How to Block Bots and Stop Bot Attacks on Your Website, Apps, & APIs

Bots represent half of all web traffic. But only 2.8% of websites were fully protected against bot attacks in 2025, down from 8.4% the year before. Meanwhile, AI bot traffic has quadrupled, with LLM crawlers alone generating nearly 1.7 billion requests in a single month (Datadome Global Bot Security Report). The gap between threat and readiness has never been wider.

We wrote this guide to help you close it. Below, we walk through what bot protection actually means, the attack types you need to defend against, and the specific techniques that work (and which ones don’t) to block bots across your website, mobile app, and APIs.

What is bot protection?

Bot protection is the set of tools, practices, and policies that identify, manage, and block malicious automated traffic. It covers websites, mobile apps, and API endpoints. A strong bot protection strategy separates legitimate automation (search engine crawlers, uptime monitors, partner integrations) from harmful bots that scrape content, stuff credentials, commit fraud, or overwhelm infrastructure.

The scale of the problem is severe. DataDome tested nearly 17,000 websites across 22 industries and found that over 61% were fully unprotected against simple bot attacks. That means the majority of businesses online have zero effective defense against even basic automated attacks.

Bot protection is no longer optional, every business with a web presence needs a strategy for managing automated traffic.

What are bad bots?

Internet robots—or just “bots”—are automated software programs that are designed to perform relatively simple, repetitive actions over the internet. A key characteristic is that bots can perform tasks at a much faster speed than humans can, and a bot can operate 24/7 with no need for breaks or rest.

There are both good and bad bots. A good bot is typically owned by a legitimate company (e.g. Google or Facebook) and won’t hide its identity as a bot. Good bots follow the rules and policies of your website’s robots.txt file. A bad bot, on the other hand, might try to disguise itself as a human to cause all sorts of problems.

The line between “good” and “bad” bots is blurring. A Google crawler that indexes your site for search results is clearly helpful. A scraper stealing your pricing data is clearly harmful. But with AI agents now operating autonomously, the threat landscape has evolved. Malicious actors can build agents that appear legitimate—starting as a shopping assistant, for example, but programmed to exploit vulnerabilities when the opportunity arises. The question is no longer just what category a bot or AI agent falls into when it arrives. It’s whether that agent was designed with malicious intent from the start—and whether your defenses can tell the difference.

What are the most common bot attack types?

Below are nine categories of bot attacks that target businesses most frequently. Understanding them is the first step toward building the right defense.

1. Credential stuffing and account takeover

Credential stuffing bots take lists of stolen usernames and passwords from data breaches and test them against login pages on a massive scale. Because many users reuse passwords across sites, even a small success rate yields thousands of compromised accounts. DataDome’s 2025 Global Bot Security Report found that 23% of AI bot traffic touched login pages, making account takeover one of the fastest-growing attack vectors.

2. Web scraping and data harvesting

Scraping bots extract proprietary content (product listings, pricing, reviews, articles) and feed it to competitors or resell it. For businesses that rely on original content or competitive pricing, scraping can erase a market advantage overnight. Scraping bots also feed real-time competitor price intelligence tools, meaning a rival can see your pricing and inventory the moment you update them.

3. Layer 7 DDoS attacks

Unlike network-layer DDoS attacks that flood bandwidth, Layer 7 (application-layer) attacks send legitimate-looking HTTP requests designed to overwhelm your web server, API, or database. Each individual request appears normal, making these attacks significantly harder to detect and filter.

4. Scalper and hoarder bots

Common in e-commerce and ticketing, scalper and hoarder bots snap up limited-availability inventory (concert tickets, sneaker drops, product restocks) faster than any human can. Legitimate customers get shut out, and items reappear on resale markets at inflated prices.

5. Spam and content abuse bots

These bots flood forms, comment sections, and review platforms with spam. They pollute data, damage brand credibility, and create moderation headaches that drain internal resources.

6. Payment fraud and card-testing bots

Card-testing bots use stolen credit card numbers and run small transactions against your checkout to verify which cards are active. Once validated, those cards are used for payment fraud. Each failed transaction still carries processing fees and chargeback risk. The FBI’s IC3 reported $16.6 billion in cybercrime losses in 2024, with cyber-enabled fraud making up 83% of all reported losses.

