CrossClassify – AI-Powered Device Fingerprinting for Fraud Prevention

Detect bots and fraud using behavioral device fingerprinting

Fingerprint every user action to reveal abnormal and automated behavior.

See it in action

How it works

Device Finger Printing Hero Section Image

Solution

Device Fingerprint Issues We Resolve

Prevent fraud with accurate, real-time device intelligence.

Book a Demo

Stop Device Spoofing Fraud

Prevent unauthorized access with advanced device fingerprinting techniques that detect tampered device attributes, emulators, or masking attempts.

Catch Returning Fraudulent Devices

Detect repeat offenders using persistent device fingerprints to identify fraud rings and returning bad actors.

Detect Synthetic Identity Fraud

Expose synthetic IDs by analyzing device behavior, configuration inconsistencies, and cross-session anomalies.

Block Automated Bot Attacks

Stop bots and scripts by analyzing device entropy and fingerprint consistency across sessions.

Prevent Device Evasion Techniques

Identify users attempting device resets, clean re-installs, or cloaking tactics through resilient fingerprinting.

Stop Multi-Account Fraud

Detect multi-accounting and abuse by correlating unique device fingerprints used across fake or bonus accounts.

Account Takeover Risk Detection

Prevent account takeover by flagging unusual device signatures during login or sensitive actions.

Block Fake Account Creation

Stop fake signups by verifying if the device has a risky fingerprint or fraud history.

Mitigate Bot and Script Abuse

Prevent abuse of your platform by identifying automated tools using real-time fingerprint anomaly detection.

Detect Identity and Device Spoofing

Reveal impersonators using device emulators or identity spoofing through signature mismatches.

Score Device Risk in Real-Time

Assign dynamic risk scores based on device history, configuration, and behavioral signals to protect transactions.

In Action

Try Cross Classify in Action

We support a wide range of device fingerprint recognition methods to quickly detect any threats to your product. Try our quick demo to see how it works — just keep in mind, the production version is even more powerful.

Want to Try Cross Classify in Action?

Technologies

Our Approach to Device Fingerprint Intelligence

Detect devices, reveal fraud, protect accounts.

Continuous Device Monitoring

Our device fingerprinting solution gathers and correlates multiple hardware and software attributes to build a unique device identity, resistant to evasion and spoofing. This enables continuous device monitoring across sessions, detecting returning fraudsters, device manipulation, and multi-account fraud even when IPs, browsers, or cookies are changed.

Learn More ❯

Behavior Analysis with Fingerprint Signals

By combining device fingerprinting signals with behavioral analysis, our system detects unusual patterns in how users interact with devices, catching scripted bot abuse, synthetic identity fraud, and account takeover attempts. Even if a device is spoofed, our precise fingerprinting algorithm reveals hidden behavioral inconsistencies.

Learn More ❯

Behavior Analysis with Fingerprint Signals Image

Geo Analysis Based on Device Fingerprint

CrossClassify’s device fingerprinting engine includes geo-location intelligence, linking device IDs with IPs, regions, and time zones. This flags device/IP mismatches, proxy usage, and geolocation anomalies associated with fraudulent logins or account takeovers.

Learn More ❯

Geo Analysis Based on Device Fingerprint Image

Device Link Analysis for Fraud Rings

Our technology performs device-based link analysis, uncovering hidden connections between accounts sharing the same fingerprint, devices reused for bonus abuse, or coordinated bot behavior. We map fraud networks by linking sessions, devices, and login patterns using our multi-attribute fingerprinting system.

Learn More ❯

Device Link Analysis for Fraud Rings Image

Enhanced Security and Fingerprinting Accuracy

CrossClassify’s fingerprinting engine uses entropy-rich signals like hardware specs, canvas, WebGL, OS, and behavioral markers to ensure high fingerprinting accuracy. This boosts protection against emulators, spoofers, and fraudulent devices, dramatically improving your fraud detection rates.

