Pacific Lutheran University reported a data breach to the Montana Attorney General. The breach was reported on 2017-04-18. The breach occurred from 1/23/2017 to 2/22/2017. 7 Montana residents were affected.
Affected (this filing): 7
Clustered 2 filings across 2 jurisdictions · filed Apr 18, 2017. View entity profile → Other incidents for this victim →
incident inc_9534ad1620984150 · 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.
MT WA
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Jan 23, 2017
When the intrusion reportedly occurred, per the linked filings
Jan 26, 2017
Reported by WASHINGTON AG filing
Pacific Lutheran University reported a data breach to the Montana Attorney General. The breach was reported on 2017-04-18. The breach occurred from 1/23/2017 to 2/22/2017. 7 Montana residents were affected.
Affected (this filing): 7
Pacific Lutheran University, a education sector entity reported a phishing incident to the Washington Attorney General. The organization became aware of the incident on 2017-01-26 and filed notice on 2017-04-18. 813 Washington residents were affected. 82 days elapsed between awareness and notification. 3 days to identify the breach. 27 days to contain the breach.
Affected (this filing): 813
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.