Sanction teardown · CA California, USA · 2025-12-17
L.A. Housing Outreach, LLC v. Medoff
What happened
In CA California, 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 (Case Law)The opinion notes many citations in counsel's reply brief were incorrect or did not exist; the court struck the brief and relied on this factual finding when imposing sanctions.
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Misrepresented (Case Law)Counsel cited Green v. Healthcare Services, Inc. for the proposition that stay denials are reversed for ignoring hardships, but the court observed Green dealt with a wrongful death action and did not support that proposition.
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
Reply brief struck; monetary sanction; State Bar referral (monetary penalty: 5070 USD.)
Additional detail
The court found that the majority of legal authorities in appellant counsel's reply brief were incorrect or did not support the propositions for which they were cited. The court struck the reply brief, imposed monetary sanctions of $5,070, and directed a copy of the opinion be forwarded to the State Bar.
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/1255/LA_Housing_Outreach_v._Mdeoff_17_December_2025.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).