7. API abuse bots

APIs are the connective tissue of modern applications, and attackers know it. DataDome’s 2025 Global Bot Security Report shows that 64% of AI bot traffic targeted forms and 5% reached checkout flows. These bots exploit API business logic: manipulating pricing endpoints, extracting user data, or automating unauthorized actions that a WAF would never catch.

8. Vulnerability scanning bots

Automated scanners continuously probe websites and applications for known vulnerabilities, including outdated software, misconfigured servers, exposed admin panels. When they find a weakness, it gets sold or exploited for data theft, malware injection, or ransomware deployment.

9. AI-enhanced bots

This is the emerging frontier. AI-enhanced bots use machine learning to mimic human behavior, bypass CAPTCHAs, rotate fingerprints, and adapt tactics in real time. The 2025 Global Bot Security Report found that advanced anti-fingerprinting bots were blocked by only ~7% of targets, leaving most organizations highly vulnerable. These bots don’t follow scripts; they make decisions. Traditional defenses built for static automation cannot keep pace.

How do bad bots impact your business?

Bad bots are dangerous because they are specifically and carefully designed to perform malicious attacks, including brute force attacks, credential stuffing attacks, web scraping, and even large-scale DDoS attacks. Bot attacks can impact your business in many ways, including but not limited to:

Stealing your sensitive data

Content scraper bots steal and reuse your content without your permission. They can also steal sensitive user data from your database if they gain access to it, which might expose you to legal penalties and impact your reputation in the long term. Advanced bots can even harvest your users’ credit card information if it is not properly protected.

Slowing down your site speed

Bot activities on your site will put extra strain on your server’s resources, impacting performance and slowing down your site. Slow page speed might drive your visitors away and affect your site’s SEO performance.

Spamming your site with fraudulent links

Spambots can spam your forms, comment sections, and other areas on your website or platform that allow user-generated inputs. They often leave links to fraudulent/scam websites on your platform, which can negatively impact your business’s reputation and result in your site getting penalized by Google.

Skewing your analytics and costs

Bots disrupt your site’s overall analytics and might affect the cost of your advertising. Ad publishers might charge you a lot more for ad space because they assume you have increased traffic, even though it’s coming from bots. On the other hand, if you are a publisher and you don’t stop bad bots from reaching your site, your reputation can be damaged if your bot traffic reaches your advertisers.

Ruining your competitive advantage

The harsh truth is, fraudsters can steal your pricing data and sell it to competitors, or they may work for your competitors directly. Either way, you lose your competitive advantage. This threat is especially acute in price-sensitive industries like ticketing, travel, and hospitality, where a few dollars can determine who wins the sale.

Here’s how it works: Bad bots scrape your pricing data. Your competitor buys the data, then undercuts your prices, eliminating your competitive edge.

How to detect bot traffic on your website

You can’t block what you can’t see. Before choosing a bot mitigation strategy, you need to understand how much of your traffic is automated and how sophisticated those bots are.

The four levels of bot sophistication

Why is monitoring website traffic essential?

Most businesses don’t discover they have a bot problem until the damage is already visible: Inflated cloud bills, corrupted analytics, or a wave of account takeover complaints from customers. That’s why continuous traffic monitoring is essential, not optional.

Tools like Google Analytics, server access logs, and dedicated bot management dashboards each reveal different pieces of the picture. Google Analytics shows behavioral anomalies (bounce rates, session duration, geographic spikes). Server logs expose raw request volumes, user-agent strings, and endpoint targeting patterns. And a bot management dashboard like DataDome’s gives you real-time classification of every request with the context to act on it immediately.

What bot activity signs should I look out for?

Several patterns in your traffic data point to bot activity. Watch for these across Google Analytics, server logs, and your CDN dashboard.

• Unusual login spikes. A sudden surge of login attempts (especially failed ones) often signals a credential stuffing campaign. This is especially concerning outside normal business hours.
• Abnormal page view patterns. Bots visit pages in sequences that real users don’t: hitting every product page in order, visiting hundreds of pages in seconds, or accessing pages with no inbound links.
• Unexpected geographic clusters. A traffic spike from a region where you have no customers or marketing activity is a common indicator of botnet activity.
• Session anomalies. Zero-second sessions, visits with no mouse movement, or sessions that skip directly to checkout without browsing are all behavioral red flags.
• API traffic irregularities. A disproportionate volume of requests hitting specific API endpoints (pricing, login, checkout) compared to normal user flows is a strong signal of API abuse.

