Clustered 3 filings across 3 jurisdictions · filing window May 30, 2026 → Jun 9, 2026. View entity profile → Other incidents for this victim →
incident inc_4b3449df9736430e · merge_method human · confidence 100%
Discovered → first regulatory filing
Gap between first leak claim and first regulatory filing
Time between earliest and latest filing
Not recorded for this incident
Discovery variance · Materiality delta · SEC filing delay — no SEC 8-K in this cluster; needs two dated filings.
IN NH
Leak Site · State AG
Earliest sighting first · deep chronology in Litigation Timeline
Mar 28, 2026
When the intrusion reportedly occurred, per the linked filings
Mar 28, 2026
Reported by NEW HAMPSHIRE AG filing
Taos Mountain Casino is a Native American gaming casino located in Taos, New Mexico. It is owned and operated by the Taos Pueblo, a federally recognized tribe known for its ancient, historic adobe pueblo.
Taos Mountain Casino notified the New Hampshire Attorney General of a cybersecurity incident discovered on March 28, 2026. Unauthorized access to computer systems resulted in the potential compromise of one New Hampshire resident's name, address, and Social Security number. The casino disconnected network access, engaged forensic investigators, reset credentials, and offered 12 months of credit monitoring via Kroll.
Affected (this filing): 1
Taos Mountain Casino reported a data breach to the Indiana Attorney General. The breach occurred on 2026-03-28 and was reported on 2026-06-09. 1 Indiana residents were affected. 4,099 individuals affected in total.
Affected (this filing): 4,099
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.