Bot Detection

A bot hits your signup form, creates an account, and immediately scraping your product, all within a few seconds of arriving — and this happens hundreds of times a day from different IPs, different user agents, and different email addresses. You're playing whack-a-mole against an opponent with infinite moles. But nowadays, not all bots are bad!

In fact, you probably want well-behaved bots to spend time on your site, like AI agents and LLM assistants. Traditional bot detection tools are heavy-handed and imprecise, and they're just as likely to block a good bot as a bad one.

Dregs does it differently. By combining advanced bot detection with behavioral analysis, Dregs has what you need to prevent bad and abusive bots while welcoming the well-behaved bots.

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. Some are crude scripts that are easy to catch. But the ones that actually cause damage are sophisticated — headless browsers that render JavaScript, rotate IPs, and mimic human behavior just well enough to slip past your defenses.

The bot landscape keeps getting worse, not better. Off-the-shelf headless browser frameworks are free and well-documented. CAPTCHA-solving services cost pennies. Residential proxy networks make IP-based detection nearly useless.

The conventional defenses aren't keeping up.

CAPTCHAs CAPTCHA farms and AI solvers defeat them for fractions of a cent per challenge
Rate limiting Distributed bot networks use thousands of IPs, staying well under per-IP thresholds
WAFs Signature-based rules miss niche or unknown bots and sophisticated browser automation
User-agent blocking User agents are trivially spoofed, and any bot can claim to be the latest version of Chrome
Honeypots Effective against naive crawlers, but sophisticated bots avoid hidden fields and invisible links

Each of these defenses catches some bots, some of the time. But a determined bot operator can bypass all of them simultaneously, and the arms race never ends. Besides, even if you somehow identify bots with 100% accuracy, how do you block the bad ones without impeding the good ones?

You need a behavior-driven bot detection approach 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 actively undermines your security posture.

Resource hogging

Bot traffic consumes compute, bandwidth, and API capacity that you're paying for. Aggressive scrapers and stuffers can spike your cloud bill and degrade performance for real users, sometimes triggering costly auto-scaling.

Data pollution

Fake signups, spam submissions, and bot-generated events contaminate your analytics. Conversion rates, activation funnels, and engagement metrics lose meaning when a significant percentage of your "users" are scripts.

Security exposure

Credential stuffing bots test stolen username/password combinations against your login form. Content scrapers steal your proprietary data. Account creation bots build stockpiles of fake accounts for future abuse campaigns.

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.

Low Humanity score revealing headless browser fingerprint anomalies

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 has a fingerprint that is hard to convincingly replicate in automation.

Behavior score observations showing impossibly fast and uniform event timing

Behavior Score

Bots behave differently than humans, even when they try not to. 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 still lack the natural variance of real human behavior.

Low Authenticity score flagging auto-generated identity data

Authenticity Score

When bots create accounts, they generate identity data programmatically. The Authenticity score detects auto-generated names that don't follow natural naming patterns, email addresses that follow predictable formats (sequential numbers, random character strings), and identity data that doesn't add up to a real person. Bots creating accounts at scale inevitably produce patterns.

Device fingerprint detail revealing headless browser characteristics

Device Fingerprinting

Headless browsers leave distinctive device fingerprints, even when they try to impersonate real browsers. Missing plugins, inconsistent screen dimensions, 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, to recognize bot traffic across multiple accounts.

Example: Catching a Credential Stuffing Bot

With Dregs, here's what it might look like when a bot operator runs a credential stuffing campaign against your login page:

0s
A new visitor arrives at your login page. Dregs collects the device fingerprint on first page load — before any form interaction.
0.1s
The device fingerprint reveals headless Chrome with an impossible hardware profile. The Humanity score drops to 8.
0.2s
The visitor submits a login attempt just 50ms after the page finished loading. No human types credentials that fast. The Behavior score drops to 12. Two more login attempts follow within the next 200ms, each with different credentials.
Seconds later
A "Bot" badge is assigned based on the combined Humanity and Behavior scores. An alert fires to your monitoring channel. A webhook notifies your application, which immediately blocks the session and drops all pending login attempts.

The entire detection and response cycle happens in seconds — faster than the bot can finish its first batch of credential tests.

Responding to Bot Traffic

Not all bots deserve the same response. Some you want to block immediately. Others you might want to observe quietly. Dregs gives you the detection signals — you decide how to act on them.

Total blocking

Terminate the session as soon as the bot is detected. Best for credential stuffing, spam bots, and other clearly malicious automation. The bot gets nothing, and your resources are protected. Fast and decisive.

Rate limiting

Slow down suspicious sessions with artificial delays and rate limits. The bot operator sees their throughput collapse but can't easily determine why, wasting their time and resources.

Silent monitoring

Watch without acting. Let the bot operate while you observe its behavior, targets, and techniques. Useful for well-behaved bots or when you don't want to interfere with wanted automations.

With Dregs webhooks, any of these responses can be fully automated. Your application receives scores, badges, and alerts in real time and acts on them without human intervention — whether it's 2 AM on a Tuesday or the middle of a holiday weekend.

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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