Bot Detection: What It Is, Tools & How It Works

As of this year, bots have officially surpassed the number of humans on the internet. For the first time, automated web traffic accounts for 51% of all internet activity — a clear sign of just how drastically the digital landscape has shifted since its inception

But this isn’t just a technological milestone; it’s a golden opportunity for fraudsters. Automation allows bad actors to scale their attacks effortlessly, probing for weak points in defense systems and slipping through back- (and sometimes even front-) doors faster than human teams can react. Bots aren’t just a nuisance; they’re a force multiplier for fraud, capable of launching thousands of attacks simultaneously with surgical precision.

What Is Bot Detection?

Bot detection is the process of identifying and distinguishing automated traffic (bots) from human users across websites, servers or networks. It aims to recognize individual bots, botnets and scripts by analyzing how they behave and connect to your systems.

Not all bots are harmful. Google’s web crawlers help index pages for search, monitoring bots from uptime services help to ensure site availability and SEO tools and site analytics bots serve legitimate functions. Yet, an alarming percentage of bot traffic is used for fraudulent purposes. According to reports, 37% of bot traffic is attributed to bad bots.

In fraud prevention, bots can signal risk as they’re often used to automate account takeovers (ATOs), generate fake signups or attempt fraudulent payments. The challenge then is to allow the good bots and stop the bad ones before they breach your defenses.

The Importance of Bot Detection for Businesses

Bot detection ensures your web traffic comes from real users. Fraudsters rely on bots to mimic human behavior and launch scaled attacks like credential stuffing, carding, bonus abuse and fake onboarding attempts. These are particularly damaging in high-risk industries like fintech, eCommerce and iGaming.

Once deployed, bot attacks can hammer your site 24/7: thousands of login attempts per second, dozens of fake signups with synthetic data, credit card fields filled in at inhuman speed. Each action undermines trust, skews metrics, adds fraud losses and bloats operational overheads like KYC costs and manual reviews.

How to Detect Bots and Bot Traffic

Bot detection often starts with spotting the subtle but consistent signs of automation — clues that separate human users from scripted activity. Unlike real users, bots behave with mechanical precision or exhibit strange inconsistencies that reveal their true nature.

• Unusual behavior patterns: Bots tend to operate at inhuman speeds — completing forms in milliseconds, refreshing pages rapidly or interacting with site elements without the natural delays you’d expect from a real user.
• Device and browser inconsistencies: Device fingerprinting can uncover mismatched or spoofed configurations that indicate the presence of bots.
• Geolocation and time-based anomalies: A user logging in from New York at 3 a.m. and again from Singapore five minutes later should raise red flags. Especially if they’re completing high-risk actions.

To detect bots effectively, you need to examine the full context of every interaction. That means not just analyzing a single data point, but correlating several: how the user connects, how fast they move through a workflow, what device they’re using and how that behavior compares to the rest of your traffic.

Bot Detection Techniques

Bot detection techniques vary in their efficacy. As such, if you’re keen to protect your business from the negative consequences of bot traffic, it’s a good idea to use a combination of approaches. Let’s take a look at some of these:

• Firewalls and blacklists: Web application firewalls (WAFs) and access-control lists (ACLs) can be effective against known threats. They provide protection from session hijacking, cross-site scripting, SQL injections and the like but advanced bots can easily slip past.
• CAPTCHAs: Useful against basic bots, but not enough on their own. Sophisticated fraudsters now use CAPTCHA-solving services or machine learning to bypass this purported safety mechanism.
• Two-factor (2FA) and multi-factor authentication (MFA) : Adds an extra step for account access, protecting against bot-enabled takeovers. That said, it won’t help against bots used for fake registrations or distributed denial of service (DDoS) attacks.
• Real-time monitoring: Constant surveillance of traffic ensures you can flag suspicious behavior as it happens rather than after the damage is done.
• Device fingerprinting: Gathers non-identifiable data from a user’s hardware and software setup to detect anomalies. Ideal for spotting emulators, automation tools and reused setups.
• Device hashes: In the case of bots set up to commit multi-accounting abuse, creating and comparing device hashes will allow you to identify returning users and bots, even if they attempt to pass off as different people.

Why Is Bot Detection So Difficult?

When it comes to the detection of basic bots, adding a few rudimentary technical hurdles will work. For insWhile CAPTCHAs have been shown to reduce bot traffic by up to 88%, the sophisticated bots are a different story. Modern bots can simulate mouse movements, typing patterns, and even human-like timing, allowing them to bypass traditional bot detection tools. To counteract this, businesses tighten their defenses to catch these advanced threats — often at the cost of user experience. Legitimate customers may face repeated CAPTCHAs, blocked logins or rejected transactions, which lead to frustration, abandoned checkouts and ultimately, lost revenue and trust.

For example, referral fraud bots are designed to trigger rewards and start affiliate fraud by completing a sequence of actions mimicking human behavior that may not raise any eyebrows.

1. Sign up for affiliate programs
2. Auto-click links
3. Auto-fill forms using synthetic data
4. Use stolen cards to make deposits
5. Trigger reward payouts
6. Change device settings, then repeat

These complex, human-like actions are harder to catch and incredibly damaging. That is, of course, unless you have the right bot detection tool.

How Does SEON Help With Bot Detection

SEON is a full end-to-end risk mitigation platform that enables fraud detection and bot mitigation SEON combines machine learning, data enrichment and real-time monitoring to paint a full picture of any user interacting with your platform.

• Spot spoofed environments with device fingerprinting: Detect headless browsers, emulators and virtual machines by analyzing over 300 device parameters. Ideal for catching bots trying to spoof or rotate identities.
• Separate humans from scripts with behavioral analysis: Monitor mouse movements, typing cadence and timing to identify automated behavior, making it easier to block bots that mimic real users.
• Uncover hidden threats with IP & network intelligence: Flag connections using proxy and VPN and compare IP geolocation with user-submitted information to catch inconsistencies and expose coordinated bot activity early.
• Catch high-speed automation with velocity rules: Detect unnatural activity spikes, like mass account creation or repeated logins, by tracking the speed and frequency of user actions in real time.

By layering these capabilities, SEON gives you a proactive, adaptable defense against both basic and sophisticated bot threats — catching them early, and acting before they harm your business.

FAQs for Bot Detection

Sources

•  Imperva: 2025 Bad Bod Report