Tech
Understanding Bot Attacks
Identifying the entities behind bad bots
Bad bots are operated by malicious actors who use them as tools to launch large-scale attacks, primarily for financial gain. These attackers aim to maximize returns while minimizing costs, much like any business. Bots provide an efficient, cost-effective, and sophisticated means of evading detection. Implementing modern bot management solutions can help reduce the profitability of such bot attacks. Also check bot detection test
What risks come with bad bots?
Malicious bots are used for various harmful activities, including:
Account Takeover: Bots exploit stolen credentials to hijack accounts. Nearly half of all login attempts are from advanced bots. Once inside, attackers can make fraudulent purchases, steal payment information, or deplete loyalty points.
Inventory Issues: Scalper bots buy in-demand, limited-supply items to resell at high prices. They can also pile up inventory by adding products to carts without checking out, making items appear out of stock to legitimate customers.
Fake Account Creation: Bots create seemingly legitimate accounts to commit fraud, exploit new account promotions, purchase high-demand products, or spread misinformation.
Website Scraping: Bots scrape site content, allowing competitors to undercut prices or scammers to create counterfeit sites, deceiving customers into buying fake goods or stealing payment information.
Carding: Bots test stolen credit card details to identify valid cards, leading to fraudulent transactions, chargebacks, and brand damage.
Slow Site Speed and Increased Costs: High-volume bot traffic can degrade site performance and increase operational costs, adversely affecting customer experience.
How do bot attacks work?
Bots target multiple online channels, exploiting vulnerabilities for malicious purposes. The main channels are:
APIs: APIs account for 90% of the web app attack surface and 80% of web traffic, making them prime targets. Traditional detection methods, like fingerprinting, often fail to protect APIs effectively.
Mobile Applications: Bots also target mobile apps, where security may be weaker due to user negligence. While human-like behaviors are harder to mimic on mobile, the threat remains significant.
Websites: Bots frequently attack websites, attempting actions like login attempts or data scraping to impersonate brands or steal information. Attackers leverage automation to scale their attacks and increase profitability.
Can Malicious Actors Use Fake Data to Trick Bot Detection Systems?
Yes, malicious actors can indeed use fake data to
deceive bot detection systems. This tactic is becoming increasingly popular for several reasons:
Attackers can purchase harvested digital fingerprints to use during their attacks. By mimicking real human behavior, these fingerprints can trick traditional bot detection solutions into thinking they are interacting with legitimate users.
The growing trend of internet privacy allows real users to mask their true identities. As a result, legacy bot detection solutions struggle to distinguish between genuine users and bots.
Given these challenges, a modern approach to bot detection is essential. This approach must account for the increasing sophistication of bots, which now closely mimic human behavior and the evolving behaviors of real users who increasingly resemble bots.
