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Bot Detection

How to Detect a Bot

March 27, 20238 min Read

Malicious bots are sophisticated programs designed to mess with traffic for the benefit of a single individual, service or organization. These bots can be used to create an unfair advantage over others by mimicking human activity and avoiding common security tools. As AI bots get smarter, it’s important to take steps toward protecting your business from attack. Implementing a multi-layered security strategy that accounts for malicious bots and other threats is the best way to ensure the safety and security of your organization.

As algorithms become more advanced and AI bots become smarter, detecting bots is a crucial step to take when it comes to protecting an enterprise and its consumers.

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What Is a Bot?

Bots are a useful tool that enables their “owners” to automate tasks. For example, bots can be used to collect information online more efficiently than humans and employed for social media campaigns if set up properly. However, automated bad bots can cause problems by spamming users or performing malicious actions on websites or devices.

Malicious bot traffic can disrupt the normal functioning of websites, applications, or other internet of things (IoT) devices. Bot attacks are often coordinated across a network of devices to increase their effectiveness. In a bot attack, multiple bots or a botnet are used to perform an action, like attempting to log into a user account as part of a credential stuffing attack, on a website or device in quick succession. With this tactic, attackers can quickly overwhelm a server with traffic and or take it offline through a distributed denial of service attack (DDoS). This could lead to the website being unavailable for users or cause financial damage due to lost revenue or a hurt reputation amongst legitimate users who cannot access the website.

Overall, it's important to recognize bot traffic when browsing the internet and take steps to protect against its abusive traffic.

What are the different generations of bots?

Generally, bots can be classified as good or bad. Good bots include web crawlers (also known as Google bots), chatbots, and search engine bots. They perform automated tasks on a website or application to help it run more smoothly. Additionally, chatbots are now regularly used as a way to provide nearly human interactions with customers as part of a customer service tool on enterprise websites and apps.

Bad bots used as part of a cyberattack can be hard to detect because they often appear to be legitimate user behavior. In fact, bots are becoming more advanced as machine learning (ML) and AI become more widely used.

As technology continues to evolve, so do bots. Here are how bots have advanced over the years:

Four generations of bot challenges

  1. First-generation bots are built with basic scripting tools and mainly perform basic automated tasks like scraping, spamming, and posting fake comments on social media sites.
  2. Second-generation bots mainly operate through website development and automation tools like web analytics and user interface automation tools.
  3. Third-generation bots incorporate advanced machine learning algorithms that can autonomously analyze user interactions with a website or application to improve their performance over time.
  4. Fourth-generation bots are more robust and accurate, especially as it pertains to mimicking human behavior and evading detection.

Identifying the Signs of Bot Activity

Traffic increases or anomalous time on page

An increase in traffic can be a sign of bot activity. Unusual traffic increases (often during odd hours) such as spike in pageviews, bounce rates, and low average session duration can show bot traffic. Additionally, an increase in bounce rate can mean there’s bot traffic on a website. An abnormally low time on page can also be a sign of bot activity, as bots are programmed with an expected pattern of movement and are likely to move on if they don't reach their goal within a certain period of time.

In general, constant refilling or refreshing of content can be detected in browser logs. If you are concerned about the presence of bots on your website, it is vital to conduct regular site analytics and review the data for unusual behavior.

Fake conversions

Fake conversions are a sign of malicious bots. Imposter bots can be identified by their attempts to bypass online security measures and by their activity rate. One of the common ways imposter bots try to bypass security is by performing fake user authentication, which can be detected through a sudden increase in fraudulent accounts. Another common way imposter bots try to deceive users is spamming them with fake content.

Bad bots often use spamming techniques to scrape contact information and create fake user accounts to spam social media. Junk conversions can be detected through a sudden increase in fraudulent accounts or traffic on websites. This type of bot activity disrupts user engagement on websites by distributing spam content, leading to poor user experience and ultimately bad traffic for legitimate businesses.

Four different methods for detecting bots

  1. Device fingerprinting is the process of analyzing traffic to detect malicious bots, using machine learning to identify patterns of bot activity. This method can help detect bots that are operating through basic scripting tools, such as bots built with basic web programming languages, such as JavaScript or PHP.
  2. Traffic patterns can help you identify malicious bot activities such as content scraping and account takeover. This can also help identify bots that are performing financial fraud, like fake banking accounts and credit card fraud.
  3. Page views and bounce rate enables enterprises to identify bot traffic patterns and activities. These metrics can also be used to identify bots performing denial of service attacks.
  4. Server logs and server behavior lets users look at server logs for specific behavior patterns. If done properly, you can identify bots performing malicious activities on your website.

There are several ways to detect bots on your website. However, it's important to use a mix of different detection methods to ensure your website is protected against malicious bots.

The impacts of bot detection on user experience

The detection of malicious bots can have a significant impact on a user experience. As bot detection helps to ensure legitimate traffic is allowed access to a website, legitimate users may notice improved performance or fewer server errors.

But traditional or legacy bot detection tools, like CAPTCHAs or reCAPTCHAs, can negatively impact the user experience for legitimate customers. This is because many of these tools cannot differentiate between a real human user or an automated bot and forces legitimate customers to complete frustrating tasks.

Protect your enterprise from malicious bots with professional solutions

Protecting your enterprise and customers from bot fraud is essential to keeping your data safe and your website or application free of spam bots and other malicious bot activities. An effective bot detection and bot management tool can uncover and mitigate bots before they cause harm.

Enterprises can turn to advanced bot management solutions that use both AI and machine learning algorithms for real-time bot detection and blocking. These solutions can identify and block malicious bots based on behavior, size, IP address, and other indicators. They also help enterprises secure their ubiquitous APIs by monitoring request traffic for malicious activity.

Ultimately, however, these solutions can help an enterprise protect its brand reputation and consumer trust by ensuring their data is secure and by guaranteeing that their digital touchpoints remain available and online.

Got bots? Arkose Labs has your back

Arkose Labs’ bot management solution empowers enterprises and their security teams to both detect and mitigate malicious bot activity in real time. Arkose Labs is a significant upgrade over legacy solutions. For instance, Arkose MatchKey challenges are the strongest CAPTCHA ever made. As it is difficult to automate a bot that can solve MatchKey challenges, they make cybercriminals invest more time and capital into their attacks. Once their attacks become financially untenable, cybercriminals will look elsewhere.

Additionally, Arkose Labs provides transparency with its data, including risk scoring, to empower security teams to make informed decisions on how to best mitigate both human or non-human threats. If you want to learn more about Arkose Labs’ bot management solution, get in touch with our team today for a meeting or book a demonstration.

Want to continue learning about Arkose Labs? Watch our short explainer video below:

https://www.arkoselabs.com/blog/how-to-detect-a-bot