Compiled by Citation Safe (Digital Empire Holdings LLC) from the court’s published sanction order (decided September 8, 2026). Quotes and case details come from the order itself — check the primary source before relying on them.

Sanction teardown · CA Minnesota, USA · 2026-09-08

Asiedu v. Eastlund

What happened

In CA Minnesota, 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 district court found that Asiedu cited nonexistent cases in his filings; the appellate opinion confirms that these citations did not constitute existing law but does not identify them individually.
Misrepresented (Case Law)

The district court found that Asiedu repeatedly cited caselaw for legal propositions it did not support, misleading the court; the appellate court upheld the finding but did not identify the individual misrepresented precedents.

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

Monetary Sanction (monetary penalty: 2341 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/3044/Asiedu_USA_8_September_2026.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).