IPQualityScore's Device Fingerprint Technology allows you to further analyze your users, transactions, ad traffic, and similar data to produce highly accurate Fraud Scores. Multi-layered AI & machine learning algorithms analyze user behavior and intent against millions of patterns to accurately identify high risk activity. Over hundreds of data points are scored to produce a confident result for fraud prevention.
Track user accounts with a unique Device ID to detect duplicate accounts and similar risky behavior. Cross device tracking using our device fingerprinting API also detects device spoofing, emulators, bots, location spoofing, GPS tampering, and similar patterns of malicious abuse. Use the API docs below to quickly setup the service on your website or app.
After creating a Device Fingerprint Tracker, you will be presented with a script to include on your website to analyze behavior. We recommend placing this script on a funnel page or through a critical flow of your website such as the registration, login, or checkout/payment page. It is also useful at filtering impressions, clicks, redirects, and similar actions. You may create unique trackers for different pages or sites.
It is recommended to associate a request with an identifying piece of information (such as a "userID", "clickID", "transactionID", etc.). Any Custom Tracking Variables established in your account settings can be passed with each device fingerprinting request. This allows our reporting tools to filter by specific users, products, campaigns, transactions, etc. so that you can easily identify fraudulent activity. Simply pass your value(s) to our script as seen below to take advantage of this feature.
General Notes:
Our system allows you to execute a function after results are finished loading. You can use this for a variety of reasons. The most common include:
You can specify a function to be executed after our API returns its result by adding something like this after the script tag provided on the tracker page.
If you are storing limited data upon the initial check with Startup.AfterResult(), such as the "request_id", or would like to rescore a user based on changes you have made to your Custom Scoring Weights, then you can retrieve updated data using the following example:
Let's say we didn't have the "request_id" and did not capture any data with Startup.AfterResult(), but we knew that the request used Startup.Store() to associate the lookup with "userID" = 99. The data can retrieved by setting "type" to the correct tool and appending the "userID". This approach supports any variables on your account's Custom Tracking Variables and will always return the most recent request data that matches the search parameters.
General Notes:
Easily deploy our React Device Fingerprinting SDK using our NPM package. If you are not using react, then please continue using the documentation on this page to integrate JavaScript device fingerprinting. Mobile device fingerprint SDKs for Android and iOS are also available upon request.
Key | Expected Values | Description |
---|---|---|
success | boolean | Status of the request. |
device_id | SHA256 / string | The Device ID is generated as a hash from the user's device hardware and personal settings. This value can be used for tracking users, detecting duplicate accounts, or passed to our callback endpoint for confirmation. |
guid | SHA256 / string | Hardware tracking ID which uses a different algorithm for calculating a hash of the user's device. This value can overlap with other devices that share the same hardware configuration. Please use in conjunction with "guid_confidence". |
guid_confidence | int (0 - 100) | Accuracy of the "guid" match which associates a GUID hardware profile with other users, where 0 = not likely, 100 = very likely. A result of 100 is a guaranteed match. Confidence levels below 100 use an intelligent "best guess" approach. Some "guid" results may overlap users, such as a device with factory settings for popular devices. |
fraud_chance | int (0 - 100) | How likely this device is to commit fraud or engage in abusive behavior. 0 = not likely, 100 = very likely. 25 is the median result. Fraud Scores >= 85 are suspicious, but not necessarily fraudulent. We recommend flagging or blocking traffic with Fraud Scores >= 90, but you may find it beneficial to use a higher or lower threshold. |
is_crawler | boolean | Is this device associated with being a confirmed crawler from a mainstream search engine such as Googlebot, Bingbot, Yandex, etc. |
connection_type | string | Classification of the IP address connection type as "Residential", "Corporate", "Education", "Mobile", or "Data Center". |
proxy | boolean | Returns true if the lookup is on a Proxy, VPN, or Tor connection. |
vpn | boolean | Is this IP suspected of being a VPN connection? (proxy will always be true if this is true) |
tor | boolean | Is this IP suspected of being a Tor connection? (proxy will always be true if this is true) |
active_vpn | Premium Account Feature - Identifies active VPN connections used by popular VPN services and private VPN servers. | boolean |
active_tor | Premium Account Feature - Identifies active TOR exits on the TOR network. | boolean |
