ODJFS fixes security flaw following recent update to unemployment system
Ohio Department of Job and Family Services (ODJFS) Director Matt Damschroder announced Monday that the agency’s information technology team discovered and fixed a security flaw that fraudsters recently attempted to exploit in Ohio’s unemployment system.
Over the past three weeks, the department has been experiencing an increased number of attempts to fraudulently access the state’s unemployment system. The root cause of the system vulnerability was determined to be a code flaw in the Ohio Job Insurance (OJI) system, specifically the linking of identity and authentication functionality between OJI and the state’s OH|ID single sign-on system.
As a precaution, ODJFS locked more than 28,000 accounts with suspicious activity. When an account is locked, the legitimate user cannot access their unemployment account and payments on the accounts are suspended.
“Our teams are working to ensure bad actors don’t have any opportunity to take benefits out of the hands of eligible Ohioans,” said Damschroder.
ODJFS estimates that $189,184.62 was paid out in bogus claims because of this security event.
This past weekend, ODJFS emailed locked account users with instructions on how to authenticate their identity online and re-establish the link to their OH|ID by setting up two-step verification and answering security challenge questions to regain access to their account.
“We currently have a high volume of callers and wait times are long,” Damschroder said. “Users can now avoid that wait time by re-authenticating their identity and regaining their access online.”
Users who are still unable to recover their account or apply for benefits online, may call ODJFS at 1-877-644-6562.
Individuals who believe they are victims of unemployment fraud may notify ODJFS online by visiting unemployment.ohio.gov. Click on the “Report Identity Theft/Fraud” button and follow the guidance for individuals.
Unemployment fraud continues to be a nationwide challenge. ODJFS is investing in robust anti-fraud measures, such as identity verification, multi-factor authentication, Artificial Intelligence and Machine Learning, and a variety of other safeguards to combat this national trend.