Sanction teardown · S.D. Mississippi, USA · 2026-06-30
Yuri Petrini v. City of Biloxi, Mississippi, et al.
What happened
In S.D. Mississippi, 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)AI-generated (fabricated) case holding presented in Plaintiff's Response that purported to support allegations not found in the cited authority.
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Misrepresented (Exhibits & Submissions)AI misrepresented facts from Plaintiff's earlier Case No. 178 by attributing a 'roof stop work order' to that prior filing/order.
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
Warning
Additional detail
The City Employees alerted the Court that Petrini's response relied on AI which 'hallucinated' a case holding and altered facts from Petrini's earlier Case No. 178—specifically attributing a roof stop-work order and related holding to Case No. 178 when that order contains no such material. The Court accepted this observation, reiterated warnings about AI-generated 'legal fiction' (citing Ferris and Fletcher), admonished the pro se plaintiff and reminded litigants of duties of candor and Rule 11, but imposed no sanctions based on the record.
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/2520/Petrini_v_City_of_Biloxi_Mississippi__USA_30_June_2026.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).