Clustered 2 filings across 2 jurisdictions · filing window Dec 20, 2024 → Feb 18, 2025. View entity profile → Other incidents for this victim →
incident inc_8c27e974d2d64b5b · merge_method human · confidence 100%
Discovered → first regulatory filing
Gap between first leak claim and first regulatory filing
Time between earliest and latest filing
Not recorded for this incident
Discovery variance · Materiality delta · SEC filing delay — no SEC 8-K in this cluster; needs two dated filings.
PII
ME
Leak Site · State AG
Earliest sighting first · deep chronology in Litigation Timeline
Oct 22, 2024 → Nov 21, 2024
When the intrusion reportedly occurred, per the linked filings
City of Noblesville is a company that operates in the Government industry. It employs 250to499 people and has 25Mto50M of revenue. The company is headquartered in Noblesville, Indiana We present to your attention, a large SQL database, confidential data of employees, confidential data of the Police, and emergency services.
Jan 22, 2025
Reported by MAINE AG filing
The City of Noblesville (Indiana) experienced an external network breach between October 22 and November 21, 2024, discovered on January 22, 2025. An unauthorized party accessed portions of the city's network and potentially downloaded files containing personal information including names and Social Security numbers. A total of 1,841 individuals were affected, including 1 Maine resident. Notification letters were sent February 18, 2025, and 12-month IDX credit monitoring services were offered.
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): 1