Clustered 2 filings across 2 jurisdictions · filed May 12, 2026. View entity profile → Other incidents for this victim →
incident inc_dd5fcf86648d48db · 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.
NH VT
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Aug 10, 2025
When the intrusion reportedly occurred, per the linked filings
Aug 10, 2025
Reported by NEW HAMPSHIRE AG filing
Tulane University reported a data breach to the Vermont Attorney General. The breach was reported to the AGO on 2026-05-12. The reporting organization type is Educational. 69 Vermont residents were affected. Categories of data breached: Social Security Numbers, Financial Account Codes, Credit or Debit Account Info.
Tulane University notified the New Hampshire Attorney General of a data security incident involving a zero-day vulnerability in Oracle’s E-Business Suite. Unauthorized access occurred on August 10, 2025, exposing names, Social Security numbers, and direct deposit banking information of current and former employees and their dependents. Tulane notified law enforcement, applied patches, and began mailing notifications on April 2, 2026, offering one year of credit monitoring to 170 affected New Hampshire residents.
Affected (this filing): 170
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.