Clustered 2 filings across 2 jurisdictions · filing window Mar 17, 2016 → Mar 21, 2016. View entity profile → Other incidents for this victim →
incident inc_ff219b023ff045d6 · merge_method deterministic · confidence 100%
Discovered → first regulatory filing
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.
Government ID · Identity (basic) · Financial
CA NH
all State AG
Earliest sighting first · deep chronology in Litigation Timeline
Feb 17, 2016
When the intrusion reportedly occurred, per the linked filings
Feb 17, 2016
Reported by CALIFORNIA AG filing
LAZ Karp Associates, LLC, a professional services firm, notified the New Hampshire Department of Justice on March 17, 2016, of a security incident involving personal information of approximately 53 current and former New Hampshire employees. The specific nature of the unauthorized access was not detailed in the filing.
Affected (this filing): 53
Laz Karp Associates, LLC (doing business as LAZ Parking) experienced a business email compromise incident on February 17, 2016. An unknown individual impersonated an executive via email, tricking an employee into sending 2015 Form W-2s for employees. Affected data included names, addresses, Social Security numbers, and compensation data. The company notified affected employees on March 9, 2016, and offered 24 months of identity protection services.
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.