ai.type 2017 Data Breach

ai.type Virtual Keyboard App Exposure (2017): 72 Million User Records Including Address Book Contacts, IMEI & Installed Apps Left in Open Database

Platform · Mobile productivity and keyboard software services · Virtual keyboard application · Global

ai.type Virtual Keyboard App Exposure (2017): 72 Million User Records Including Address Book Contacts, IMEI & Installed Apps Left in Open Database

AI virtual keyboard application for mobile devices (no longer available)

Confirmed · ObscureIQ Intelligence
Breach Risk Index i
34/100
Lower riskHigher risk
Moderate: notable exposure with meaningful misuse potential.
Data Sensitivity i
Standard
Exposed data is largely lower-sensitivity. Standard identity-protection precautions are advised.
72.7MRecords
2017Year

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 ExposureTechnologyMobile AppUsers2017

Breach Summary

In December 2017, the virtual keyboard app ai.type exposed a misconfigured MongoDB database of 577GB, revealing detailed records on about 31 million users. The exposed data was extraordinarily broad: names, email addresses, phone numbers, dates of birth, genders, geographic locations, IP addresses, device information, IMEI and IMSI numbers, cellular network names, lists of installed apps, harvested address-book contacts, profile photos, and social-media profiles.

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

10 additional sections · verified field analysis · defensive doctrine

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

72.7M records analyzed

About ai.type

ai.type is a customizable virtual keyboard app for Android and iOS that offers themes, prediction, and emoji input to a large mobile user base.

Why They Hold Your Data

Keyboard applications collect user accounts, device data, usage analytics, and potentially highly sensitive typed-input or personalization records tied to mobile productivity workflows.

Recent Developments

The exposure drew scrutiny over how much personal data keyboard apps collect, including harvesting users’ address-book contacts.

Data Points Exposed

15 verified field types
Address Book Contacts
Cellular Network
Date of Birth High
Device Information
Email Address
Full Name
Gender
Geographic location
IMEI
Imsi
Installed Apps
IP Address
Phone Number
Profile Photo
Social Media Profile

Breach Impact

This is among the most invasive exposures in the corpus: device identifiers (IMEI/IMSI), installed-app inventories, precise location, and harvested contacts enable device tracking, deep profiling, and harm to third parties whose contact details were uploaded without consent.

Exploitation & Downstream Threats

• Identity verification bypass using name + date of birth combination | • SIM swap attacks where phone numbers are present | • Targeted phishing campaigns using exposed email addresses | • Doxxing risk from physical address exposure | • Social media account targeting and impersonation

Principal Risk Advisory

What this means for a principal

A consumer-service breach: contact and account data supports phishing, account takeover and profile enrichment. For a high-profile principal the main risk is credible impersonation and enrichment of existing exposure.

What You Should Do

  1. Guard against SIM-swap and vishing: add a carrier port-out PIN and verify any 'support' calls independently.
  2. 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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