Clustered 2 filings across 2 jurisdictions · filed Sep 27, 2024. View entity profile → Other incidents for this victim →
incident inc_5ee33efdb4d449e9 · merge_method deterministic · confidence 100%
Discovered → first regulatory filing
Range of discovered_at dates across filings
Identity (basic) · Credentials
Time between earliest and latest filing
Not recorded for this incident
Leak precedence · Materiality delta · SEC filing delay — no leak-site claim in this cluster; no SEC 8-K in this cluster.
NH VT
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Sep 19, 2024
Reported by VERMONT AG filing
Sep 27, 2024
Reported by NEW HAMPSHIRE AG filing
SUNY Schenectady County Community College notified consumers of a security incident involving unauthorized access to an employee email account. The attacker accessed sensitive information including names and potentially other PII. The college secured the account, engaged third-party specialists, and offered 24 months of credit monitoring and identity restoration services.
SUNY Schenectady County Community College notified the NH AG of unauthorized access to an employee's email account by an unknown individual. One NH resident was affected. The incident is under active investigation. Credit monitoring services are being offered.
Affected (this filing): 1
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.