Clustered 3 filings across 3 jurisdictions · filing window Jun 11, 2026 → Jul 31, 2026. View entity profile → Other incidents for this victim →
incident inc_a7add23388cd48e8 · merge_method deterministic · confidence 95%
Discovered → first regulatory filing
Range of discovered_at dates across filings
IN NH TX
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.
all State AG
per-filing reported counts
State AGs report only their own residents; bars show per-filing counts.
Earliest sighting first · deep chronology in Litigation Timeline
Apr 16, 2026
When the intrusion reportedly occurred, per the linked filings
Apr 16, 2026
Reported by NEW HAMPSHIRE AG, TEXAS AG filings
Goodwin Procter LLP reported a data breach to the Indiana Attorney General. The breach occurred on 2026-04-16 and was reported on 2026-06-11. 2 Indiana residents were affected. 31,727 individuals affected in total.
Affected (this filing): 31,727
Goodwin Procter LLP reported a cybersecurity incident to the New Hampshire Attorney General on June 22, 2026. On April 16, 2026, a single user account was compromised via social engineering (phishing). The attacker accessed the network for a limited period, obtaining personal information of one New Hampshire resident, including name, address, SSN, and financial account/credit card numbers. Goodwin disabled the account, engaged third-party experts, notified law enforcement, and offered two years of credit monitoring. The incident is contained.
Affected (this filing): 1
Goodwin Procter LLP based in Washington, District of Columbia, a other entity reported a data breach to the Texas Attorney General. The breach was discovered on 2026-04-16 and reported on 2026-07-31. 1,550 Texas residents were affected. 13,805 individuals affected in total. Types of information involved: Name of individual;Social Security Number Information;Other. Consumers were notified via U.S. Mail.
Affected (this filing): 1,550
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.