How to stop bot attacks: Techniques and best practices

There is no single tool that solves the bot problem. Effective protection requires a layered strategy and an honest understanding of where each technique falls short.

Basic (legacy) techniques to stop bots

These were the foundation of early bot defense. They still have a role, but none is effective on its own against modern bots.

IP blacklisting and geofencing

IP blacklisting and geofencing mean blocking traffic from known malicious IP addresses or entire geographic regions, which catches only the least sophisticated bots.

Why it’s not enough: Modern bots rotate across millions of residential IPs using botnets and proxy pools. IP blacklisting creates false positives for legitimate users behind shared IPs, VPNs, and corporate networks. Segpay experienced this firsthand: They did extensive IP blacklisting but found it ineffective because attackers easily switched IPs, and the risk of blocking legitimate users was too high.

User-agent analysis and robots.txt enforcement

Your robots.txt file tells bots which pages they should and shouldn’t crawl. User-agent filtering blocks requests from known bot signatures.

Why it’s not enough: Only the most unsophisticated bots respect robots.txt. It’s a directive, not a wall. Any moderately advanced bot spoofs its user-agent string to appear as a legitimate browser. While 88.9% of robots.txt files in DataDome’s dataset now explicitly block GPTBot, that signal alone doesn’t stop unauthorized crawling.

Rate limiting and throttling

Rate limiting caps the number of requests a single IP or session can make within a time window. It slows down brute-force attacks and prevents simple scripts from overwhelming your server.

Why it’s not enough: Sophisticated bot operators distribute requests across thousands of IPs, staying under the threshold on each one. Rate limiting also hurts legitimate users during traffic spikes like flash sales or product launches. It slows bots down. It does not stop them.

Web application firewalls (WAF)

WAFs filter incoming traffic based on predefined rules, blocking requests that match known attack patterns like SQL injection or cross-site scripting. Every security stack should include one.

Why a WAF alone is not enough: WAFs are rule-based and static. They require constant manual maintenance as attack patterns evolve. Modern bots send perfectly valid HTTP traffic that matches no known rule, because they’re not exploiting a vulnerability. They’re exploiting your business logic.

Intermediate techniques to stop bots

CAPTCHA challenges and alternatives

CAPTCHAs ask users to complete a task that should be easy for humans and hard for bots—selecting images of traffic lights, typing distorted characters, or checking a box.

Why traditional CAPTCHAs are effectively obsolete: In 2024, researchers at ETH Zurich demonstrated that an AI model (YOLO) could bypass Google’s reCAPTCHAv2 with a 100% success rate after being trained on just 14,000 labeled images (arxiv.org). Beyond AI bypasses, commercial CAPTCHA-solving services defeat challenges in under a second for fractions of a cent. CAPTCHAs now frustrate real users more than they stop bots.

Modern bot management platforms like DataDome replace traditional CAPTCHAs with device verification. DataDome’s Device Check assesses behavior and context without adding friction, presenting visible challenges to less than 0.01% of requests.

Device fingerprinting

Device fingerprinting collects attributes from a visitor’s browser and device (screen resolution, installed fonts, WebGL renderer, timezone, language settings) to create a unique identifier. Even if a bot rotates its IP address, its fingerprint stays consistent.

Advanced bot management solutions go further. DataDome’s device fingerprinting analyzes over 250 signals per request, including behavioral micro-signals that no headless browser can fully replicate. This depth separates basic fingerprinting (which sophisticated bots can spoof) from fingerprinting that actually catches them.

Honeypots

Honeypots are hidden elements, like invisible form fields, fake links, and decoy pages that real users never interact with but bots do. Any entity that triggers a honeypot immediately reveals itself as automated.

Honeypots catch careless bots at near-zero cost. But they do nothing against bots sophisticated enough to render JavaScript and interact only with visible elements. They’re a useful supplement, not a standalone defense.

Advanced bot management techniques

These techniques define modern bot protection. No single one is sufficient alone, but together they create defense-in-depth across the full threat spectrum.

Behavioral analysis (AI/ML-based)

Behavioral analysis uses machine learning to model what normal human interaction looks like (mouse movements, scroll patterns, keystroke dynamics, navigation sequences) and flags sessions that deviate. Unlike static rules, behavioral models adapt as bot tactics evolve.

