Sanction teardown · S.D. Ohio, USA · 2025-08-19
Lahti v. Consensys Software Inc.
What happened
In S.D. Ohio, 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:
-
IssueFabricated: Case Law
-
Misrepresented (Case Law)At least 2
-
IssueFabricated: Case Law
-
IssueFabricated: Case Law
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
Submission Stricken
Additional detail
"The case at bar epitomizes the concern. Inordinate judicial resources were expended on reviewing cases cited by Plaintiff that did not exist. No doubt Plaintiff’s opponent in this litigation was forced to expend similar energies. Here, too, as noted, certain cases Plaintiff cited in support of her arguments stood for the opposite result from that which Plaintiff stated in her briefs. This kind of activity not only wastes precious and limited judicial resources, but it also drives up the cost of litigation unnecessarily for those who must defend against or seek to prosecute claims on behalf of paying clients, given the underpinnings of the American Rule that attaches to most civil litigation in this country."
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/718/Lahti_v._Consensys_Software_USA_20_AUgust_2025.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).