Clustered 2 filings across 2 jurisdictions · filing window Mar 20, 2017 → Mar 22, 2017. View entity profile → Other incidents for this victim →
incident inc_bc9f62905c954331 · 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
Jan 22, 2017
When the intrusion reportedly occurred, per the linked filings
Jan 22, 2017
Reported by CALIFORNIA AG filing
Urology Austin reported a data breach to the Montana Attorney General. The breach was reported on 2017-03-20. The breach occurred on 1/22/2017. 62 Montana residents were affected.
Affected (this filing): 62
On January 22, 2017, Urology Austin suffered a ransomware attack that encrypted data on its servers. The incident potentially exposed patients' names, addresses, dates of birth, Social Security numbers, and medical information. The organization shut down its network, launched an investigation, and offered one year of identity monitoring through Kroll. Remediation steps included improving network security, updating backups, and retraining employees.
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.