Intelligent bot
management at the edge

HotWall classifies every request as bot or human using behavioral fingerprinting, managed signatures and risk scoring at the edge

Start protecting Contact sales

Bot abuse scenarios

Scraping, credential stuffing, inventory hoarding and other automated abuse patterns

Web scraping

HotWall detects pricing/content/API response scraping, blocking extraction before bandwidth drains and proprietary data leaks

Credential stuffing

Behavioral fingerprinting and risk scoring stop credential-stuffing floods with stolen logins before accounts are compromised

Inventory hoarding

Edge classification stops bots hoarding cart items, limited slots and inventory from real customers during peak sales/launches

Carding and checkout fraud

Edge classification catches stolen-card testing and automated checkout abuse before fraud reaches your payment processor

Automated traffic looks like normal HTTPS

Scrapers, credential-stuffing tools and inventory hoarders bypass basic firewalls and DDoS filters; without edge bot classification, abuse reaches login, checkout and API endpoints undetected

Basic rate limits cannot tell real customers from distributed botnets

Bot classification separates legitimate users from automated abuse

Credential stuffing and scraping drain revenue, analytics accuracy and origin capacity

Automated abuse controls block malicious bots before they scale

Blocking all bots breaks SEO crawlers and partner integrations

Precise bot detection preserves legitimate automation while stopping harmful traffic

What you get with HotWall Bot Management

Classification at the edge with selective challenge for suspicious traffic

Bot vs human classification

Every request gets human/good/malicious bot labels, enabling per-type policies without breaking legitimate automation

Behavioral fingerprinting

Browsing/session behavior, header consistency and TLS signals build client fingerprints, separating real users from scripted automation

Managed bot signatures

Pre-tuned signatures catch known scraper, credential-stuffing, headless-browser and other bots, updated as patterns emerge

Risk scoring engine

Unified risk score: fingerprint/signatures/behavior history - allow trusted, low-friction challenge borderline, block confirmed bots

Low-friction challenge layer

Suspicious requests receive an invisible or low-friction challenge - proof-of-work, JS validation or behavioral check

Good bot allowlist

Recognized crawlers and verified partner bots pass without setup - SEO and integrations stay intact during attacks

How HotWall classifies bot traffic

Every request is scored on the edge before it reaches your origin - with a clear outcome for humans, good bots and malicious automation

Incoming request

Nearest edge PoP captures HTTP/S request headers, TLS fingerprint, path, cookies and session context

Signal collection

HotWall builds live client-session fingerprints from behavior, HTTP anomalies, managed bot signatures

Risk scoring

Risk engine scores fingerprint, signatures and behavior history: trusted human to malicious bot

Classification decision

Based on score, the engine returns one of three outcomes: allow, low-friction challenge or block

Action at the edge

Trusted pass instantly; suspicious get light challenges; confirmed bad bots blocked before origin load

Control automated
traffic at the edge