Sanction teardown · N.D. California, USA · 2025-07-30
Coronavirus Reporter Corporation v. Apple Inc.
What happened
In N.D. California, USA, a filing relied on ChatGPT to help draft legal argument. The court identified the following problems with the citations in that filing:
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Fabricated (Case Law)Anti-SLAPP motion cited a non-existent case; court found Klein v. Cheung, 20 Cal. App. 5th 1045 (2018) does not exist.
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Misrepresented (Case Law)Anti-SLAPP motion cited Aptos Residents Ass’n v. Cnty. of Santa Cruz in a manner unrelated to the issues posited; court found the citation misdirected to different issues.
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Misrepresented (Case Law)Anti-SLAPP motion relied on Atari Interactive, Inc. v. Redbubble, Inc., which the court found addressed different issues than those asserted.
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Misrepresented (Case Law)Anti-SLAPP motion invoked Makaeff v. Trump Univ., LLC for propositions not supported by that case, per the court.
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False Quotes (Case Law)Response to OSC attributed a quotation to Hall v. City of Los Angeles that does not appear in the opinion; court identified the quote as hallucinated.
Which AI tool
ChatGPT. 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
Sanctioned to repay opposing party's counsel fees (monetary penalty: 1 USD.)
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/637/Coronavirus_Reporter_v._Apple_USA_30_July_2025.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).