As leaks of years past proved, the complexity of user passwords weren’t always at their best. Some users might have thought if they actually used the work “password” or a variation of it hackers would never guess it. It’s a large flaw in thinking that still exists and according to new reports, the failure to complete strong passcodes has been passed down to Android users with a recent leak showing the most commonly used lock sequences.

“Now, Android lock patterns—the password alternative Google introduced in 2008 with the launch of its Android mobile OS—are getting the same sort of treatment,” according to Arstechnica.

“The Tic-Tac-Toe-style patterns, it turns out, frequently adhere to their own sets of predictable rules and often possess only a fraction of the complexity they’re capable of. The research is in its infancy since Android lock Patterns (ALPs) are so new and the number of collected real-world-patterns is comparatively miniscule.”

Apple users have a password unlock screen that consists numbers allowing you to customize your own code. It brings it’s own set of worries as there are a fixed amount of combinations that you can create but the number is increasingly high and the phone doesn’t allow you exceed more than a few tries. The same can be said with Android devices which makes it hard for anyone trying to unlock your phone to guess what your pattern is as well.

That being said, there are some patterns that are being used more frequently than others which Arstechnica highlights.

“Marte Løge, a 2015 graduate of the Norwegian University of Science and Technology, recently collected and analyzed almost 4,000 ALPs as part of her master’s thesis,” according to Arstechnica.

“She found that a large percentage of them—44 percent—started in the top left-most node of the screen. A full 77 percent of them started in one of the four corners. The average number of nodes was about five, meaning there were fewer than 9,000 possible pattern combinations.”

She also found that one of the most widely used patterns included those that resemble letters that would correspond with the users first name or someone they were close to. For the full report you can read the full story.

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