Pentagon Plans to Spend $132 Million on Credit Monitoring for DOD's OPM Hack Victims
![](https://cdn.nextgov.com/media/img/cd/2015/08/25/082515pentagonNG/860x394.jpg?1627548790)
Frontpage/Shutterstock.com
The Office of Personnel Management is asking agencies to help share in the cost of offering identity-theft protection to hacked feds.
The Defense Department plans to spend $132 million to pay for credit-monitoring services for Pentagon workers and contractors affected by the massive hack of federal background investigation files.
That’s according to a July 28 “reprogramming” request, signed by DOD Comptroller Mike McCord, asking permission from Congress to shift funds around from other budget accounts to cover the “higher-priority requirement.”
Federal News Radio first reported on the reprogramming request.
DOD’s money shifting is required to “provide a suite of identity monitoring and recovery services” for DOD personnel and contractors affected by the hack. This includes individual notifications, identity restoration support, ID monitoring for minor children and continuous credit monitoring among other services.
The Office of Personnel Management announced in July background investigation files on about 21 million current and former federal employees as well as contractors and prospective employees had been stolen by hackers. A related hack of OPM personnel files netted personal information on 4 million federal employees.
In July, OPM asked agencies to help pay for credit-monitoring services related to the hack of background check files. The total price tag for the hack-protection services is still unknown and complete notification to all affected individuals could take as long as four months.
OPM, itself, paid about $20 million for three years of identity-theft protection and credit monitoring for employees affected by the smaller hack of personnel files. As of July, OPM said about 98 percent of the 4 million employees affected had been contacted.
(Image via Frontpage/ Shutterstock.com)
NEXT STORY: IARPA tries to predict the unpredictable