Bot mitigation is a fraud-prevention mechanism that prevents bots from scaling up attacks. Attackers have learned to evade many traditional bot mitigation solutions and challenge-response mechanisms which are designed to differentiate between bot and human activity, through a mix of automated techniques.
Consumers are using a number of channels—desktops, laptops, mobile devices, and gaming consoles—to access digital services. This means there is a correlational increase in the number of entry points to a business network. Then there is an explosion in the number of APIs powering the digital economy. All these avenues provide fraudsters with a large window of opportunity for fraud and abuse. The wider the attack in the lowest possible time, results in greater the returns; and automation helps achieve this with precision. This is why fraudsters extensively use bots and automated scripts to launch many types of attacks. Request the Arkose Labs Ultimate Guide to Bot Prevention that delves into the bot detection topic further.
Bots are used in complex attacks
Using bots, fraudsters are able to launch a thousand attacks in parallel, which allows large-scale fraud attempts. Furthermore, bot scripts are easily and cheaply available, which makes them a viable tool even for aspiring fraudsters.
Fraudsters have also studied the defense mechanisms and bot mitigation solutions that businesses deploy. This informs their methodology to break these barriers. Leveraging this information, they know when to use bots or a combination of bots and humans. Advanced bots are coded in a way to escalate human sweatshops when faced with a bot mitigation solution. This not only enables fraudsters to overcome fraud-prevention mechanisms but also launch complex, hybrid attacks that are challenging to detect.
Types of attacks bots facilitate
Much like any other vocation, cybercrime is fraudsters’ business. They mobilize their resources and make calculated investments to maximize profits. Fraudsters typically use bots for credential testing, credential stuffing, and evading detection at scale. Depending on the type of attack planned, fraudsters tap into their pool of resources to ensure maximum returns with minimum investment.
- High-volume attacks: Fraudsters, often, use basic bots to scale their attacks. There are attack types where even the simplest, unsophisticated bots prove effective because of the volume they help achieve. Because of the sheer volume of the attack, a fraudster can make money even when only a fraction of the bots succeed. For instance, sending out spam. This is a low-value but high-volume activity and needs only a few users to click malicious links to make the attack profitable.
- Low and slow attacks: When fraudsters plan an attack for the future, they usually lie low initially and use bots to do the groundwork. These bots enable fraudsters to launch low and slow attacks. They copy human behavior and mock identifying characters to evade bot mitigation solutions. For instance, attacking outer customer touchpoints such as fake reviews, up/down voting videos, and abusing in-game economies, which fetches fraudsters money.
- Evading detection: Advanced bots are sophisticated and can accurately mimic human behavior. These are automated scripts that use machine vision technology to overcome detection. Fraudsters especially use them to fool bot mitigation solutions.
- Hybrid attacks: For hybrid attacks, fraudsters use a combination of bots and human ‘laborers’. Human sweatshops takeover when bots fail to overcome fraud-prevention mechanisms. This happens when the interaction with a fraud-prevention solution is more distinct and cannot be done by the bots.
Zero tolerance to fraud
Considering that fraudsters are manipulating fraud-prevention mechanisms to avoid detection, businesses cannot continue with point or legacy bot mitigation solutions. They cannot block traffic as that can lead to loss of business. Using machine vision technology, bots can clear CAPTCHAs. Even data-driven solutions cannot discern true users from fraudsters, as digital identities have been corrupted at scale and fraudsters use them to impersonate true users.
What then is the way out for businesses to keep ahead of the fraudsters without compromising on user experience?
Businesses need a zero-tolerance to bots that ensure all customer touchpoints across all potential attack surfaces are secured. They need a dynamic evaluation of incoming traffic in real-time followed by secondary screening for high-risk traffic. This allows for efficient bot mitigation without impacting genuine traffic. An approach that combines real-time risk assessments with interactive challenges, is the way to confidently eliminate all automated threats. The proven results of this approach have made Arkose Labs the only vendor that guarantees 100% commercial SLA against automated attacks.
Multi-layered approach to bot mitigation
An effective challenge-response system allows every user a chance to prove authenticity. With sophisticated risk profiling linking up with the challenge element, good users can pass through unchallenged, but those that do face the challenges can solve them in no time. Bots, however, cannot solve these enforcement challenges. This is because the challenges are context-based, rendered in real-time and resilient machine vision technology, which causes automatic and machine-based solvers to fail.
With automation removed from the equation, the returns from the attack begin to diminish. To make good the loss, fraudsters must invest more time, effort, and resources. However, the adaptive step-up challenges slow down their progress to an extent that the attack loses its financial viability, forcing fraudsters to abandon the attack.
To explore this topic further, download the Arkose Labs Ultimate Guide to Bot Prevention.