Backdoor found in OpenX ad platform

By
Follow google news

Package compromised since 2012 permits remote hijack.

A backdoor has existed for up to nine months in an platform offered OpenX , the self-described global leader of digital advertising which counts the New York Post, Coca Cola, Bloomberg and EA among its customers.

Backdoor found in OpenX ad platform

The backdoor was contained within the official OpenX package and recently removed.

It meant according to Sucuri researcher Daniel Cid that anyone who downloaded the product could have provided attackers "full access" to their web sites. 

"That’s how serious it is,"  Cid said.

StopMalvertising researcher Kimberly obtained a copy of the compromised file dated September 2012.

She said the backdoor, first reported by Heise Security (German), exists in the zip, tgz and bz2 archives of the software. 

"After examining openXVideoAds.zip, I was able to locate the PHP code in flowplayer-3.1.1.min.js, a file located in the plugins\deliveryLog\vastServeVideoPlayer\flowplayer\3.1.1 folder," she said.

"Server administrators can find out if they are running the OpenX version that contains the backdoor by searching for PHP tags inside .js files."

Users have warned administrators should be vigilant regarding potentially vulnerable installations of OpenX that their organisations have since disused.

OpenX have been contacted for comment and said they were aware of the reports but was not yet prepared to make a statement.

More to come.

Got a news tip for our journalists? Share it with us anonymously here.

Copyright © SC Magazine, Australia

Tags:

Most Read Articles

Popular text editor Notepad++ was hacked to drop malware

Popular text editor Notepad++ was hacked to drop malware

'Moltbook' social media site for AI agents had big security hole

'Moltbook' social media site for AI agents had big security hole

Bunnings facial recognition privacy breach ruling partially reversed

Bunnings facial recognition privacy breach ruling partially reversed

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?