Sanction teardown · M.D. Florida, USA · 2025-11-26
The Doc App, Inc. d/b/a My Florida Green v. Leafwell, Inc. (1)
What happened
In M.D. Florida, 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)Motion cited Henson v. Allison Transmission with reporter/citation No. 6:16-cv-1223-Orl-41DCI, 2017 WL 59085 (M.D. Fla. Jan. 5, 2017), which the Court confirmed does not exist; counsel later said he intended a different Henson (2008 WL 239153), but that case does not support the propositions cited.
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Misrepresented (Case Law)Motion cited State Farm Mut. Auto. Ins. Co. v. Pressley as 727 So. 2d 1019, 1020 (Fla. 3d DCA 1999) (yielded nothing in Westlaw); counsel later pointed to 28 So. 3d 105 (Fla. 1st DCA 2010), but that decision does not contain the quoted phrase or discuss the statute counsel attributed to it.
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False Quotes (Case Law)At least two quotations in the Motion were presented as direct quotes but the cited cases do not contain the quoted language (counsel claimed an earlier draft/paraphrase error).
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
Costs Order; CLE Order; Order to file Order in any future filing; Bar Referral (monetary penalty: 1 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/1098/The_Doc_App_v._Leafwell_USA_26_November_2025.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).