Sanction teardown · N.D. Texas, USA · 2025-09-15
Ezenwa Ebem v. Bondi et al.
What happened
In N.D. Texas, 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 (Exhibits & Submissions)Plaintiff repeatedly asserted a 'Clerk's Entry of Default' though the Clerk never entered default; the filings were refiling/relabeling of a motion (Dkt. Nos. 28-4; 29-1). Court treated this as a fabricated filing claim in the submissions.
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Misrepresented (Exhibits & Submissions)Plaintiff claimed an Immigration Judge made a 'final and binding' ruling that USCIS violated the APA; court found transcript only contained the IJ saying he 'can't do much other than wait' and noting lack of review authority, not a binding APA finding.
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
The court found the plaintiff's filings contained misrepresentations of the record—specifically, a purported 'Clerk's Entry of Default' that never existed and a claim that an Immigration Judge made a final binding APA finding. The court attributed these misrepresentations to likely AI generation, warned the plaintiff about consequences for false statements, and construed the misrepresentations as AI misapplication rather than deliberate deception.
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/799/EUGENE_EZENWA_EBEM_Plaintiff_v_PAMELA_BONDI_et_al_Defendants.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).