MC2 2024 Data Breach

MC2 Data Aggregator Exposure (2024): 2.1 Million Consumer Records Including Passwords Left in Open Database

** Company · Data services and database operations · Data-related service provider · Global

MC2 Data Aggregator Exposure (2024): 2.1 Million Consumer Records Including Passwords Left in Open Database

data-related service or database with no clearly documented consumer domain

Confirmed · ObscureIQ Intelligence
Breach Risk Index i
30/100
Lower riskHigher risk
Lower: limited current risk based on data value and recency.
Data Sensitivity i
Standard
Exposed data is largely lower-sensitivity. Standard identity-protection precautions are advised.
2.1MRecords
2024Year

The Breach Risk Index (BRI) is a proprietary 0–100 score rating how dangerous a breach is right now, based on how recently the data has been circulating on the dark web and how valuable it is to attackers.

Classification Tags
Database ExposureSocial NetworkingCreator EconomyThird Party2024

Breach Summary

In August 2024, background-check aggregator MC2 Data left a 2.2TB database publicly accessible without a password. It exposed about 2.1 million service subscribers (email, names, salted SHA-256 passwords) and, more significantly, background-check records on roughly 106 million US people including names, dates of birth, email, phone, IP and physical addresses, employment history, property and legal records, and even data on relatives and neighbors.

Full threat analysis, exploitation vectors, and principal guidance below.

9 additional sections · verified field analysis · defensive doctrine

Querying breach corpus…
Cross-referencing exposed field types…
Resolving threat-actor attribution…
Compiling principal risk advisory…

2.1M records analyzed

About MC2

MC2 Data is a US background-check and people-search data aggregator, operating under several brand names.

Why They Hold Your Data

Data services and database operators typically ingest large volumes of structured records such as names, email addresses, phone numbers, account identifiers, business records, and linked metadata so they can host, query, enrich, or redistribute datasets. Their workflows often involve record matching, data normalization, client delivery, and ongoing database maintenance across multiple data sources.

Data Points Exposed

3 verified field types
Email Address
Full Name
Password High

Breach Impact

This is a high-sensitivity data-broker exposure: comprehensive dossiers on ~106M people (including non-customers and their relatives) enable identity fraud, profiling, and targeted scams at scale.

Exploitation & Downstream Threats

• Credential stuffing against reused passwords across other platforms | • Targeted phishing campaigns using exposed email addresses

Principal Risk Advisory

What this means for a principal

A social-platform breach: profile and contact-graph data supports impersonation, enrichment and social engineering. For a high-profile principal this is targeting-grade, not merely identity-theft-grade: the combination lets an adversary locate, impersonate, or pressure the principal with little additional work.

What You Should Do

  1. Treat the home address as exposed: review mail and package handling and physical-security routines, and brief household staff to verify unusual requests.
  2. Reset any reused passwords and enable MFA on email first, then financial accounts.
  3. Guard against SIM-swap and vishing: add a carrier port-out PIN and verify any 'support' calls independently.
  4. Do not use unofficial 'am I affected' lookups; several are themselves harvesting operations.

How ObscureIQ Can Help

  1. Corpus confirmation: determine whether and where the principal (plus household and staff) appear in this dataset and which specific fields are exposed for them.
  2. Exposure mapping and footprint neutralization: cross-reference against broker-available data and suppress still-removable elements, prioritizing address and phone, since this record re-seeds broker networks.
  3. ThreatWatch tuned to this incident's identifiers and misuse pattern (impersonation and targeting patterns, not generic credential monitoring).

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