What is bot detection? | How to detect & block bad bots

Bot detection is the process of distinguishing between bot and human activity, as well as between malicious and legitimate bots. The process of bot detection plays a major role in protecting digital assets and sensitive data while allowing good bots and real users to freely use a site. Bot detection ensures that businesses can block, manage, or anticipate threats without disrupting real user experience. It’s critical for protecting brand reputation, driving operational efficiency, and ensuring customer loyalty in an increasingly automated digital world.

Some bots enhance the user journey, including responsive chatbots, search engine web crawlers, and bots that test and monitor website performance.

But the majority of bots are bad for business. Malicious bots can execute automated attacks against web and mobile applications and APIs. These include account takeover (ATO), credential stuffing, carding attacks and DDoS attacks. Bots can also create fake accounts, hoard and scalp your inventory, and scrape product and pricing information.

Website owners must accurately detect and mitigate bad bots without impacting user experience. This is essential to protecting brand reputation and revenue, optimizing efficiency, and maintaining user loyalty.

Bot detection works by recognizing markers of bad bots, including requests originating from malicious domains and patterns of bot behavior exhibited. Bots engage with web and mobile applications, and APIs in distinct ways from humans. Establishing a baseline of normal human web activity and recognizing anomalous behavior from incoming traffic is at the core of effective bot detection, addressing the challenges associated with distinguishing sophisticated bots from legitimate users.

Here are some characteristics to look at to detect bots:

• Volume and Rate of Activity: Bot traffic may flood a website in large volumes. Unlike human end users, bots can view a massive volume of pages virtually instantaneously and move through multiple pages quickly. Humans, on the other hand, interact with a page in many ways and click at a moderate pace.
• Session Duration: The duration of human sessions is fairly consistent, but bots exhibit more varied view times. Bot sessions are often much shorter or much longer than human sessions. Brief crawling sessions typically entail visiting a page and then immediately leaving it. Other bot sessions last far longer than human traffic, usually indicating that a bot is browsing the site very slowly.
• Origin of Traffic: Malicious bots may originate from different countries where your customers usually live. It is especially suspicious if the traffic comes from a geography that uses a language unfamiliar to your typical client base.
• Unusual Behavior: Bot traffic can also be detected by increases in unusual customer activity. Cyberattacks from bad bots reveal themselves through surges in end user login failures and password resets, failed transactions and high volume new account creations.

With bot detection becoming increasingly aggressive, machine learning has also become a more critical technology for identifying these advanced bots. Machine learning technology analyzes normal human behaviors like mouse movement, browsing speed, and click patterns. They continuously pick up on and learn from every web interaction to spot even the most advanced bots in real time.

Bot detection is important because it allows for effective bot mitigation, which is crucial to protecting online businesses’ revenue and reputation. Without it, businesses open themselves to vulnerabilities that can impact revenue, lose customer trust, and waste valuable resources. An accurate bot detection tool has several key benefits:

• Prevents financial losses: Bot attacks can cause large financial losses due to refunds, chargebacks, lawsuits, regulatory fines and decreased stock value. And the damage to brand reputation can negatively impact long-term growth and profits.
• Protects brand reputation and consumer trust: If bots go undetected, it can result in ATO, credential stuffing and carding attacks that steal value from your users and expose their personal information. This can lead to angry customers and bad press, which negatively impacts brand reputation and consumer trust. Being able to detect bots gives users confidence that their identities and accounts will be safe on your site.
• Ensures accurate analytics: High volumes of bot traffic — both legitimate and malicious — can lead businesses to falsely categorize their website activity and result in poor business decisions about pricing, stocking goods, and investing in marketing and advertising .  By detecting bots and distinguishing bots from human activity, businesses can make good strategic decisions based on accurate numbers for real human visitors.
• Maintains website performance and preserves user experience: Bot traffic can tax your infrastructure and compromise website performance. Longer page load times frustrate human users, driving them to your competitors. Detecting and blocking bots, without increasing latency, helps your website run smoothly and preserves user experience.
• Reduces IT costs: Bot detection and early mitigation help streamline automated security efforts to fight off invisible threats, so IT teams can better prioritize their efforts and resources.
• Provides insights into otherwise invisible threats: Without effective bot detection tools, businesses can remain unaware of ongoing attacks until the damage is already done.

Here are a few techniques that a bot management solution may employ to detect bad bots on web and mobile applications, and APIs:

• Fingerprinting: Fingerprinting is the process of analyzing information, including HTTP headers to detect the software, network protocols, operating systems, or hardware devices from which a request originates. This allows security solutions to detect bots coming from malicious sources.
• Verification challenges: Website owners can deploy challenge problems that only humans can solve. A CAPTCHA is a common example of this verification process. But CAPTCHA tests disrupt the user journey, frustrate human users and drive abandonment. CAPTCHA tests also cannot guarantee protection because today’s sophisticated bots can easily solve CAPTCHAs. Alternatively, cybercriminals can leverage inexpensive CAPTCHA-solving farms. Human Challenge , an alternative human verification, preserves user experience by blocking bad bots with a single click.

• Honeypots: Honeypots are traps designed to trick a bot into revealing itself. An example is adding a hidden HTML input element to a page that legitimate human users can’t see. So, if a user accesses the element, you can be sure it’s a bot. Another technique is to stack two clickable elements in the same place on a page. Human users can only click on the upper element, while bots will click on both.
• Behavioral Analysis: Modern solutions take a behavior-based approach to bot management. Machine learning systems closely study all user behaviors and compare bot behaviors with those of legitimate human users. This technology spots small anomalies in user patterns, including on-page behavior, network signature and client and browser versions.
• IP Analysis: With tools like VPNs and proxies, or unusual geographic regions, IP analysis flags traffic from malicious sources. Bot management systems cross-reference IP addresses against global threat intelligence databases, recognize strange patterns, and detect suspicious IPs to block threats before they are able to cause serious damage. To improve accuracy, solutions may also analyze user-agent strings for inconsistencies or spoofed identities to block threats.

