As mobile app usage continues to increase, so does the potential for fraud. Fraudsters are finding new ways to exploit vulnerabilities in mobile devices that enable device spoofing, circumventing device fingerprinting methods, and large-scale attacks from a handful of devices. Protecting businesses and their customers from these threats requires the use of risk, trust, fraud, bots and behavior detection services that can leverage a wider range of telemetry and risk signals.
One way to gain more robust telemetry to detect risk in mobile devices is to leverage mobile detection SDKs, which expand on the amount of device metadata exposed by webSDKs. In this blog post, we’ll provide an overview of the problem space and attack methods used to target mobile devices and the benefits of native SDKs for detecting risk, trust, fraud, bots and behavior on mobile devices.
Mobile devices have become an integral part of our daily lives, with increased usage driven by a rise in mobile banking, e-commerce and other sensitive transactions, especially among Gen Z. As a result, mobile devices have become more attractive targets for cybercriminals looking for a foothold into users’ accounts to commit fraud, steal personally identifying information, access corporate networks and engage in other malicious activities.
In fact, mobile devices now account for over 60% of all digital fraud — a number that is likely to rise as organized crime rings, online marketplaces and generative AI continue to lower the bar for waging sophisticated attacks.
To gain access to the wealth of information and increasing amount of financial data exposed by smartphones and other mobile devices, fraudsters are leveraging a range of attack methods used to target mobile devices. Some of these methods include:
As a result of these increasingly evasive methods, it has become more difficult for businesses to distinguish between trusted users’ devices and devices that have been spoofed or compromised. This complicates businesses’ ability to leverage legitimate users’ known devices as a trust anchor to reduce friction — making it imperative that fraud and security teams leverage robust telemetry to detect risk and trust in mobile devices.
Native detection SDKs are software development kits that are specifically designed for mobile devices. They are designed specifically for mobile devices and can be integrated into mobile apps to gain access to more device metadata than webSDKs, as they have access to low-level system information and hardware components that allows for a more comprehensive view of the device’s behavior.
This includes the ability to collect more detailed information, such as sensor data, mobile network data and country codes, and other information which can be used to identify potential risks or attacks. Additionally, native detection SDKs can leverage operating system APIs to monitor for changes in device settings or behavior, and can more effectively detect tampering attempts or other suspicious activity.
In addition, native detection SDKs can run in the background of the device, allowing for continuous real-time detection and faster threat response, and they can be easily integrated into mobile apps for straightforward implementation with a short time to value.
Transmit Security’s best-in-class risk, trust, fraud, bots and behavior Detection and Response Services have native SDKs for both Android and iOS, enabling more robust detection of the growing threats that target mobile devices and applications. In our Transmit Security Research Labs, our researchers have developed sophisticated techniques that leverage our mobile SDKs to detect a wide range of risk signals, including mobile emulators, network mismatches, app cloning, rooting and jailbreaking, that can indicate threats to mobile applications.
In the next blog in this series, we’ll delve further into the differences and similarities between iOS and Android native detection and review how our Android and iOS SDKs can be used to detect emerging fraud techniques. To find out more about our native mobile SDKs for Detection and Response, check out the documentation page here.