This is the core of what makes advanced bot management different from legacy tools. A behavioral engine doesn’t need to recognize a bot’s signature. It recognizes that the behavior isn’t human.

Real-time threat intelligence

Real-time threat intelligence aggregates data from billions of requests across all protected sites to identify emerging attack patterns. When a new bot technique appears on one website, every other protected site benefits from updated detection immediately.

DataDome processes over 5 trillion signals per day across its customer network. A new attack vector identified on a retail site in Europe triggers updated protection for a financial services company in North America within milliseconds.

Multi-layered verification

No single detection method catches every bot. Multi-layered verification combines fingerprinting, behavioral analysis, invisible device verification, and reputation scoring applied in sequence. If a bot evades one layer, it hits the next.

API-specific bot protection

APIs present unique challenges. There’s no browser to fingerprint, no mouse to track, no page to render. API-specific protection analyzes request patterns, payload structures, authentication behavior, and session context to identify automated abuse. Many security stacks protect web and mobile, but leave APIs completely exposed.

Dynamic and risk-based challenges

Instead of applying the same challenge to every visitor, dynamic challenges adjust based on risk score. A low-risk session sees zero friction. A suspicious session faces an invisible challenge. A high-risk session gets visible verification. This minimizes false positives while maximizing detection.

Custom rules engine

Every business has unique traffic patterns and attack surfaces. A custom rules engine lets security teams create specific protections: Rate limits on particular endpoints, allowlists for partner bots, and targeted blocks based on business logic. All without modifying application code.

Mitigation responses: What to do when you detect a bot

Blocking isn’t always the best response. Sophisticated bot operators monitor success rates. If requests suddenly start failing, they know they’ve been detected and change tactics immediately. A smarter approach uses varied responses.

• Blocking. Deny the request outright. Use for clearly malicious traffic (DDoS, known attack signatures).
• Challenging. Present a verification step (invisible or visible) that forces the bot to prove it’s human. Useful for uncertain traffic.
• Throttling. Slow down requests without blocking them. The bot operator may not realize they’ve been detected.
• Honey trapping. Serve the bot fake data, like wrong prices, fake inventory, decoy content. The bot thinks it’s succeeding while your real data stays protected.

Why bot protection must keep pace with AI

Bot defense is not a set-it-and-forget-it project. The threat landscape evolves continuously, and protection that worked six months ago may already have gaps. When evaluating vendors, focus on these criteria.

AI bots don’t just follow scripts. They analyze defenses, identify weaknesses, and adjust in real time. They use residential proxies, manipulate TLS fingerprints, and mimic human behavior with enough fidelity to pass traditional detection. At the same time, the barrier to entry for attackers has dropped. Bots-as-a-Service platforms and open-source tools mean launching a sophisticated attack no longer requires deep technical expertise.

The 2025 Global Bot Security Report documents this shift: AI bot traffic quadrupled between January and August across DataDome’s customer base, rising from 2.6% of verified bot traffic to over 10.1%. The old “bot or not?” model is no longer sufficient. Effective protection now requires understanding intent: What an automated visitor is trying to do, not just whether it’s a bot.

Your protection needs to update as fast as threats do. Static rules and manual tuning can’t keep pace. Effective bot management requires AI models that learn from billions of requests, a threat research team actively monitoring new techniques, and real-time updates that deploy across your infrastructure the moment a new threat emerges.

How to choose the right bot management solution

Not all bot management solutions deliver the same protection. When evaluating vendors, focus on these criteria.

Start protecting your website from bots with DataDome

Investing in the right bot protection solution is the best approach for blocking and mitigating bots on your website, mobile app, and API. Effective bot protection will:

1. Differentiate between legitimate human users and malicious bots mimicking humans to keep false positives as low as possible.
2. Identify the source of bot traffic and its reputation to prevent false positives.
3. Utilize AI technologies to analyze each bot’s behavior and make a case-by-case decision in managing these bot activities.
4. Allow good bots to access your site to provide their benefits, according to your preferences.

With bots getting more sophisticated than ever, having the right bot management strategy to block bad bots is no longer a luxury but a necessity.

Book a demo to see how DataDome can protect your business from bots, or run a free Vulnerability Scan to test your defenses today.