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Compiled by Citation Safe (Digital Empire Holdings LLC) from the court’s published sanction order (decided September 28, 2026). Quotes and case details come from the order itself — check the primary source before relying on them.

Sanction teardown · Federal Court, Canada · 2026-09-28

Ahmed v. Minister of Citizenship and Immigration

What happened

In Federal Court, Canada, 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 memorandum cited a case that could not be found at the stated citation; the Court treated it as a fictitious authority used in the Applicants’ arguments.
  • Fabricated (Case Law)
    The memorandum cited a case that could not be found at the stated citation; the Court treated it as a fictitious authority used in the Applicants’ arguments.
  • Fabricated (Case Law)
    The memorandum cited a case that could not be found at the stated citation; the Court treated it as a fictitious authority used in the Applicants’ arguments.
  • Fabricated (Case Law)
    The memorandum cited a case that could not be found at the stated citation; the Court treated it as a fictitious authority used in the Applicants’ arguments.
  • Fabricated (Case Law)
    The memorandum cited a case that could not be found at the stated citation; the Court treated it as a fictitious authority used in the Applicants’ arguments.
  • Misrepresented (Case Law)
    The memorandum attributed a procedural-fairness proposition concerning notice of a manifestly unfounded finding to He, but the cited paragraphs only stated general principles concerning credibility and did not turn on procedural fairness.
  • Misrepresented (Case Law)
    The memorandum cited paragraphs 28–33 of Garza for a procedural-fairness proposition, but Garza contains only ten paragraphs and addresses mischaracterization of evidence and stereotypical views concerning marriage.
  • Misrepresented (Case Law)
    The memorandum attributed to Sitnikova a broad rule requiring decision-makers to seek original or alternative-format documents before making fraud findings, but the case instead held that adverse credibility findings cannot be made merely by labeling critical documents as having little probative value.

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

Motion to extend time dismissed; application for leave and judicial review dismissed; no costs ordered, although the Court noted potential sanctions for filing an abusive document.

Additional detail

The Applicants’ Memorandum of Argument cited five cases that could not be found at the cited references and inaccurately characterized several existing decisions. The Court inferred that AI had been used without adequate human verification, noting that the filing contained fictitious authorities and misleading arguments. The Court declined to extend the filing deadline because reliance on false citations and misleading legal arguments constituted an abuse of process, but imposed no costs because the Respondent did not seek them.

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/3164/2026fc1202.pdf, via Damien Charlotin's public AI Hallucination Cases Database (CC0).