Clustered 2 filings across 2 jurisdictions · filing window Mar 24, 2017 → Mar 25, 2017. View entity profile → Other incidents for this victim →
incident inc_8d8e4b7f1a0f48bd · merge_method deterministic · confidence 100%
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.
FEDERAL MT
HHS OCR · State AG
Earliest sighting first · deep chronology in Litigation Timeline
Jan 24, 2017
When the intrusion reportedly occurred, per the linked filings
Washington University School of Medicine reported a data breach to the Montana Attorney General. The breach was reported on 2017-03-24. The breach occurred on 1/24/2017. 4 Montana residents were affected.
Affected (this filing): 4
Washington University School of Medicine reported to HHS on 2017-03-25 a Hacking/IT Incident affecting 80,270 individuals. The breach resulted from an email phishing attack on employees. Breached information, located on email servers, included names, addresses, dates of birth, Social Security numbers, financial information, and treatment information. In response, the university implemented additional safeguards and retrained staff.
Affected (this filing): 80,270
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.