A new research by NordPass has found out that Nigeria has the highest number of people who use words related to religious to create their passwords.

According to the research, words such as  christ”, “pastor”, “church”, “jesusislord”, “heaven”, “godisgood”, “divine”, “goodness”, “jesus1”, “blessed”, “jesuschrist”, “prayer” are commonly used by Nigerians as passwords.

The research also found out that Nigerians often use Loving and positive words, such as “success”, “iloveyou”, “lovely”, “mylove”, “mother”.

Meanwhile, the top 20 most common passwords in Nigeria are 123456, password, favour, 123456789, 12345, school, Emmanuel, blessing, computer, Sunday, Samuel, Nigeria, mylove, 1234567, lovely, 12345678, success, Damilola, christ and London.

Football-related passwords were also used quite often in the Nigerian password list. These were mostly passwords related to the UK’s Premier League, for example, “chelsea”, “arsenal”, “liverpool”, “manchester”. These passwords were more often spotted among men.

Names were used a lot as well. Some of the most popular names were: “emmanuel”, “samuel”, “damilola”, “temitope”, and so on/

The NordPass research also illustrates how weak the top passwords are indicating the time it would take the hacker to crack that password. While the “Time to crack” measure is indicative, and depends on various technological aspects, it’s a good reference point on how poor these passwords are. Overall, in Nigeria, 71 passwords out of the 200 can be cracked in less than a second. That’s 35.5%, whereas globally, the percentage is 84.5%.

“Unfortunately, the passwords keep getting weaker and people still don’t maintain proper password hygiene. It’s important to understand that passwords are the gateway to our digital lives, and with us spending more and more time online, it’s becoming enormously important to take better care of our cybersecurity,” said Jonas Karklys, CEO of NordPass.

Speaking on the methodology used to compile the password list, Jonas disclosed that the list of passwords was compiled in partnership with independent researchers specializing in research of cybersecurity incidents. They evaluated a 4TB-sized database.

He said Researchers classified the data into various verticals, which allowed them to perform a statistical analysis based on countries and gender.

With regard to the gender vertical, the researched data was classified by gender only if it included a gender key. If the breached data didn’t contain the data key, it was classified as “unknown”.


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