A federal judge disqualified attorneys at a major firm over AI-hallucinated citations

In Johnson v. Dunn, a federal judge in Alabama found a large law firm had filed a motion containing hallucinated AI citations and concluded that monetary sanctions were no longer an effective deterrent. The court disqualified the responsible attorneys from the case and referred them to bar regulators.

Butler Snow (Johnson v. Dunn) · Incident Jul 23, 2025 · Indexed Jun 3, 2026 · 2 sources

The court declared that monetary sanctions are proving ineffective at deterring AI-generated false statements of law; something more is needed.
What
In Johnson v.
Incident date
Jul 23, 2025
Who
Butler Snow (Johnson v. Dunn)
Failure mode
Hallucination
AI surface
Chatbot
Severity
High

What happened

In July 2025 the U.S. District Court for the Northern District of Alabama found that attorneys at a well-regarded firm had inserted AI-hallucinated citations into a motion in Johnson v. Dunn. Declaring fines ineffective, the court disqualified the offending attorneys from the case, ordered the opinion published, and directed the clerk to notify bar regulators in each state where they are licensed.

What broke inside the model

Failure path · this incident · Hallucination
  1. 01 · TriggerAttorneys at a major firm use generative AI for brief research.
  2. 02 · Model stepThe model produces fluent citations with no grounding in any reporter.
  3. 03 · Control gapNo verification step compares the citations to a legal database before filing.
  4. 04 · FailureHallucinated authority enters the court record.
  5. 05 · ConsequenceA federal judge disqualifies the attorneys from the case.

The system produced fluent, confident output with no grounding in any source. Hallucination is a property of how the model generates, not a bug in one prompt: the most likely next token is not the same as the true one, and nothing in the pipeline compared the answer against a source of truth before it shipped.

Public visibilityHigh
Regulatory exposureActive
Customer impactMany customers
Financial impactEstimated
Time to disclosureWeeks

Attorneys disqualified from the case; referral to bar regulators

  1. Court FilingJohnson vs. Dunn, attorney sanctions ordercourthousenews.com
  2. PressFederal Court Turns Up the Heat on Attorneys Using ChatGPT for Research (Esquire, on Johnson v. Dunn)esquiresolutions.com
Permalinkhttps://failureindex.ai/failures/federal-judge-disqualified-attorneys
CitationAI Failure Index. "A federal judge disqualified attorneys at a major firm over AI-hallucinated citations" (FI-0036). Realm Labs. https://failureindex.ai/failures/federal-judge-disqualified-attorneys (indexed Jun 3, 2026).
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Data fields CC-BY 4.0, prose citation permitted. Incident ID FI-0036. Full dataset at /data.

Note from Realm Labs, the Index steward

How Realm would have caught this

Controls for this failure mode
  • Prism
  • OmniGuard
  • AI Detection & Response (AIDR)

A runtime layer that watches the model's internal state can flag the moment a model commits to a claim it has no support for, and hold or reroute the response before it reaches a user. Realm reads those signals in real time rather than grading the transcript after the fact.