Real buyers blocked at checkout
Generic managed rules misfire under peak load. At a global entertainment brand, a SQL-injection rule tripped on third-party tracking cookies and kept campaign shoppers off the checkout.
Peak shopping traffic looks a lot like an attack. Static rules block real buyers at checkout, while bots blend into the rush. Huskeys tunes your existing Network Edge for the busiest days of the year.
Generic managed rules misfire under peak load. At a global entertainment brand, a SQL-injection rule tripped on third-party tracking cookies and kept campaign shoppers off the checkout.
More shoppers send AI agents to compare, add to cart and buy. Block them all and you lose real orders. Let them all in and bad bots follow.
Scalpers, scrapers and card-testers mimic real browsers and ride the holiday spike, while expensive inspections run on every request.
Rules tuned for a normal week start blocking when traffic spikes. Anything above the line gets a 403, and most of it is real shoppers.
Illustrative traffic pattern.
Drag the handle to see where the money goes when your WAF blocks real buyers, and when it doesn’t.
/checkout403 Blocked/login200 Let through/cart?utm=bf403 Blocked/api/prices200 Let through/payment403 Blocked/gift-cards200 Let through/checkout403 Blocked/login200 Let through/cart?utm=bf403 Blocked/api/prices200 Let through/payment403 Blocked/gift-cards200 Let through/checkout200 Order placed/loginBlocked early/cart?utm=bf200 Added to cart/api/pricesBlocked early/payment200 Paid/gift-cardsBlocked early/checkout200 Order placed/loginBlocked early/cart?utm=bf200 Added to cart/api/pricesBlocked early/payment200 Paid/gift-cardsBlocked earlyThree quick answers. We estimate how many real buyers your rules block at peak, and what that costs.
Estimate only, modeled from how recently rules were tuned and a typical holiday traffic surge. The review measures your real numbers.
A one-page checklist for retail and e-commerce security teams.
“Since implementing Huskeys, we’ve significantly hardened our current WAF, reducing false positives and catching sophisticated threats.” Read the full case study