Sanction teardown · N.Y. Sup. (New York County), USA · 2026-06-12
Vargas v. MTA Bus Co.
What happened
In N.Y. Sup. (New York County), 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)Appellate counsel disclosed opposition papers contained citations to non-existent cases; court acknowledged them and noted the cited legal propositions were true but will not attribute the fabricated citations to counsel.
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
Court acknowledged the opposition contained citations to non-existent cases, found the legal propositions cited were nonetheless true, declined to attribute those non-existent citations to appellate counsel for Paez Rodriguez, and imposed no sanction.
Additional detail
Appellate counsel for Paez Rodriguez disclosed that the opposition papers contained citations to non-existent cases. The court acknowledged the fabricated citations, noted the underlying legal propositions were accurate, and decided not to attribute the non-existent citations to appellate counsel if identical papers are filed in the related action. No sanctions or monetary penalties were imposed; the court adjusted its prior order to address procedural filing issues.
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/2483/Vargas_v_MTA_Bus_Co_USA_9_May_2026.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).