The High Price Tag of Malicious Bots
A bot is a term used to describe a software application designed to carry out automated tasks online. These tasks vary in complexity, but typically involve repetitive actions that would be difficult and extremely repetitive for a human to carry out – usually due to the high volumes involved and the speed at which they must be carried out.
Wikipedia, for instance, uses bots to flag user edits that amount to vandalism, or to suggest edits that would be likely to improve articles. Google, meanwhile, uses web-crawling bots to scour the index of the internet so that articles appear in search results.
These, and countless other “good” bots, perform helpful, useful tasks that improve the user experience in some way.
Of course, while many bots perform beneficial actions, there are – unfortunately — plenty that do not. “Bad” bots can be used by cyber attackers or other bad actors to make life miserable for users: perhaps carrying out vulnerability scans to identify weaknesses to be exploited, performing acts of vandalism, spreading fake news, scraping protected content, executing credential stuffing attacks, and more.
Bots carry out their work largely undercover. Much of the time, users don’t interact with bots, although they certainly witness their effects – both good and bad. Identifying bots, especially the bad ones, require special bot detection tools. When it comes to staying safe online, they can make all the difference.
Bad bots, bad bots. Whatcha gonna do?
Bad bots cause damage in all sorts of ways. One of these is the economic damage wrought on businesses that have malicious bot traffic targeted at them. According to a recent report, bots cost businesses an average of 3.6 percent of annual revenue, equating – in some cases – to hundreds of millions of dollars for the worst-hit businesses.
One of the most damaging aspects of bad bot attacks is how long it can take to discover them: a crucial part of being able to stop them in their tracks. The same report notes that, on average, it takes upward of 14 weeks – approaching four months – for a successful bot attack to be detected.
This poses a major challenge when it comes to being able to adequately carry out damage limitation that could detrimentally impact customer satisfaction, a company’s reputation, and far more.
As noted up top, bad bots can come in a variety of different flavors. One example is a scalper bot which will rapidly swoop in and snap up certain pieces of inventory, such as concert tickets or video game consoles that are in short supply. These can then be sold on for a hefty profit by the creator or owner of the bot in question. The result is an impaired customer experience, since the bots move faster than any genuine user is able to, and rob them of the ability to buy certain items on a website.
Another type of bot is an account checker, which utilizes stolen credentials in the form of usernames and passwords to try and take over accounts in what is known as credential stuffing attacks.
One more bot is the scraper bot, which “scrapes” data such as product descriptions, inventory levels, prices, and more – and then use it as a way to undercut competitors or steal users away.
When asked, more than 80 percent of businesses said that levels of customer satisfaction had been impacted negatively by bots. The problem’s not going away, either. As more users rely on the internet, and specifically the likes of e-commerce websites for retail, the ramifications of bad bots are going to be felt more than ever. To this, you can add technological advances that make it possible to use bots for automating a growing number of nefarious activities, which previously would have required a human behind the scenes.
Protect against bad bots
Protecting against bad bots is essential. Fortunately, help is at hand in the form of advanced bot protection tools. These function by collecting and analyzing user behavioral data, then seeking out anomalies that differ from what it expects to see. Machine learning technology is a game-changer in this domain by making bot detection systems that grow smarter over time.
The really impressive part, though, is that these tools don’t block all bots indiscriminately; they’re able to block just the bad bots, while still allowing good bots to continue doing their thing.
As the late Melvin Kranzberg said, “technology is neither good nor bad, but neither is it neutral.” This 100 percent applies to bots, which simply follow automated scripts to carry out tasks across the internet. Whether those tasks are beneficial or detrimental to the user experience can vary wildly.
By using the right safeguards, however, organizations can ensure they get to promote the positive usage of bots while minimizing the more negative effects.
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