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June 16th, 2011, 09:43 GMT · By

Apple Pulls iOS App That Collected User Passwords

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Big Brother Camera Security findings - the most commonly used passwords
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An application that anonymously collected user passwords has been pulled from the App Store shortly after its developer, Daniel Amitay, published the patterns of choosing a passcode.

Big Brother Camera Security is an iPhone/iPod touch app that takes a photo if the user presses the home button.

It is aimed at those who may want to know if someone has been sneaking a peak at their iPhone.

Based on data collected by his app, Amitay revealed that the top passcodes punched in follow typical formulas.

Users mostly go after the ever-popular four consecutive digits 1234, followed by 0000, and other sequences of four identical digits. Also popular are pattern codes, like moving in a line up and down the pad. One such example is 0852.

5683 is also a popular passcode. Although not creating a pattern in itself, it is mostly used because of what it spells on key pads where letters are associated with numbers. In this case, the password spells out ‘love.’

Many also choose passwords like 1990 or 2000, symbolizing their birth or graduation year, reports say.

Since it’s very likely that many of these users’ passcodes are also the ones used to unlock their iPhones and iPod touches, Apple decided to remove Amitay’s Big Brother Camera Security application from the App Store.

He confirms it on his blog, where he reveals that he “Got a call from Apple last night regarding the removal of Big Brother from the App Store.”

“Apparrently, Apple believed that I was ‘surreptitiously harvesting user passwords’.”

However, he adds, Big Brother Camera Security did not do any harm.

He says he has sent in a new update without the analytics in question.

Moreover, he sent an appealing on the following grounds:

 - Data in question was specific to my app, and not the iPhone.
 - Data in question was anonymous and had no identifying markers.
 - Data in question was for the purpose of improving effectiveness of future updates.




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