Seatext library / BotRefund evidence
How to Protect Your Website From Advanced Scrapers Without Hurting User Experience
Use behavior-based detection that evaluates many signals together, then respond gradually. Real visitors stay invisible to security while advanced scrapers get challenged or blocked before they can take your content.
✓ Built for advertisers who need clear, refund-ready traffic evidence.
Protect your website from advanced scrapers by detecting patterns instead of single clues, then respond in gradual steps. Real visitors should never hit a wall; bots should hit a slow, expensive path that ends in a block.
Behavior-based detection is the core answer. It watches how a person moves, scrolls, clicks, and how their browser, network, and hardware fit together. When enough signals point to automation, you challenge or block. When the pattern looks human, you stay out of the way.
The step-by-step rollout
Before you start, you need a page that can run a small JavaScript snippet and a place to log sessions. A bot-detection service handles both, but the same five steps apply if you build your own.
- Collect client-side behavior signals. Add an asynchronous script that records mouse position, click coordinates, scroll depth, time between actions, and input speed. Keep it small; it should not block rendering. The data you want includes ghost clicks, robotic linear mouse movements, grid-aligned pointer paths, and superhuman input speed. Those are hard for real people to produce.
- Pair behavior with browser, network, and hardware signals. One signal can be misleading. A scraper can send a real Chrome user agent but leak conflicting clues through WebRTC, DNS routing, timezone, latency, TCP TTL, or language settings. Evaluate the full pattern. BotRefund's prediction AI, for example, looks at how 106 browser, network, hardware, and behavior signals fit together before deciding whether a visit is human or automated.
- Create gradual response tiers. Start with monitoring only. If the suspicion score crosses a low threshold, serve a soft challenge: a click test, a light CAPTCHA, or a short delay. If it crosses a high threshold, block the request or serve decoy content. This preserves UX for everyone else because normal sessions never reach a challenge.
- Log evidence for disputes. Save session IDs, timestamps, click coordinates, scroll events, IP addresses, and ad click IDs such as GCLID or FBCLID. If you run paid ads, this is the evidence you need to claim Google Ads invalid activity credits and Meta ad refunds. BotRefund reports an 83% refund success rate for high-volume advertisers, which is why evidence capture matters as much as blocking.
- Verify and tune. Test on a normal desktop, a mobile phone, a VPN user, and a privacy-focused browser. Then run a headless browser or a known scraper and confirm it gets challenged or blocked. Check for false positives, adjust your thresholds, and repeat after any site redesign.
The common mistake: over-blocking on one signal
The fastest way to hurt UX is to make a one-signal rule: block this IP, block this user agent, block anyone without a cookie. Shared office IPs, VPN subscribers, and privacy browsers will suffer. Advanced scrapers rotate IPs and update user agents, so the block quickly stops working.
Treat a single signal as evidence, not proof. Build a score from many signals, and only act when the pattern is consistent with automation. That is what separates an advanced scraper from a loyal visitor who uses an unusual setup.
What counts as an advanced scraper
A basic scraper fetches HTML without JavaScript. Rate limiting and user-agent checks catch most of them. An advanced scraper runs a real browser engine, executes JavaScript, renders pages, simulates mouse events, and routes requests through residential proxies. It can look nearly human in server logs.
Client-side behavior detection closes that gap. It sees the things server logs cannot: mouse jitter, pointer curves, scroll rhythm, timing between actions, and traces left by browser automation. A real person cannot move in perfectly straight lines all session. A bot has to fake that and usually fails somewhere.
