Checkout and signup are where abuse costs you directly: fake accounts, card testing, coupon and promotion abuse, and credential stuffing. They are also the pages where a false positive costs you a customer. Both make the same demand — a decision you can defend.
What these attacks have in common
They are automated, they are fast, and they are designed to look like ordinary traffic. A single scripted signup is easy to miss; ten thousand in an hour is a different problem. Rate limits catch the obvious spikes and miss the patient attacker.
Which signals carry weight
- Interaction timing. Variation in how a real person moves and types is hard to fake consistently; uniform machine timing stands out.
- Dwell and sequence. Real users pause, correct mistakes, and revisit fields. Scripts execute in a clean order.
- Client integrity. An automated or tampered browser leaves fingerprints a normal session does not.
- Contradictions. Client signals that disagree with each other are strong evidence of a faked environment.
- Request context. Proxy headers, origin, and a signed disclosure round out the behavioural picture.
Why graded beats binary
A yes-or-no check forces a choice between blocking a real customer and letting a bot through. A graded score lets you treat the ambiguous middle differently: allow the clear, flag the uncertain, block the clear. Verified agents can be admitted by policy so a legitimate integration is not caught in the sweep.
Keep the evidence
When a legitimate user is flagged, support needs a reason, not a shrug. Each Volance response names the checks that ran and which moved the score, so a decision can be explained to the person on the other end — and tuned once you see where your traffic actually sits.
Roll out in monitor mode
Log the verdicts first and compare them with what you know. Only let the policy act once the split looks right. Because enforcement runs on your server, tightening it is a change you make deliberately, not something a vendor does to you.
Frequently asked
Will this block real customers?
Run in monitor mode first and tune the thresholds. Graded scores let you flag the uncertain middle instead of forcing a block, and every decision carries its evidence.
Can it stop card testing?
It scores the session evidence around each attempt, so a burst of automated checkout attempts shows up as a pattern rather than as unrelated requests. Policy stays on your server.