Ticketek discloses cyber incident on external cloud platform

By
Follow google news

Some customer data "may" have been impacted.

Ticketek Australia has disclosed a “cyber incident” impacting customer information that it says was stored in a third-party cloud environment.

Ticketek discloses cyber incident on external cloud platform

The ticketing company said the data - which “may” cover “customer names, dates of birth and email addresses” - was “stored in a cloud-based platform, hosted by a reputable, global third-party supplier.”

“Since our third-party supplier brought this to our attention, over the past few days we have worked diligently to put every resource into completing an investigation so that we can communicate with customers who may have been impacted, and other stakeholders, as quickly as possible,” Ticketek said in a statement late Friday.

“Our priority at this initial stage is to best protect our customers, people and all others who have entrusted us with their information. 

“As such, we have already commenced notifying those customers who may have been impacted.”

Ticketek noted that passwords and payment information were not impacted, because they were either encrypted or run separately.

The company said it had notified authorities including the Australian Cyber Security Centre (ACSC), the Office of the Australian Information Commissioner (OAIC) and the National Office of Cyber Security.

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

Most Read Articles

NSW Health clinicians "normalise" bypass of cyber security controls

NSW Health clinicians "normalise" bypass of cyber security controls

ServiceNow nears deal to buy cyber security startup

ServiceNow nears deal to buy cyber security startup

UK government was hacked in October, minister confirms

UK government was hacked in October, minister confirms

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?