Today, bots account for nearly 50% of global internet traffic. While beneficial bots, like search engine crawlers, play a crucial role in helping businesses reach audiences, a substantial portion of bots operate with harmful intent. Malicious bots can steal content, execute credential stuffing attacks, overwhelm web servers, distort analytics, and more. Without proactive risk intelligence systems in place, businesses face serious threats, from compromised data security to degraded user experience.
In fact an in-depth report by Imperva ("2024 Bad Bot Report") had some interesting insights on how bot attacks target crucial APIs that handle identity verification during login and then subsequently conduct account takeovers. Account takeover attacks targeting APIs accounted for 44% of all ATO attacks recorded.
This is one small example of why bot detection techniques need to be prioritised urgently. Let's understand more.
Bot detection: The basics
Bot detection is the process of understanding whether the user accessing a website is a real human or an automated bot.
This detection relies on sophisticated techniques that analyze various indicators—such as browser attributes, mouse movements, request patterns, and IP reputation—to detect unusual behaviours that suggest bot activity. And when we say unusual, we mean - decidedly not human. For example, this image from Cloud Blog shows how a human operating a mouse will never make the hard right angles that an automated bot will.
The most advanced systems leverage machine learning to improve detection accuracy, continually adapting to recognize and flag new bot behaviors.
Unmasking the malicious intents of bots
While legitimate bots serve positive functions, such as content indexing by search engines and price monitoring by comparison sites, malicious entities will deploy bots to exploit business vulnerabilities. Here are some infamous methods:
1. Credential stuffing attacks
Bots attempt thousands of username and password combinations to gain unauthorized access to accounts. Successful attacks can lead to severe data theft, unauthorized transactions, and reputational harm to the business. All of these major brands suffered just in the last one year losing billions in revenue. (Source: Kaspersky)
2. Data scraping
Bots swiftly gather sensitive data, like pricing, content, and proprietary information, which can lead to competitive disadvantages, intellectual property theft, and unauthorized data redistribution. This activity disrupts revenue and devalues a brand’s unique offerings.
3. Publicly available tools
There are easily available tools online that fraudsters or entities that want to cause large scale damage may use. Tools like Selenium, Puppeteer are easy to access, affordable and can easily execute JavaScript in the browser, enabling bots to scrape dynamic content.
4. Distributed Denial of Service (DDoS) attacks
Bots can overwhelm a server with excessive requests, slowing down or completely crashing a website. These attacks lead to service interruptions, financial loss, and damaged customer trust.
5. Spam and fake account creation
Bots flood websites with spam or create fake accounts, polluting the user experience and skewing metrics. Fake accounts are often used to post irrelevant content, damaging a website’s credibility and SEO performance.
Related read: New Account Fraud: Definition, Types and Prevention Measures
6. Click and Ad Fraud
Bots can inflate ad clicks or views, depleting advertising budgets and reducing campaign ROI. This fraudulent activity distorts marketing data, wastes resources, and erodes trust between advertisers and platforms.
Why should you care about bad bots?
Since we started this blog by saying there are good bots and bad bots, we know all industries that have a degree of digital dependence, will have a degree of bot activity. But what's worrying is the ratio of bad to good. Imperva has another great insight the share of bad bot traffic by industry!
Uncontrolled bot traffic can have far-reaching consequences. From inflating your infrastructure costs to damaging brand reputation, bot-driven activities pose risks across multiple facets of an organization. Here are some of those aforementioned consequences:
1. Cost efficiency and resource optimization
Blocking malicious bots reduces bandwidth and infrastructure expenses, optimizing IT budgets and freeing resources for business growth. It also lessens the load on customer support by minimizing bot-driven inquiries, allowing teams to focus on real customer needs.
2. Enhanced user experience and brand protection
High bot traffic can slow down or crash websites, frustrating users and eroding trust. By filtering out malicious bots, your website remains responsive and reliable, protecting brand reputation and delivering a positive experience for legitimate users.
3. Data integrity and informed decision-making
Bots can skew website analytics, leading to inaccurate metrics that misguide strategic decisions. Effective detection ensures that only genuine user interactions are captured, improving data accuracy and supporting well-informed business strategies.
4. Competitive advantage and intellectual property protection
By blocking bots that scrape pricing, content, and proprietary information, you preserve your competitive edge and prevent unauthorized use of valuable business data.
5. Regulatory compliance and security assurance
For businesses handling sensitive data, bot detection helps prevent unauthorized access and reinforces compliance with privacy laws like GDPR and CCPA, building trust with customers and regulators alike.
Bot detection: The most effective strategies
With bots evolving, it’s essential to use a combination of interaction-based verification, behavioral analysis, and technical safeguards. Here are some of the most effective bot detection strategies:
1. Interaction-Based Verification
Adding elements like pop-ups, CAPTCHAs, and rendering challenges that require user interactions can help filter out bots. Many basic bots lack the capability to navigate these obstacles, making this an effective first line of defense.
2. Behavioral Analysis and Machine Learning
By monitoring natural user behaviors—such as scrolling patterns, mouse movements, and click timing—behavioral analysis can help identify bots based on abnormal interactions. Machine learning further enhances this by analyzing large datasets, recognizing subtle patterns, and adapting to new bot behaviors over time.
Related read: Behavioral Biometrics: Analyzing How a Fraudster Acts
3. Web Application Firewalls (WAFs)
WAFs add an additional security layer by filtering out traffic based on known attack signatures. When properly tuned, WAFs can block a wide range of bot attacks, reducing the overall bot traffic load on your systems.
4. Multi-Factor Authentication (MFA) and IP Blocklists
While not direct bot mitigation, MFA helps protect against credential-stuffing bots by requiring user verification for account access. Combined with IP blocklists for known bot sources, this strengthens account security and deters unauthorized access.
Bureau: Your partner for efficient bot detection
At Bureau, we deploy a multi-layered approach to detect bot traffic using:
- Behavioral Analysis: By tracking user interactions—such as clicks, scrolling, and mouse movements—Bureau can identify patterns commonly associated with automated behavior. This approach enables us to distinguish bots from real users based on interaction style.
- Bureau Fingerprint: Bureau uses advanced fingerprinting to analyze device and browser characteristics for anomalies. By monitoring unique Device IDs, user agents, IP addresses, and browser headers, our system detects inconsistencies that are indicative of bot behavior.
- Honeypots: Hidden elements, or “honeypots,” are embedded within the HTML structure. Legitimate users won't interact with these traps, but bots will, allowing Bureau to quickly identify automated interactions without impacting user experience.
- JavaScript Computations: Bureau implements complex JavaScript computations that require human-like responses to complete. Automated scripts struggle with these tasks, allowing our system to filter out bots that lack the capability to handle advanced computations
Bureau Bot Detection technology in action -
Set up a call with us to see a live demo of our solutions in action.
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This blog was written by Sathyan B. Currently Senior Frontend Developer at Bureau, he is passionate about advancing the fraud prevention domain and specializes in architecting and delivering robust, end-to-end web applications. Connect to Sathyan here.
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