Compiled by Citation Safe (Digital Empire Holdings LLC) from the court’s published sanction order (decided September 17, 2026). Quotes and case details come from the order itself — check the primary source before relying on them.

Sanction teardown · W.D. Washington, USA · 2026-09-17

Cabrera Thompson v. Seattle Public Schools

What happened

In W.D. Washington, 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:

Fabricated (Case Law)

The Court found that the cited case did not exist. The Washington Reports page cited contained Cascade Security Bank v. Butler, while the Pacific Reporter page cited contained a different Kansas case. The citation was used to support an agency and ratification theory for binding non-signatories to an EEOC settlement agreement.
Misrepresented (Case Law)

The citation and proposition were materially incorrect. The Court explained that the actual Jankelson v. Cisel was a 1970 medical-malpractice case, reported at 3 Wn. App. 139, 473 P.2d 202, and did not concern aiding and abetting. The cited Washington Appellate Reports and Pacific Reporter locations corresponded to other cases.

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

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/3118/Thompson_v._Seattle_Public_Schools_USA_17_September_2026.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).