Majority Of Bad Bots Behave Like Humans

Nearly all bad bot traffic on the Web imitates human user behavior in some way or attempts to evade detection, while humans now encompass more than 54 percent of all website traffic after being outnumbered by bots the past two years.

New 2015 bot data from Distil Networks, which draws from its Hadoop cluster that includes 74 billion bot requests and data culled from its customer base shows, that bad bot traffic decreased from 22.78% to 18.61% from 2014 to 2015, while good bot traffic dropped from 36.32% to 27.04% during that period, putting human user traffic on top. But the jump in human Web traffic likely has much to do with a rise in new Internet users in China, India, and Indonesia, the report says.

“Bots still have the upper hand,” says Rami Essaid, CEO of Distil. “What we’ve seen in the past year is bots are more sophisticated in their tactics and more focused: the bad guys are lot less likely to throw [bots] on the Web to a more focused approach of ‘we’re going to narrow down the attack to a specific aspect of a Web app.’”

Distil’s bad bot data doesn’t include bots used in distributed denial-of-service attacks: it focuses on bots used for fraud and other badness, such as web scraping, data-mining for competitive purposes, personal and financial data-stealing, brute-force login, man-in-the middle attacks, digital ad fraud, spam, and transaction fraud.

These “advanced persistent” bots, as Distil calls the latest generation of bots, are able to execute JavaScript, load cookies, manipulate a mouse, imitate keystrokes, and other human actions. he says. “Bots are a lot more intelligent than ever before,” and often are embedded in the browser and more difficult to spot, he says. “They look like a real person.”

Essaid says he was surprised these sophisticated bots are now the majority. “Sixty-three percent can load JavaScript, for example,” he says. “That’s big ... If the majority are running JavaScript, they are skewing all of the marketing numbers,” for example, he says.

Nearly 40% can perform human-like behaviors and tasks, and 73% use multiple IP addresses to evade detection. Some 20% of these bots use more than 100 IP addresses.

Bots indeed are a boon for bad guys. In addition to bots that spread banking Trojans and other malicious code, online ad fraud via bots is booming, according to a recent report by the Association of National Advertisers (ANA) and WhiteOps. The average brand suffered $10 million in damages in 2015, and bots are expected to cause some $7.2 billion in losses to advertisers this year, up from $5 billion in 2014. This brand of bots tricks advertisers with phony clicks that appear to be from human users.

Distil’s data shows that midsized websites are hit most with bad bots: 26% of all Web traffic on sites with an Alexa ranking of 10,001 to 50,000, came from bad bots. Real-estate websites overall suffered a 300% jump in bad bot traffic, and 31% of all web traffic on digital publishing sites comes from bad bot activity.

The US ranks as the number one nation with bad bots (40%), followed by India and Israel. Maldives has the highest bad bots per online user, 526, followed by Israel (168) and Kyrgyzstan (94).

“It’s where the end bot is coming from, but not necessarily who’s puppeteering the bot. In Maldives, there’s a giant ring of people running botnets out of there, but [there’s one] that also controls bots worldwide,” Essaid says. And US and Indian users are are popular bot targets due to their higher-speed Internet connections, for example.

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