Clustered 2 filings across 2 jurisdictions · filing window Nov 13, 2025 → Dec 24, 2025. View entity profile → Other incidents for this victim →
incident inc_9f06b8272de54faf · merge_method llm · confidence 43%
Time between earliest and latest filing
Not recorded for this incident
Discovery variance · Leak precedence · Materiality delta · SEC filing delay — no leak-site claim in this cluster; no SEC 8-K in this cluster; needs two dated filings.
Identity (basic) · Government ID · Financial account
MD VT
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Nov 1, 2023 → Aug 31, 2024
When the intrusion reportedly occurred, per the linked filings
TD Bank, N.A. notified the Maryland Attorney General that an employee improperly accessed the personal information of one Maryland resident between November 2023 and August 2024. The data involved included name, address, phone number, date of birth, SSN, account number, debit card number, and transactional data. The bank notified the customer and offered two years of free credit monitoring.
Affected (this filing): 1
TD Bank N.A. reported an insider incident where an employee compromised customer personal information, including SSNs, DOBs, and account numbers. The bank conducted an internal investigation and offered two years of complimentary credit monitoring via Fraud-Defender.
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.