AI Privacy IncidentFebruary 3, 2026

Sears Home Services AI chatbot and call database exposure

Vendor: Transformco
Product: Samantha / KAIros (Sears Home Services AI)
Severity: high
Status: confirmed-resolved
Users affected: undisclosed; approximately 3.7 million records across three databases

Summary

On February 3, 2026, security researcher Jeremiah Fowler discovered three publicly accessible databases belonging to Sears Home Services, the home repair division of Transformco. The databases contained approximately 3.7 million records generated by the company's AI-assisted customer service systems, named Samantha and KAIros, including chat transcripts, scheduling logs, and audio recordings from customer calls. Transformco restricted access within one day of disclosure and did not issue a public statement on the exposure.

What happened

  • Fowler found three unprotected cloud databases holding 2.1 million chat transcript files, 207,381 scheduling logs, and approximately 1.4 million audio recordings from calls processed by AI-assisted scheduling and support systems.
  • The files contained customer names, physical addresses, email addresses, phone numbers, and service appointment details in plaintext.
  • The audio recordings totaled 3.9 TB of stored data.
  • Fowler submitted a responsible disclosure notice to Transformco. Access to all three databases was restricted within one day. Transformco did not respond to follow-up inquiries and did not issue a public acknowledgment of the exposure.
  • Fowler published his findings on March 17, 2026.

Timeline

  • 2026-02-03 -- Fowler discovers the three publicly accessible databases.
  • 2026-02-04 -- Transformco restricts database access within one day of disclosure.
  • 2026-03-17 -- Fowler publishes findings after confirming remediation.

What remains unclear

  • The period during which the databases were publicly accessible before February 3, 2026, has not been disclosed.
  • Transformco has not confirmed whether any third party accessed the data before Fowler's discovery.
  • The number of individual customers represented in the 3.7 million records has not been specified publicly.

Broader context

Customer-facing AI systems that log, transcribe, and archive interactions at scale create data concentrations with higher exposure consequences than equivalent text-only systems. Voice recordings introduce a distinct risk category: audio can be processed to extract biometric identifiers and reproduced in ways that static text cannot. The databases covered recordings dating back to at least 2024, meaning the accumulated exposure window substantially predated the discovery date.

Sources

Selvam Sivakumar
Written by

Selvam Sivakumar

Founder, Elephas.app

Selvam Sivakumar is the founder of Elephas and an expert in AI, Mac apps, and productivity tools. He writes about practical ways professionals can use AI to work smarter while keeping their data private.

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