-2 was cited as supporting a substantive 'technical failures' rule, but the Rule actually concerns amendments by General Order; Court found the characterization incorrect.
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
Monetary Sanction; CLE; Bar referral (monetary penalty: 950 USD.)
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/1164/Gladstone_-_Nupeutics_USA_5_December_2025.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).