> For the complete documentation index, see [llms.txt](https://docs.vida.id/identity-stack/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.vida.id/identity-stack/verify/id-fraud-shield-sdk/how-id-fraud-shield-works.md).

# How ID Fraud Shield Works

### How ID Fraud Shield Works

ID Fraud Shield operates through a three-stage process that ensures comprehensive fraud detection while maintaining optimal performance:

#### 1. Signal Collection

When your mobile app initializes the SDK, it immediately begins collecting device and behavioral signals:

* **Device Identity**: Fingerprint, hardware model, OS version, device age
* **Threat Indicators**: Emulator detection, rooted/jailbroken status, debugger, malware, app tampering
* **Network Intelligence**: IP address, geolocation, VPN/proxy detection, ISP information
* **Behavioral Patterns**: Copy-paste events, hesitation patterns, session duration, number of copy-paste events
* **Session Context**: IP velocity, device-to-account linkage, historical fraud patterns

This collection happens automatically and requires no user permissions, ensuring zero friction for your users.

#### 2. API Response

Your application receives a compact JSON response containing:

* **ruleEvaluations\[]**: Array of all triggered rules with their risk levels
* **deviceProfile**: Key device signals and threat indicators
* **ipProfile**: Network intelligence and geolocation data
* **behaviorMetrics**: User interaction patterns
* **riskLevel**: Overall assessment result (CRITICAL | HIGH | MEDIUM | LOW)
* **partnerTrxId**: Your transaction identifier for tracking

This response enables your application to make instant decisions: block transactions, require step-up authentication, flag for review, or allow seamlessly.

### Where ID Fraud Shield Works

ID Fraud Shield integrates across critical touch points in your application:

#### Mobile Applications

Currently, ID Fraud Shield is available for:

* **iOS Native Applications**: Swift/Objective-C via iOS SDK
* **Android Native Applications**: Kotlin/Java via Android SDK

#### Use Cases

Device intelligence is captured and evaluated during:

* **Account Opening**: Detect fake accounts, device farms, and synthetic identities
* **User Login**: Prevent credential stuffing and account takeover attempts
* **Password Reset**: Identify suspicious password change attempts
* **Fund Transfers**: Prevent fraudulent transactions and social engineering scams
* **Profile Updates**: Monitor changes to sensitive account information
* **High-Value Transactions**: Apply enhanced scrutiny to large-value activities