Bot Detection
A bot hits your signup form, creates a fake account, and starts scraping your product, all within a few seconds. It happens hundreds of times a day from different IPs, different user agents, and different email addresses, not one of them a customer, while the proprietor of this enterprise sleeps soundly through the entire performance. You're playing whack-a-mole against an opponent with infinite moles. And not every bot deserves the mallet.
You probably want well-behaved bots spending time on your site nowadays, like AI agents and LLM assistants. But traditional bot detection swings at everything that moves, and its false positives are as likely to hit a good bot (or a real customer) as a bad one.
Dregs does it differently, combining bot detection with behavioral analysis to stop the abusive bots while waving the well-behaved ones through.
The Bot Problem
Bad bots are everywhere. They create fake accounts, scrape your content, test stolen credentials, spam your forms, inflate your metrics, and hammer your APIs at four in the morning. The crude ones announce themselves in the user agent. The ones that do real damage are better turned out — headless browsers that render JavaScript, rotate IPs, and imitate a human well enough to get through the door.
The bot landscape keeps getting worse, not better. Off-the-shelf headless browser frameworks are free and thoroughly documented. CAPTCHA-solving services cost pennies. Residential proxy networks have reduced IP-based detection to decoration.
The conventional defenses aren't keeping up.
| The Traditional Defense | Why It Often Fails |
|---|---|
| CAPTCHAs | Solver farms clear them for a fraction of a cent while your customers squint at traffic lights. The bots pay a rounding error; the humans pay in patience. |
| Rate limiting | Distributed networks spread the work over thousands of IPs, each one sitting politely under every threshold. Volume caps catch the clumsy operations and merely inconvenience the rest. |
| WAFs | Signature-based rules know only the bots already caught elsewhere, never the one visiting you now. Anything newly built or lightly modified walks straight past. |
| User-agent blocking | The user agent is a self-reported claim, and self-reported claims are trivially spoofed. Any script can present itself as the newest Chrome, and the well-built ones always do. |
| Honeypots | Hidden form fields catch naive crawlers that fill in everything they see. Anything better built inspects the page the way a browser renders it and steps around the trap without pausing. |
Each defense catches some bots, some of the time. A determined operator walks through all of them at once, with the unhurried confidence of somebody who did the same to four hundred sites this month. Besides, even if you could identify every bot, how do you block the bad ones without impeding the good ones?
You need behavior-driven detection that looks deeper than surface-level signals.
What Unwanted Bot Traffic Costs Your Business
Bot traffic isn't just a nuisance. It degrades your product, wastes your money, and undermines your security posture.
Resource hogging
Bot traffic consumes compute, bandwidth, and API capacity you're paying for. Scrapers spike your cloud bill and degrade performance for real users, while your auto-scaling obligingly buys more capacity so the scraping can proceed at full speed.Data pollution
Fake signups, spam submissions, and bot-generated events contaminate your analytics. Conversion rates, activation funnels, and engagement metrics stop meaning anything when a good share of your "users" are scripts that never saw the page.Security exposure
Credential stuffing bots work through stolen username/password combinations against your login form. Content scrapers help themselves to your proprietary data. Account creation bots lay down stockpiles of fake accounts against campaigns not yet dreamed up.How Dregs Detects Bots
Dregs doesn't rely on any single signal. Its scoring pipeline analyzes every visitor from multiple angles simultaneously (device, behavior, identity, and timing), making it extremely difficult for a bot to pass as human across all dimensions at once. Scores settle moments after new activity, and each one opens into its observations.
Humanity Score
The Humanity score is the primary bot detection signal. Dregs analyzes browser fingerprint characteristics that headless browsers struggle to fake: impossible hardware profiles, missing browser APIs, inconsistent rendering behavior, and dozens of other indicators. A real browser on real hardware is hard to counterfeit; a headless one claims a graphics card and then declines to render anything with it.
Behavior Score
Bots behave differently than humans, however carefully instructed otherwise. The Behavior score catches impossibly fast page navigation, unnaturally uniform timing intervals, sessions that skip straight to high-value targets, and interaction patterns that no human would produce. Even bots with randomized delays lack the natural variance of real human behavior, the randomness itself suspiciously even.
Authenticity Score
Bots generate identity data programmatically. The Authenticity score detects auto-generated names assembled from a word list, email addresses that follow predictable formats (sequential numbers, random character strings), and identity data that doesn't add up to a real person. Accounts manufactured at volume inevitably produce patterns, and an address that counts upward is not a subtle one.
Device Fingerprinting
Headless browsers leave distinctive device fingerprints, however earnestly they claim to be ordinary Chrome. Missing plugins, screen dimensions matching no real display, absent GPU rendering capabilities, and other hardware-level signals create a fingerprint that stands out. Dregs recognizes these patterns across sessions, IPs, and user agents, catching bot traffic across multiple accounts.
Example: Catching a Credential Stuffing Bot
With Dregs, here's what it looks like when an operator points a credential stuffing campaign at your login page:
Nobody had to be woken up... the cycle finishes almost instantly, well before the bot clears its first batch of credentials. Each score opens into its observations, so you can see exactly why a session was flagged, sparing your real users the false positives.
Responding to Bot Traffic
Not all bots deserve the same response. Some you block immediately. Others you watch quietly. Dregs gives you the detection signals, plus custom rules and lists (badge rules and datasets, in Dregs terms) to decide how each is handled.
Total blocking
Terminate the session as soon as the bot is detected. Best for credential stuffing, spam bots, and other clearly malicious automation. The campaign returns nothing on the investment, and your resources are protected.
Rate limiting
Slow suspicious sessions with artificial delays and rate limits. Throughput collapses at the far end with no explanation, costing the operator time and proxy budget alike.
Silent monitoring
Watch without acting. Let the bot carry on while you record its behavior, targets, and techniques. Useful for well-behaved bots, or for automation you want on the site.
Speed matters when responding to bots. By the time a human reviews an alert, the bot has finished and gone home. Dregs webhooks let your application react near-instantly to suspicious activity, blocking or throttling the session before it causes real damage, with less manual review in the loop.
Bot traffic often manifests as credential stuffing or fake signups. Dregs detects the underlying automation regardless of what the bot is trying to do.
Stop unwanted bots before they do damage.
Dregs identifies automated traffic from the first page load. No training period, no rule tuning, no CAPTCHA tax on your real users. Stop the bad bots while allowing good ones.
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