DFAT exposes email addresses of Aussies stuck overseas

By
Follow google news

Applicants to a financial assistance program.

The Department of Foreign Affairs and Trade (DFAT) apologised late Wednesday after mistakenly exposing the email addresses of Australians stuck overseas that had applied for financial assistance to get home.

DFAT exposes email addresses of Aussies stuck overseas

The email addresses “were visible to other” recipients of the email sent by DFAT at 11.15am on Wednesday regarding the department’s financial hardship program.

Set up earlier this month, the program offers six-month loans to Australians stranded overseas to pay for expenses, including flights home.

Recipients of the email said that the number of addresses exposed in the ‘to’ field ranged from around 1000 to many multiples of that number, though a report by The Guardian put the number in the “hundreds”.

The department tried to recall the message before sending a follow-up missive asking recipients to delete it and not forward it elsewhere.

It sought to assure program applicants that it took “privacy and the handling of personal information very seriously” and added that it had “reviewed internal measures” to prevent a repeat.

In an official statement published to Twitter just before 9pm, DFAT apologised "for unintentionally disclosing email addresses of stranded Australians we’re trying to help get home."

“No other personal information was disclosed," it added. “We want to get you home, and are working as hard as we can to do so.”

Got a news tip for our journalists? Share it with us anonymously here.
Copyright © iTnews.com.au . All rights reserved.
Tags:

Most Read Articles

Telstra used ConnectID impermissibly for months

Telstra used ConnectID impermissibly for months

University of Sydney "online IT code library" breached

University of Sydney "online IT code library" breached

US bars approvals of new models of DJI, all other foreign drones

US bars approvals of new models of DJI, all other foreign drones

Services Australia describes fraud, debt-related machine learning use cases

Services Australia describes fraud, debt-related machine learning use cases

Log In

  |  Forgot your password?