What is Bot Traffic?

How Bot Traffic Works

Bots are software programs that run automated tasks over the internet. They're everywhere, accounting for roughly a quarter to almost half of all web traffic depending on which study you look at. Fraudlogix IVT Detection identifies and filters malicious bot traffic before it inflates metrics or drains ad budgets. Some are helpful. Google's crawler bot indexes websites so they show up in search results. Monitoring bots check if your site is up and running. Chat bots answer customer questions.

But a lot of bots exist for more questionable reasons. Some generate fake clicks on ads to drain competitors' budgets. Others scrape pricing data or steal content. Bad bots probe for security vulnerabilities, spam comment sections, or try millions of password combinations hoping to break into accounts.

The line between good and bad bots isn't always clear. A search engine crawler is fine, but someone deploying 50 bots to scrape your entire product catalog and pricing isn't. Some bots identify themselves properly. Others try hard to look human by rotating IPs, mimicking mouse movements, and varying their behavior to avoid detection.

Modern bots have gotten sophisticated. Simple ones just send HTTP requests and follow links mechanically. Advanced bots run full browsers, execute JavaScript, handle cookies, and simulate realistic user behavior. The most sophisticated bots use machine learning to adapt their patterns based on what gets blocked.

Good Bots vs Bad Bots

Not all bots are created equal. Understanding the difference helps you figure out what to block and what to allow.

Good Bots (Legitimate Automation)

Search engine crawlers like Googlebot and Bingbot index your content so people can find you. Social media bots from Facebook and Twitter grab previews when someone shares your links. Monitoring services check if your site is online and performing well. Feed readers aggregate your blog posts or news updates.

These bots generally follow the rules. They identify themselves through user agents, respect robots.txt files, and don't overwhelm servers with requests. Most website owners want these bots visiting because they provide value, whether that's search visibility or uptime monitoring.

Bad Bots (Malicious or Fraudulent)

Click fraud bots generate fake clicks on pay-per-click ads, either to drain competitor budgets or inflate publisher earnings. Scraper bots steal content, pricing data, or email addresses at scale. Credential stuffing bots try stolen username/password pairs across multiple sites hoping for matches.

DDoS bots flood sites with traffic to knock them offline. Spam bots post junk in comment sections or forums. Vulnerability scanners probe for security weaknesses to exploit. Inventory hoarding bots buy up concert tickets or limited products to resell at markup.

For advertisers specifically, bot traffic means paying for impressions or clicks that will never convert. Someone running display ads might see great impression numbers but no actual sales because half the "views" came from bots loading pages that no human ever saw.

Gray Area Bots

Some bots fall in between. SEO tools that crawl competitor sites gather competitive intelligence but might violate terms of service. Price comparison bots help consumers but hurt retailers trying to prevent price matching. Archive bots preserve web history but ignore content removal requests.

How to Detect Bot Traffic

Bot detection requires looking at multiple signals because no single indicator is foolproof. Good bots are easy to spot. Bad bots try to blend in.

IP Analysis and Risk Scoring

Look at where traffic comes from. Data center IPs almost always indicate bots since real users browse from residential internet connections. IP Risk Scoring evaluates each connection in real-time, identifying data center hosting, proxy usage, and IPs with fraud history. This catches the majority of bot traffic before it costs you money.

Behavioral Analysis

Watch how visitors interact. Real people move their mouse, scroll at human speeds, and navigate somewhat unpredictably. Bots often show perfect timing intervals, zero mouse movement, impossibly fast page loads, or navigation patterns that violate basic physics (like clicking multiple buttons simultaneously).

Look for other behavioral red flags. Does traffic arrive at 3am local time with perfect consistency? Do visitors navigate directly to obscure URLs without following any links? Are session durations suspiciously uniform?

User Agent and Browser Fingerprinting

Check user agents for known bot signatures. Simple bots often declare themselves or use outdated browser strings. But sophisticated bots fake legitimate user agents, so you need deeper analysis. Browser fingerprinting examines fonts, plugins, screen resolution, timezone, and dozens of other attributes. Bots usually have subtle inconsistencies that don't match real devices.

JavaScript and Cookie Testing

Simple bots don't execute JavaScript or accept cookies. If a visitor doesn't run your JavaScript tracking or rejects all cookies, it's likely automated. More advanced bots handle these, but you can look for timing inconsistencies in JavaScript execution or missing browser APIs that real browsers always have.

Traffic Pattern Analysis

Look at aggregate patterns rather than individual sessions. Is traffic arriving in perfect waves? Are conversion rates suspiciously low despite high engagement? Do you see huge spikes from specific geographic regions or ISPs that don't match your normal audience?

How to Prevent Bot Traffic

Stopping bot traffic requires multiple layers of defense. Bots that bypass one method often get caught by another.

1. Pre-Bid IP Blocklist

Block known bot sources before they cost money. Pre-Bid IP Blocklists filter data centers, hosting providers, and identified bot networks at the auction level. This prevents bot impressions from entering your campaigns, stopping the problem at its source. For programmatic advertising, pre-bid blocking is the most cost-effective bot prevention.

2. Real-Time IP Risk Scoring

Evaluate every connection as it happens. IP Risk Score analyzes hundreds of factors in milliseconds to determine if an IP is likely to be a bot. It catches new bot operations that haven't been catalogued yet, identifying suspicious patterns even when individual IPs are unknown.

3. Comprehensive IVT Detection

Deploy Programmatic IVT Detection that combines IP analysis, behavioral monitoring, and device fingerprinting. Pixel-based detection identifies bots through interaction patterns, missing browser features, and technical signatures that static lists miss. This catches sophisticated bots that evade simpler methods.

4. Rate Limiting and Traffic Shaping

Limit how many requests a single IP or user can make in a given timeframe. Real users don't load 50 pages per second. Aggressive rate limiting stops bot attacks but can also frustrate legitimate users if set too strictly, so calibrate based on your normal traffic patterns.

5. CAPTCHA and Challenge-Response

Use CAPTCHAs or similar challenges for suspicious traffic. Modern versions are less annoying than old "type these distorted letters" tests. Invisible CAPTCHAs analyze behavior and only challenge users who seem automated. This catches bots that bypass other detection but adds friction for legitimate users.

6. Allow Good Bots, Block Bad Bots

Maintain separate rules for known good bots. You want Google and Bing crawling your site for SEO. Create allowlists for legitimate bot user agents while blocking or challenging everything else. The IAB maintains a standard list of approved bots that most ad verification tools reference.

7. Monitor and Adapt

Bot tactics evolve constantly. What works this month might not work next month. Regularly review your bot traffic patterns, adjust detection rules, and update blocklists. Use analytics to spot new bot patterns before they cause significant damage.

Frequently Asked Questions