Learn More ❯

Enhanced Security and Fingerprinting Accuracy Image

Seamless Fingerprint Integration

Our device fingerprint API supports fast, flexible integration with your web, mobile, or hybrid infrastructure. Whether you’re securing user onboarding, login flows, or payment checkpoints, our SDK integrates in minutes and scales with you.

Learn More ❯

Real-Time Alerts and Fingerprint Notifications

Receive real-time alerts on risky device behavior, fingerprint mismatches, and signs of session hijacking or scripted activity. Our system instantly flags suspicious activity across your application using robust device signals.

Learn More ❯

Real-Time Alerts and Fingerprint Notifications

Blog

Latest from Cross Classify

Device Fingerprinting

How Does Device Fingerprinting Work?

Device fingerprinting creates a unique digital identifier for a device by analyzing a combination of its attributes. These attributes are collected from the device’s hardware, software, and network environment, enabling precise and persistent identification.

30 Dec 2024

Enhancing Security via Fingerprinting

Device Fingerprinting: Revolutionizing Digital Security and Beyond

In 2024, cybercrime is projected to cost the global economy approximately $9.5 trillion USD annually, underscoring the escalating threat to businesses worldwide

29 Oct 2024

Frequently asked questions

Device fingerprinting builds a unique device identity to detect when a login comes from a tampered or unfamiliar device. CrossClassify compares incoming device fingerprints to known safe or suspicious profiles to flag account takeover attempts in real time, blocking compromised access before damage.
Read more

Yes, by analyzing improbable combinations of device attributes and behavioral signals, device fingerprinting reveals synthetic identities. CrossClassify’s algorithm combines hardware, software, and behavioral markers to expose fake identities and prevent new account creation fraud.
Read more

Device spoofing detection flags manipulated or masked device details that fraudsters use to evade tracing. CrossClassify’s fingerprint engine resists spoofing by correlating multiple entropy signals, spotting tampered or emulated devices even if the attacker tries to alter visible attributes.
Read more

By tracking persistent device identifiers, fingerprinting exposes when the same device registers multiple bonus accounts. CrossClassify links these device fingerprints in real time to detect bonus abuse and block creation of additional fake accounts.
Read more

Automated bots often leave behind inconsistent device or behavioral patterns. Device fingerprinting identifies such anomalies and links bot sessions across devices. CrossClassify combines fingerprint signals with behavioral analysis to detect and block scripted bot attacks.
Read more

Yes, device evasion tactics like resetting browsers or reinstalling apps disrupt other signals but not persistent fingerprints. CrossClassify’s algorithm detects those attempts and maintains consistent device identity to flag and block device evasion fraud.
Read more

Combining location data with fingerprinting reveals when a device’s expected geolocation changes unusually. CrossClassify flags geo device mismatches and proxies in login or transaction flows to prevent remote account fraud.
Read more

High-entropy, multi-attribute signals like canvas, WebGL, hardware specs, and network data improve precision. CrossClassify’s robust fingerprint algorithm delivers low false positives while accurately identifying risky devices, even when other static signals (cookies, IP) fail.
Read more

Yes, our lightweight device fingerprint API and SDKs for web and mobile are designed for seamless deployment. CrossClassify integrates into onboarding, login, and transaction flows with minimal friction and fast setup.
Read more

Yes, CrossClassify triggers real‑time alerts when device fingerprint anomalies occur, such as mismatched fingerprints or repeated failed attempts from the same device. Receive notifications instantly to act before fraud escalates.
Read more

Let’s Get Started

Discover how to secure your app against fraud using CrossClassify

See it in action

Book a Demo

No credit card required

Frequently asked questions

How does device fingerprinting prevent account takeover fraud?

Can device fingerprinting detect synthetic identity fraud?

What is device spoofing detection with fingerprinting?

How do device fingerprints stop multi‑account bonus abuse?

How can device fingerprinting mitigate bot and scripted abuse?

Does device fingerprinting detect device evasion techniques?

Is geo-based device fingerprinting effective against remote fraud?

How accurate is device fingerprinting in fraud detection?

Can device fingerprinting integrate into my existing fraud stack easily?

Do I receive alerts based on fingerprint mismatches or risky devices?