Knowledgebase

Detecting Automated Attacks Print

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Bots against payment flows.

WHAT THEY ATTEMPT

Card testing with stolen numbers Credential stuffing against accounts Enumeration of account numbers or references Abuse of promotional credit Scraping of balances or data

WHAT CARD TESTING LOOKS LIKE

High volume, low value, high failure rate, from varied sources.

WHY IT MUST BE STOPPED QUICKLY

Fees accrue, decline ratios rise, and schemes intervene.

WHAT DETECTION SIGNALS EXIST

Velocity per address, device and account Failure rate far above normal Requests lacking normal browser characteristics Patterns in timing that are too regular

WHAT RESPONSES EXIST

Rate limiting Challenges Blocking sources Requiring authentication earlier

WHAT TO BE CAREFUL WITH

Blocking shared addresses, which affects many legitimate users.

WHY THAT MATTERS HERE

Address sharing is common, so address-based blocking has wide effect.

WHAT TO PREFER

Device and behavioural signals over address alone.

WHAT ENUMERATION PREVENTION REQUIRES

Identifiers that cannot be guessed Rate limiting on lookups Responses that do not reveal existence

WHAT TO MONITOR

Failure rates by endpoint, which reveal attacks in progress.

WHAT TO PREPARE

A rapid response, since these attacks develop in minutes.


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