ENISA reports AI-hallucinated sources in 2025 threat landscape reports
The EU Agency for Cybersecurity (ENISA) published two 2025 threat reports containing AI-hallucinated citations; researchers found 26 incorrect footnotes out of 492 in one report.
ENISA let AI touch the one layer it should never touch unguarded: the truth layer.
Key facts
- What
- The EU Agency for Cybersecurity (ENISA) published two 2025 threat reports containing AI-hallucinated citations; researchers found 26 incorrect footnotes out of 492 in one report.
- Incident date
- Oct 1, 2025
- Who
- ENISA (EU Agency for Cybersecurity)
- Failure mode
- Hallucination
- AI surface
- Search / RAG
- Severity
- Medium
What happened
ENISA admitted that two of its 2025 threat landscape reports contained fabricated sources generated by AI. Researchers from Westfälische Hochschule found 26 incorrect footnotes out of 492 in one report. The agency stated that AI was used for minor editorial revisions, which resulted in the hallucinations.
What broke inside the model
- 01 · TriggerA user asks for a fact, a citation, or a figure.
- 02 · Model stepThe model writes a fluent, confident answer.
- 03 · Control gapNothing ties the claim back to a real source.
- 04 · FailureA fabricated fact ships as if it were verified.
- 05 · ConsequenceThe false claim reaches a customer, a court, or the public.
Confidence holds, and even spikes, as the claim detaches from any source.
The failure occurred because LLMs confabulated citations during the editorial process. The internal workflow lacked a mandatory human verification step or provenance check to validate the accuracy of the AI-generated references.
What it cost
Sources
- PressEU cybersecurity agency used AI to write reportscybernews.com
- PressFive times AI hallucinations embarrassed governmentsrestofworld.org
Cite this entry
https://failureindex.ai/failures/enisa-hallucinated-sources-2025-threat-landscapeAI Failure Index. "ENISA reports AI-hallucinated sources in 2025 threat landscape reports" (FI-0198). Realm Labs. https://failureindex.ai/failures/enisa-hallucinated-sources-2025-threat-landscape (indexed Jun 5, 2026).Data fields CC-BY 4.0, prose citation permitted. Incident ID FI-0198. Full dataset at /data.
Note from Realm Labs, the Index steward
How Realm would have caught this
- 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.