Clustered 2 filings across 2 jurisdictions · filing window Nov 22, 2023 → Nov 28, 2023. View entity profile → Other incidents for this victim →
incident inc_d1f639e3e8e040be · merge_method deterministic · confidence 100%
Discovered → first regulatory filing
Time between earliest and latest filing
Not recorded for this incident
Identity (basic) · Government ID
NH VT
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Oct 31, 2023
When the intrusion reportedly occurred, per the linked filings
Oct 31, 2023
Reported by NEW HAMPSHIRE AG filing
DePauw University notified consumers of a data breach involving unauthorized access to personal information, including names and government IDs. The university offered 90 days of credit monitoring via TransUnion and provided guidance on credit freezes and fraud alerts. The incident was reported to the Vermont Attorney General.
DePauw University notified the New Hampshire Attorney General of a cybersecurity incident occurring on October 31, 2023. An unauthorized third party infiltrated systems, potentially exposing personal information (names, SSNs, DOBs) for 10 NH residents. DePauw engaged forensic specialists, notified individuals on November 22, 2023, and offered credit monitoring. No evidence of misuse was found.
Affected (this filing): 10
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.