Sanction teardown · M.D. Pennsylvania, USA · 2025-12-03
United States v. Brian Boehm
What happened
In M.D. Pennsylvania, 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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Misrepresented (Case Law)Cited United States v. Helena, 906 F.3d 288, 291 (3d Cir. 2018) to suggest only a court (not probation) may impose supervised-release conditions; Helena did not involve a probation officer imposing conditions and was mischaracterized.
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False Quotes (Case Law)Quoted Albertson as stating probation officers 'lack authority' to expand judicial conditions; the phrase does not appear in the published opinion and the case was misapplied.
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False Quotes (Case Law)Attributed statements to United States v. Miller, 594 F.3d 172 (3d Cir. 2010) about explicit imposition of monitoring costs; the court found those quotes and propositions false and Miller was misused.
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
Ordered disclosure of AI use and affidavit certifying accuracy of citations for future filings
Additional detail
"12) The Al tool possibly used was sophisticated enough to include pinpoint citations to precedential Third Circuit authority.13) Fortunately for Boehm , the cases cited in his motion are very real decisions by the Third Circuit Court of Appeals.14) Unfortunately for Boehm, these cases are misrepresented in his motion and his motion also contains false quotations from these opinions."
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/1123/USA_v._Boehm_USA_3_December_2025.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).