Sanction teardown · D. Montana, USA · 2025-12-01
Brick v. Gallatin County, et al.
What happened
In D. Montana, 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 a non-existent case 'Beville v. City of Quitman, Texas, 21 F.4th 917 (5th Cir. 2021)'; the Court found the citation does not exist and directed attention to other actual cases.
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Misrepresented (Case Law)Plaintiff relied on Bevill v. Fletcher (26 F.4th 270) as supporting that a judge's pretrial declaration of guilt removes judicial immunity or supports a §1983 retaliation claim; the Court found Plaintiff mischaracterized the actual holdings.
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
Not specified in source record.
Additional detail
Plaintiff repeatedly cited non-existent or misleading authorities in her Fourth Amended Complaint. The Court identified at least one fabricated citation and several mischaracterized cases, noting these failures to comply with Rule 8 and prior court instruction, and relied on the deficient pleadings in granting dismissal.
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/1113/Brick_v._Breuner_USA_1_December_2025.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).