743,131 Americans Affected by Massive Data Breach – Firm Says Unknown Attacker May Have Exposed Names, Social Security Numbers, Driver’s License Numb
Hundreds of thousands of Americans are now at risk of identity theft and fraud after an attacker hit a healthcare firm.
In a new filing with the Office of the Maine Attorney General, the Michigan-based McLaren Health Care says 743,131 Americans are impacted by a major cybersecurity incident.
The firm says an unknown threat actor gained access to McLaren’s database and stole patient information, which may include names, Social Security numbers, driver’s license numbers, medical histories and health insurance records.
“On or about August 5, 2024, McLaren became aware of suspicious activity related to certain McLaren/Karmanos computer systems and they immediately activated their emergency response processes. Additionally, McLaren launched an investigation with the assistance of third-party forensic specialists to secure their network and to determine the nature and scope of the activity. Through the investigation, it was determined that there was unauthorized access to the network between July 17, 2024, and August 3, 2024.
As part of the investigation, McLaren undertook an extensive forensic review of the potentially impacted files to determine whether any sensitive information was present. It was through this process, which concluded on May 5, 2025, that McLaren determined that personal information and protected health information pertaining to individuals was contained within the files involved.”
McLaren is a $7.3 billion health care delivery system that oversees 12 hospitals, ambulatory surgery centers and imaging centers along with a network of primary and specialty care doctors.
The firm says it sent letters of notification to patients affected by the data breach, while offering free credit monitoring services through IDX for 12 months.
For now, McLaren says that it is reviewing its security protocols and implementing additional technical safeguards to avoid a potential repeat of the incident.
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