Sanction teardown · W.D. Virginia, USA · 2025-08-27
United States v. Michael Shane DeBaere (1)
What happened
In W.D. Virginia, 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 (Doctrinal Work)DeBaere cited a non-existent provision of the Guide to Judiciary Policy (Vol. 8, Pt. E, § 220.40) and quoted language that the court determined does not exist; court found the quotation fabricated and provided no basis for disclosure.
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Fabricated (Case Law)DeBaere relied on a fabricated Sixth Circuit decision cited as United States v. Zai, 939 F.3d 740, 746 (6th Cir. 2019), including a quoted passage that the court determined was invented; court rejected the authority as non-existent/misleading.
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Fabricated (Case Law)DeBaere cited United States v. Parisi, 363 F. Supp. 3d 281 (W.D.N.Y. 2019) as support for early termination; the court determined that citation is fabricated and provides no support.
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Fabricated (Case Law)The defendant's filings contained numerous additional fabricated or mischaracterized cases and quotations (the brief contained over 70 citations the court described as fabricated or mischaracterized); the court emphasized the defendant's responsibility to verify authorities.
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
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/755/UNITED_STATES_OF_AMERICA_v_MICHAEL_SHANE_DEBAERE.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).