iOS devices

Fingerprint's device intelligence platform is also available for iOS devices. Our device intelligence platform for iOS helps you to accurately identify the devices that interact with your mobile app and provides high-quality smart signals that will help you identify risky transactions before they happen.

To make integrations with mobile apps easier, we offer SDKs for apps built natively as well as for apps built using multi-platform frameworks (e.g. React Native).

A Fingerprint account is required to be able to use the Fingerprint Identification SDK in your mobile apps. If you do not have an account yet, please sign up for one.

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Download our demo app from App Store to see Fingerprint in action!

Device Identifier

When Fingerprint Identification SDK is integrated into your mobile app, for every device that interacts with your app, you will be able to receive a unique device identifier (i.e. visitorId). The visitor ID is derived solely from Apple's identifierForVendor (IDFV) property. The SDK does not use any fingerprinting techniques to identify a device.

However, despite the visitor ID being derived from IDFV, there are a few important differences between them:

• The visitor ID will remain the same even when the app is removed and re-installed whereas the IDFV will not.
• In addition to being scoped by the vendor, the visitor ID is also scoped by the Fingerprint Workspace. It means the only time the visitor ID remains the same between two apps is when the apps are from the same vendor and when they belong to the same Fingerprint workspace.

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Did you know?

The device identifier generated by the iOS SDK (embedded within your mobile app) will be different from the visitor ID generated by the Javascript agent (embedded within your website).

The identification accuracy, when compared with browsers, is better for iOS devices because the IDFV property has higher longevity than the signals used for identifying browsers.

For your reference, we have listed various scenarios where a visitor ID will remain the same before and after and where a new visitor ID will be created.

Proximity Detection for iOS Devices

Proximity detection is a complementary, location-based signal. Unlike the visitor ID, the proximity ID does not identify a unique device but instead represents a fixed geographical zone within which the device is observed. This provides an additional layer of context, making it possible to identify groups of devices in the same physical area or a single device that may have changed its identity while remaining in the same zone.

• To use this feature, make sure to update your app to use iOS SDK v2.10.0 or higher.
• Ensure your app declares the required location permissions. For integration details, please follow the instructions on the iOS SDK configuration page.
• Proximity IDs and related data (e.g., confidence level, precision radius) will be exposed only via the Server API, webhooks, or when Sealed Client Results are enabled.

We use a discrete global grid system to generate proximity data in a consistent and privacy-conscious way. This approach allows us to represent user locations as coarse, non-identifiable spatial zones (proximity IDs), enabling scalable proximity detection and fraud analysis while protecting user privacy.

The response will include proximity results in the following structure:

{
  "proximity": {
    "data": {
      "id": "Ykq4nTqI4aa",
      "precisionRadius": 10,
      "confidence": 0.91
    }
  }
}

id

The id field is a stable identifier for a given proximity zone. Devices observed within the same zone will share the same id. It can be used for detecting behaviors like:

• Devices frequently appearing together (co-location patterns).
• Repeated activity from the same physical area.
• Potential device farms or shared access points. id cannot be reverse-mapped to a specific geolocation, enabling privacy-preserving location-based analysis without compromising user identity or precision.

precisionRadius

The precisionRadius field indicates the precision level of the proximity zone, expressed in meters. For example, "precisionRadius": 10 means the device's location was mapped to a zone covering an area approximately 10 meters across.

• Smaller values correspond to finer-grained zones and higher precision.
• Proximity precision levels are hierarchical: each proximity ID is contained within a parent proximity ID at a coarser level (larger precisionRadius).
  • Devices with identical coordinates can map to different proximity IDs if their reported location accuracies differ significantly.
  • For example, identical coordinates with 5 m and 10 m location accuracy would map to the same proximity ID, while 50 m accuracy would map to a different, coarser proximity ID.
• By default, we return the most precise proximity ID based on the location signals, but you can also retrieve proximity data at a specific (default or larger) precisionRadius using /events/search.

How to interpret precisionRadius

confidence

The confidence field ranges from 0 to 1 and reflects the likelihood that the true device location lies within the mapped proximity zone rather than an adjacent one. It is calculated by evaluating multiple factors that determine how well the device location coordinates and accuracy radius fit within the proximity zone.

• Scores closer to 1 indicate high confidence that the true device location is inside the mapped proximity zone, as the device location area fits cleanly within its bounds.
• Scores closer to 0 indicate low confidence, as the device location area is only partially contained within the proximity zone bounds, suggesting the true location point may lie within an adjacent zone. Even with a score of 0, the true location will always be either within the mapped proximity zone or an immediately adjacent one. Retrieving proximity IDs from /events/search at coarser precision levels (filtering by larger precisionRadius values) typically yields higher confidence scores.

iOS Smart Signals

Smart Signals are actionable device intelligence signals that help you to make informed decisions about the device and thus prevent fraud. These signals could be used as input to your machine learning models behind your fraud detection or risk mitigation engines. For example, when you know that a request is originating from a jailbroken device, you will be able to take additional precautionary security steps (e.g., multi-factor authentication).

When your mobile app requests a visitor ID, the SDK, along with the IDFV, will collect several other attributes from the device. The Smart Signals are deduced by combining these attributes with additional algorithms.

For iOS, the following smart signals are available:

• Factory Reset Detection
• Frida Detection
• Geolocation Spoofing Detection
• IP Geolocation Detection
• IP Blocklist Detection
• Jailbroken Device Detection
• MitM Attack Detection
• Tampered Request Detection
• VPN Detection

These smart signals are available as part of our Pro Plus and Enterprise plans. If you are interested in one or more of these signals, please contact our support team to enable them. Signing up for an Enterprise plan does not automatically enable these signals.

Fingerprint Identification SDK for iOS

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Current Version: 2.10.0

For release notes and older versions, please visit the Changelog for iOS SDK page.

Supported Versions

The minimum version that the iOS SDK for Fingerprint Identification supports is iOS 13, tvOS 15. Per Apple and Statista, this will allow your app to be compatible with a wide variety of active iOS devices.

As of May 2023, our SDK will allow your app to be compatible with more than 94% of the devices in the world.

Getting Started Guides

Our Getting Started guides are aimed at helping you to integrate our SDK with your apps easily.

• For native iOS apps, see Getting Started Guides > iOS.
• For apps built using Flutter, see our Flutter SDK on Github.
• For apps built using React Native, see our React Native SDK on Github.

Privacy Manifest File Requirements for App Store

During WWDC 2023, Apple introduced a new requirement where app and SDK developers must create privacy manifest files to declare the data that their app/SDK collects and the reasons for collecting this data. Accordingly, starting from v2.3.2, the Fingerprint Identification SDK for iOS will include a privacy manifest file. To learn more, please see Understanding privacy manifest files.

FingerprintJS-iOS: Open-source identification library for iOS

We also provide a lightweight, open-source library called fingerprintjs-ios which is available to use for free by everyone. Our commercial SDK, Fingerprint Identification for iOS, is based on our well-maintained, free, open-source library.

For your better understanding, here is a complete set of differences between our open-source library (fingerprintjs-ios) and our commercial SDK (fingerprint-ios-pro).