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Clustered 4 filings across 3 jurisdictions · filing window Jun 5, 2024 → Apr 23, 2025. View entity profile → Other incidents for this victim →
incident inc_fb577f5fe3f84aa3 · merge_method human · confidence 100%
Discovered → first regulatory filing
Range of discovered_at dates across filings
Gap between first leak claim and first regulatory filing
Time between earliest and latest filing
Not recorded for this incident
Materiality delta · SEC filing delay — no SEC 8-K in this cluster.
PII · Government ID
CA ME
Leak Site · State AG
Earliest sighting first · deep chronology in Litigation Timeline
Jun 3, 2024 → Jun 7, 2024
When the intrusion reportedly occurred, per the linked filings
Jun 5, 2024
Reported by CALIFORNIA AG filing
We unlock the potential of millions of people worldwide. Our assessments, publications and research spread knowledge, spark enquiry and aid underst anding around the world.
We unlock the potential of millions of people worldwide. Our assessments, publications and research spread knowledge, spark enquiry and aid underst anding around the world.
Apr 8, 2025
Reported by MAINE AG filing
Cambridge University Press & Assessment experienced a cybersecurity incident involving unauthorized access to a network segment of its Australian subsidiary. Suspicious activity was identified on June 5, 2024, with the breach window occurring between June 3 and June 7, 2024. The incident involved personal information, including names and addresses. The company engaged forensic experts, notified law enforcement, and enhanced security controls. Affected individuals are offered two years of credit and identity monitoring.
Cambridge University Press & Assessment (CUPA) experienced a network intrusion during June 3–7, 2024, in which an unauthorized actor exfiltrated data from a subsidiary network segment in Australia on June 5, 2024. On April 8, 2025, CUPA determined that 68 Maine residents' names and Social Security numbers were among the affected files. Consumer notifications were mailed April 23, 2025. Two years of Experian credit monitoring was offered to affected individuals.
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.
Affected (this filing): 68