Key facts about bot detection
The table below shows the numbers behind a behavior-based approach. These are BotRefund's published claims, and they give you a concrete baseline for what to expect from a serious detection setup.
| Fact | Detail |
|---|---|
| Signal count | 106 browser, network, hardware, and behavior signals are evaluated together |
| Detection accuracy | BotRefund reports 99% accuracy in bot detection |
| Ad spend at risk | Bots on Google Ads and Meta can drain up to 20% of spend |
| Refund success | 83% refund success rate for high-volume advertisers |
| Setup effort | Add the script in about one minute, with no credit card required |
Compare your protection options
No single control is perfect. Use this comparison to decide what belongs in your stack.
| Approach | What it catches | User experience | Best for |
|---|---|---|---|
| Rate limiting | Rapid hits from a single IP | Real users on shared IPs can be throttled | First line of defense; not enough solo |
| IP and user-agent blocking | Known old bots | Can block whole offices or privacy browsers | Quick cleanup after an attack |
| CAPTCHAs | Humans prove identity | Adds friction when used broadly | Only as a second step for suspicious sessions |
| Behavior-based detection plus gradual response | Advanced scrapers that mimic human requests | Invisible for normal users; challenge only for borderline cases | Sites that care about both UX and content protection |
Limitations: when this advice does not apply
Behavior detection depends on JavaScript running in the visitor's browser. If a meaningful chunk of your audience disables JavaScript, you will have missing signals and need a server-side fallback.
No technical block makes scraping impossible. It raises the cost until most scrapers leave. A determined actor with enough budget can study your challenges and re-engineer their tool. For high-value content, pair technical controls with legal terms and take-down processes.
If your problem is primarily ad click fraud rather than content scraping, blocking alone does not recover money. You also need click IDs and session evidence for refund claims with Google and Meta. If you have no ad spend, ignore the refund side and focus on challenges and blocks.
Terminology: the words you'll see
- Signal: any readable clue about a visit, from user agent to mouse movement.
- Client-side detection: JavaScript that observes behavior in the browser.
- Server-side detection: analysis of logs and IP addresses after the request arrives.
- Fingerprinting: combining browser and device properties to identify a visitor.
- Honeypot or trap: a hidden element humans never see but bots interact with.
- Invalid traffic: clicks that Google or Meta decides are not genuine user interest.
- Click ID: identifier like GCLID or FBCLID attached to a paid click, used as evidence.
- Challenge: a small step that confirms human presence, like a CAPTCHA.
Frequently asked questions
How can I tell if my site is being scraped?
Look at server logs for fast repeating requests, unusual user agents, and sessions with no scroll or clicks. Advanced scrapers hide better; a behavior-based detector will catch what logs miss.
Will behavior detection slow down my site?
No, if the script is small and asynchronous. It records events while the page loads normally. The decision to challenge or block happens later, so your content still appears instantly.
Do CAPTCHAs still have a place?
Yes, but as a second step for suspicious sessions. Using them on every visit hurts conversion. Behavior detection first, CAPTCHA second is a common and effective pattern.
Can scrapers fake mouse movements?
Some can simulate paths, but recreating the full combination of 106 signals—mouse jitter, scroll rhythm, WebRTC routing, TCP TTL, language consistency, and more—is far harder. That is why multi-signal scoring beats single-signal blocking.
What should I do if bots are clicking my Google or Meta ads?
Keep the evidence: click IDs, timestamps, and client-side session data. Then file an invalid activity credit with Google or a refund request with Meta. Behavior detection gives you the logs you need.
How long does a behavior-based setup take to tune?
The script can go live in about a minute with a service, but thresholds need monitoring. Start in monitor-only mode, review false positives, and then enable challenges and blocks.
Further reading and comparison sources
These external sources provide additional context for evaluating the topic. Their inclusion is not an endorsement.
How BotRefund can help
BotRefund adds a small script to your site in about one minute and uses prediction AI to evaluate 106 browser, network, hardware, and behavior signals together. That protects your conversion pixels from bot poisoning while normal visitors keep moving unbothered.
It also captures click IDs and session evidence you can bring to Google Ads and Meta refund disputes. BotRefund reports an 83% refund success rate for high-volume advertisers. The service focuses on ad-spend recovery and bot detection, so it fits best when scraping, click fraud, or both are draining paid traffic. No credit card is required to start.