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Structured extracts of public breach disclosures — regulator filings (SEC, HHS, state AGs, EU DPAs) alongside threat-actor leak-site claims and press reports. SEC and HHS filings render inline from the originating regulator’s public record under the fair report privilege; other sources link out to the source URL. AI-extracted with full per-record audit trail (model, prompt version, confidence).

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Ziprecruiter, Inc. data breach (2026) · DisclosureLens

All incidents View linkage analytics →

Incident · single filing

ZIPRECRUITER, INC.

One linked filing — more sources may join as they report · filed Feb 25, 2026. View entity profile → Other incidents for this victim →

incident inc_67510b4081824aab · merge_method deterministic

Litigation Timing

Not recorded for this incident

Discovery variance · Leak precedence · Materiality delta · SEC filing delay · Filing span — no leak-site claim in this cluster; needs two dated filings.

SEC 10-K Item 1CConfirmedLifecycle stage 2 of 3: ConfirmedUnverified claimConfirmedEnforced

Affected (total reported)

—

Data types

—

Jurisdictions

FEDERAL

Linked filings

all SEC 10-K Item 1C

Timeline

Earliest sighting first · deep chronology in Litigation Timeline

FEDERALSEC 10-K Item 1CFirst filing
Filed Feb 25, 2026bd_424814c821c3827f
ZipRecruiter, Inc. filed Item 1C of its 10-K disclosing its cybersecurity governance, risk management, and strategy. The filing states that cybersecurity threats have not materially affected its business or financial condition. No specific cybersecurity incident, breach, or material impact is disclosed.

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.