Sanction teardown · W.D. Kentucky, USA · 2026-05-28
Roger Patel et al. v. Chandresh Patel et al.
What happened
In W.D. Kentucky, 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)Court flagged this cited case and citation as an apparent AI-generated fabrication included in Petitioners' brief.
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False Quotes (Case Law)Court identified an attributed quotation that appears not to exist in the cited opinion and flagged it as an AI-generated false quotation.
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Misrepresented (Case Law)Court noted the brief quoted language and attributed a legal proposition to Grable; flagged as an apparent AI-driven misrepresentation of the case's holding.
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False Quotes (Case Law)Court identified an asserted holding and quotation as an apparent AI-generated misquotation or misattribution to this Supreme Court decision.
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False Quotes (Case Law)Court flagged an attributed phrase to Reiter as an apparent fabricated or inaccurately quoted passage in 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
Warning
Additional detail
Order to Show Cause is here.
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/2584/Patel_v._Patel_USA_7_July_2026.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).