Facebook can be manipulated to get millions of fake likes: Study reveals

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In an interesting development, the popular social media platform Facebook has now allowed thousands of accounts - real and fake - to generate at least 100 million "likes" and comments as part of so-called "collusion networks. This was basically due to a security loophole in the platform.

Facebook can be manipulated to get millions of fake likes

The case was brought to light by researchers from the University of Iowa in the U.S. and Lahore University of Management Sciences in Pakistan. During their investigation, they discovered sites that operated 'collusion networks', which was used to generate Facebook likes for free.

The new study documenting the security loophole noted that a thriving ecosystem of large-scale reputation manipulation services that leverage the principle of collusion was found. While the researchers looked at top 50 networks, they believe that much more could exist.

The researchers have also revealed that in order to participate, users had to grant the networks wide-ranging access to their accounts. Once the access was granted those accounts could be harnessed to like others, researchers said. Further, the researchers have revealed that the collusion networks exploited OAuth code, which let third-party apps like iMovie and Spotify access users' Facebook accounts.

In an experiment, CBS News also enrolled a fake Facebook account into a collusion network, granting it OAuth privileges through Apple's iMovie app. As time passed CBS News witnessed that within minutes, two posts from the brand new account had gained dozens of likes.

CBS News also reported that they tracked the collusion networks in the run-up to the 2016 US presidential election, but the agency was unable to pinpoint whether the networks were used to boost posts to benefit or hurt candidates.

Nonetheless, the researchers have warned the exploit could be used for even dangerous things or criminal acts. In addition to reputation manipulation, these networks could probably steal personal information of members.

The research was published on Wednesday and it will be formally presented at the Association for Computing Machinery Internet Measurement Conference on Nov. 1.

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