Transaction Abuse – Castle

Transaction Abuse

Stop card testing before the transaction

Implement velocity checks to prevent a transaction attempt from reaching your payment processor in the first place.

Real-time blocking

Rules execute in milliseconds to block transaction abuse inline without noticeable delay.

Custom definitions

Define transaction abuse your way using advanced filtering and real-time velocity queries.

Granular analytics

Leverage BI-grade analytics to expose transaction abuse and fraud rings at scale.

Data enrichment

Enriched with device intelligence, risk scores, velocity metrics, and much more.

Segmentation

Define transaction abuse using custom logic

Castle lets you use advanced filtering, real-time velocity queries, and custom lists to segment out transaction abuse with high precision.

includeBlocked Credit Card

or

Abuse Score

is > 90

and

Count of events Transaction by Device Fingerprint in the last 1 hour

is > 3

Automation

Action on transaction abuse in real-time

Rules execute in milliseconds and can be used to adapt the user experience based on risk in real-time.

is > 90

and

Disposable Email

is true

and

Count events Registration by Device Fingerprint in the last day

is > 3

or

Signals includeBlocked country

Real-time decisions

Assessments of data like user count per device or hourly failed logins executed in the blink of an eye.

Inline blocking

Initiate request blocks or step-up verifications anywhere in your app without disrupting the user experience.

Alerts & notifications

Ensure your team and users stay informed with triggered Slack notifications or webhooks.

Analytics

A holistic view of transaction abuse

Harness the power of BI-grade analytics to expose transaction abuse attacks and unravel fraud rings with precision.

Explore

1d Past day Save as
Event Name Registration Attempted, Login Attempted, …
and
Policy Action deny, challenge
Add filter Reset Events 3,159 Users 268 Devices 290 IPs 641

100500

Timestamp Policy Event User Location Connection Device Lists Signals
Sat, Aug 8 07:59:08 Challenge Medium Abuse Score 732496 kevin.qfanjul@gmail.com Spain33204, Gijón Telefonica de Espana 83.53.25.12 Chrome on Windows 10
07:59:08 Deny Bad email 471896 oleg.kalinovskiy75@gmail.com Ukraine29000, Khmelnytskyi Kyivstar 188.163.27.70 Chrome on Windows 10
07:59:08 Deny [ScAuth] Attempted Login 956616 themba.ndlovu@gmail.com South Africa8001, Cape Town Starlink 212.105.137.116 Chrome on Windows 10
07:59:08 Deny Password Reset Policy 849676 priya.sharma@gmail.com India400001, Mumbai Jio 157.49.135.38 Chrome on Windows 10
07:59:08 Challenge Trusted Device Policy 753516 anton.volkov.2023@gmail.com Russian Federation672000, Chita Rostelecom 95.189.74.74 Chrome on Windows 10

Enrichment

All the data you need to pinpoint transaction abuse

Every interaction is enriched with comprehensive device intelligence, risk scores, location data, and much more.

Risk Scores

Out of the box risk scores for account abuse, account takeover, and bot abuse.

Velocities

Compute personalized signals based on real-time metrics like counts, sums, averages, and more.

Device fingerprinting

Persistent device identifiers resilient to storage resets and resistant to privacy plug-ins.

Bot detection

Identify bot actions via bot scores, headless indicators, or velocity and rate limit checks.