Crypto Scammers Still Thrive on Twitter despite Clampdown

Scam bots after cryptocurrency on Twitter

Although Twitter has claimed that its fight against scam-bots has led to the suspension of over 70 million fake accounts in the past two months, it seems the bots are winning the day. The crypto sector is still being targeted by scammers that have so far escaped the social giant’s house-cleaning.

Recent Twitter activity shows the bots are still on the hunt for cryptocurrency on Twitter. Most of the scams offer free Ethereum currency in the form of promotions and giveaways, using the bait of huge returns for contract sign-ons that involve a small bitcoin investment. Camouflaged as big players in various sectors, they are making catches that amount to millions of dollars in cryptocurrency as a result.

Crypto Industry Fighting Back

Developers in the industry have not been taking the attacks by fraudulent tweeters lying down. Instead they have been working on solutions aimed at identifying and eliminating the chameleon-like scammers which adopt the usernames and profile pictures of luminaries.

These recently included legendary cybersecurity giant and 2016 US presidential runner John McAfee, and cryptocurrency trader and analyst Tone Vays. But they are not shy of using accounts run by dignitaries and stars within the music, movie and political arenas as well.

Crypto Scam-Bots Still Thriving

Having faked their accounts, the most common way the scam-bots use these is by pushing giveaways in responses to tweets. And they don’t do it just once or twice. A researcher from the Institute for the Future’s Digital Intelligence Lab in California says these pseudo accounts can tweet their fake promises more than a thousand times a day. Samuel C. Woolley said this alone should help Twitter identify the scam-bots.

Recent scam-tweets conducted in the past few days indicate that in spite of the Twitter clamp-down on fake accounts, the scammers are still offering deals that could  be avoided by canny tweeters with the standard “if it’s too good to be true, it probably isn’t” approach.

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