By studying hundreds of variables, machine learning systems can identify even the most sophisticated attacks, which would be invisible to human inspection. This can be used as a constant feedback and learning tool, continuously updating a dataset of attack patterns, based on hundreds of billions of interactions with web, mobile applications, and APIs. Continuous monitoring is an adaptable approach that manages and anticipates bot attacks in real-time without having to interfere with real user experience.

After detecting bad bots, here are a few ways to manage the malicious bot traffic:

• Rate-limit with a WAF: Websites can leverage web application firewalls (WAFs) to set rate limits based on specific rules for actions like credit card inputs and login attempts. Rate limiting won’t stop an attack, but it will slow it down so website owners can intervene. While WAFs are a good foundation, they are not enough to block bots alone. Advanced bots can get past WAFs by mirroring user behavior and rotating through many different IP addresses to bypass IP-based rules. These evasive bots can comprise more than 65% of all bad bots.
• Require proof of work: Proof of work (PoW) requires a user’s device to solve a computational challenge before executing an action, such as logging into an account or completing a transaction. This consumes a lot of energy and CPU cycles when multiple bots try to complete an action simultaneously from a single device. PoW places a cost burden on attackers, and they lose incentive to return to the website.
• Block or redirect traffic: Website owners can block bot access using block pages, redirect the malicious traffic, or block the internet address responsible for the bot traffic.

The growing advancement of technology also means the advancement of bots, thus making detection more difficult as well. With malicious actors becoming more complex and AI scrapers more common, here are some of the biggest challenges when detecting bots:

Bots are programmed to mimic human behavior

The most advanced bots are now expertly mimicking mouse movements, time delays, and human click patterns to avoid detection. This can make basic detection method, such as IP or user agent analysis inefficient in detecting advanced bots.

Rapid evolution of bot technology

Attackers constantly update their tactics, making static detection systems obsolete quickly. New bot attack methods emerge constantly, meaning new defenses must also be updated and learned in real time.

AI-driven scrapers and crawlers

New AI technologies can now power bots that are harder to distinguish from real users. AI bots adapt to defenses in real time, learn from blocked interactions, and even self-correct behaviors to avoid detection.

Legitimate bot traffic complicates filtering

Not all bots are bad, and having to distinguish between the helpful bots and malicious ones requires nuance. Search engine crawlers, uptime monitors, and accessibility tools are good bots that prove useful to digital spaces. Filtering out the bad actors without accidentally blocking the good bots that businesses depend on for visibility, functionality, and compliance is essential.

Limited visibility

Without being equipped with the most effective tools, businesses may be left in the dark about how bots are operating behind the scenes until serious damage is done. Having an effective bot management solution in place can help businesses better understand how bots are interacting with their websites, mobile apps, and APIs.

Balancing security with user experience

Sometimes, aggressive security measures can overcorrect and block real users. When detection systems flag legitimate users by mistake, false positives can cause friction that slows down real customers and can drive away loyal customers if not handled carefully.

Staying ahead of advanced bot attacks takes more than your baseline security efforts. It requires real-time monitoring and innovative technology. That’s where HUMAN steps in.

The Human Defense Platform offers a suite of bot management solutions that use a combination of intelligent fingerprinting, behavioral analysis, and pattern recognition to detect and mitigate bad bots with unparalleled accuracy. These include Account Takeover Defense, Transaction Abuse Defense, Scraping Defense, Fake Account Defense, Ad Fraud Defense, and Data Contamination Defense. The machine learning system identifies bots in real-time on web and mobile apps, and APIs.

HUMAN’s bot management solutions are designed for low latency, functioning out-of-band so it does not impact application performance. The solution easily integrates with any infrastructure, including CDNs, web servers, middleware. This optimizes security resources and infrastructure costs, and enables your team to focus on innovation and growth instead of catching malicious bots.

Can you get rid of bots?

You can’t completely get rid of bots, but with the right tools, you can block and mitigate malicious bots with bot management solutions. Some bots are good and can be useful to your website, so you don’t want to remove all bots. The goal is to remove the harmful ones that can affect your business.

How do you tell if a viewer is a bot?

You can tell a viewer is a bot by analyzing patterns like abnormal browsing speed, strange click behavior, inconsistent session duration, unusual device characteristics, and odd traffic origins. Because bots are becoming more advanced at mimicking human behavior, machine learning technology is essential in detecting these skilled bots.

How do you tell if a bot is crawling your site?

Sudden spikes in traffic, unusual page access patterns, frequent requests from the same IP addresses, and strange user agent strings can often signify that a bot is crawling your site.

Is bot traffic illegal?

Bot traffic is not illegal, but malicious bot activity like credential stuffing, scraping copyrighted content, or executing DDoS attacks is illegal.

How do you filter bot traffic?

Effective bot management solutions help flag suspicious behavior with techniques like IP reputation analysis, behavioral modeling, device fingerprinting, rate limiting, and machine learning.

How do I stop viewbotting?

Viewbotting is when bad bots falsely increase viewership on digital ads, YouTube, or Twitch. To reduce this activity, monitoring unusual engagement patterns, blocking known botnets, using CAPTCHAs, and machine learning techniques can help distinguish the fake bots from real viewers in real time.

What does CAPTCHA mean? | How CAPTCHAs work

What is account takeover? | How to detect & stop it

Carding: what it is and how to prevent it

What is scraping? | Protection from web scraping & data scraping

What is bot mitigation? | 4 types of bots & botnets | How to stop bots