Clustered 2 filings across 1 jurisdiction · filed Dec 9, 2020. View entity profile → Other incidents for this victim →
incident inc_ed3ac90bf2be49cc · merge_method deterministic · confidence 100%
Discovered → first regulatory filing
Range of discovered_at dates across filings
Identity (basic) · Government ID
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.
ME
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Nov 2, 2020
When the intrusion reportedly occurred, per the linked filings
Nov 2, 2020
Reported by MAINE AG filings
Employment Specialists of Maine, Inc. experienced a ransomware attack on its server, which encrypted company data. The attackers demanded a ransom, but the company did not pay and was able to restore its data from backups. The breach potentially exposed the names and driver's license numbers of approximately 3,000 individuals, almost all of whom are Maine residents.
Affected (this filing): 2,999
Employment Specialists of Maine, Inc. experienced a ransomware attack on its server. The attackers encrypted data and demanded a ransom, which was not paid. The company was able to restore its data from backups. While there is no evidence that data was exfiltrated, the company is notifying affected individuals out of an abundance of caution. The breach potentially exposed names and driver's license numbers.
Affected (this filing): 3,000
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.