Clustered 2 filings across 2 jurisdictions · filed May 15, 2017. View entity profile → Other incidents for this victim →
incident inc_f073c11f72cf4971 · merge_method deterministic · confidence 100%
Discovered → first regulatory filing
Time between earliest and latest filing
Not recorded for this incident
Discovery variance · Leak precedence · Materiality delta · SEC filing delay — no leak-site claim in this cluster; no SEC 8-K in this cluster; needs two dated filings.
CA MT
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Feb 16, 2017
When the intrusion reportedly occurred, per the linked filings
Apr 15, 2017
Reported by CALIFORNIA AG filing
University of New Mexico Foundation reported a data breach to the Montana Attorney General. The breach was reported on 2017-05-15. The breach occurred from 2/16/2017 to 5/15/2017. 57 Montana residents were affected.
Affected (this filing): 57
The University of New Mexico Foundation disclosed that an unauthorized individual gained access to its network via a security services provider account in mid-April 2017. Affected data included names, contact info, SSNs, bank account/routing numbers, and employment data for donors and employees. The investigation was ongoing at the time of notification. Credit monitoring was offered.
About this clustering
DisclosureLens links filings into incidents through layered matchers: deterministic rules (same source document, multistate filings of one breach, tight-window same-victim pairs), a weighted-similarity scorer for cross-source candidates, and an operator review queue for everything uncertain. Each link records its own method and confidence — shown per filing in the timeline below. The system defaults to NOT merging when uncertain, because a false merge (collapsing two unrelated breaches) is more harmful than a false split (showing related filings separately); uncertain pairs route to human review instead of auto-merging. Filing summaries shown in the timeline are AI-generated extracts — verify each against its linked source.