Sanction teardown · N.D. Illinois, USA · 2026-04-09
Ifeoma Delliane Chinedu Obi v. Cook County, Illinois, et al. (1)
What happened
In N.D. Illinois, 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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False Quotes (Case Law)Plaintiff quoted language attributed to Marshall v. Marshall (547 U.S. 293 (2006)) that the Court found does not appear in that decision.
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Fabricated (Case Law)Plaintiff relied on a non-existent Seventh Circuit case cited as Andrade v. Arby Concessions to dispute the court's dismissal; Court found the case is not real.
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False Quotes (Exhibits & Submissions)Plaintiff attributed a quoted passage to this Court's November 18, 2025 Order that the Court found is not in that Order.
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False Quotes (Case Law)Plaintiff quoted Ridder v. City of Springfield (109 F.3d 288) as saying sanctions are unavailable unless served before the case is disposed of; Court found that language is not in Ridder.
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
Brief Struck; Monetary Sanction (monetary penalty: 4999 USD.)
Additional detail
(Sanction was initially 9,750 USD, but court later corrected the order, reducing the amount to 5000 USD. No explanation was given.)
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/1982/gov.uscourts.ilnd.475370.97.0.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).