recent_abuse | boolean | This value will indicate if there has been any recently verified abuse across our network for this user. Abuse could be a confirmed chargeback, compromised device, fake app install, or similar malicious behavior within the past few days. |
bot_status | boolean | Premium Account Feature - Indicates if this device is a bot, spoofed device, or non-human request. Provides stronger confidence in decision making. |
reasons | array[string] | Premium Account Feature - Fraud Score Insights explain how this device's Fraud Score was calculated and provides further detail into enhanced Fraud Scores and penalties. This data point is only available via the postback API so real-time users cannot reverse engineer why they were penalized. |
ssl_fingerprint | string | Premium Account Feature - SSL fingerprint contains a sha256 of the SSL/TLS cyphers this device supports. Useful for detecting small changes in device fingerprints. This data point is only available via the postback API so real-time users cannot reverse engineer why they were penalized. |
device_timezone | boolean | Premium Account Feature - Time zone pulled directly from the user's device. This value may still look accurate and aligned to the user's IP location for high risk users, however we do detect location spoofing through other device signals. |
high_risk_device | boolean | Premium Account Feature - Indicates devices with a high confidence of fraudulent activity including emulators, virtual devices, location spoofing, and automated behavior. |
ISP | string | Internet Service Provider of the IP address. If unavailable, then "N/A". |
country | string | Two letter country code of the IP address, example: "US". |
city | string | City of IP address if available or "N/A" if unknown. |
region | string | Region or state of IP address if available or "N/A" if unknown. |
timezone | string | Time zone of IP address if available or "N/A" if unknown. |
mobile | boolean | Is this a mobile device? |
operating_system | string | Operating system name and version or "N/A" if unknown. |
browser | string | Browser name and version or "N/A" if unknown. |
brand | string | Brand name of the device or "N/A" if unknown. |
model | string | Model name of the device or "N/A" if unknown. |
ip_address | string | The IP Address associated with the device in IPv4 or IPv6 format. |
unique | boolean | Returns false if this device ID has been seen on multiple IP addresses. Returns true if we haven't seen this ID on multiple IPs. |
canvas_hash | SHA256 / string | A hash of the user's Canvas profile, calculated by the graphics card and other device hardware. This value is often not unique, so should not be used to identify a specific user. |
webgl_hash | SHA256 / string | A hash of the user's WebGL profile, calculated by the graphics card and other device hardware. This value is often not unique, so should not be used to identify a specific user. |
request_id | string | A unique identifier for this request that can be used to lookup the request details, interact with our API reports, or send a postback conversion notice. |
click_date | Date Time | Time of this request. (Premium feature) |
first_seen | Date Time | Time of the first request. (Premium feature) |
last_seen | Date Time | Time of the most recent request. (Premium feature) |
You can specify a function to be executed after our API fails to return its results correctly. This could be a result of them blocking some of our tracking or disabling third party scripts.
General Notes:
You can optionally process the Device Fingerprint service to collect additional details after the user has performed an action, such as after the user has submitted an order or purchase form. Our system allows you to provide an element to bind to as part of an "onclick" or "onsubmit" trigger. When the user clicks or submits that element, the Device Fingerprint code will execute and gather the form elements you've specified to perform fraud analysis.
The trigger will override the default action of the element's "onclick" or "onsubmit" function, perform IPQS fraud analysis and Device Fingerprinting service, and then execute the original action of the element. For example, if you bind the trigger to a form's submit button, our Device Fingerprint script will run first, then it will append the results of our fraud scoring to your form, and submit the form to your server. Setting "Startup.FormFieldPrepend" will prepend a title to all appended form variables as shown in the example above.
If you would like to prevent submitting the form right away, then you can use the Startup.AfterResult() function detailed above. When using the Startup.AfterResult() function, the Device Fingerprint will not append the results to your form. The console log will report errors if the service is unable to bind to your supplied trigger.
If you prefer to execute code right before our API is called during a trigger event, you can optionally supply a callback function as the second parameter on Startup.Trigger(). The event object will be passed so you can optionally utilize preventDefault() or call any other function as needed.
The form trigger framework allows you to specify additional fields for order submission and payment processing. These additional fields allow us to better track your users provide better fraud analysis to prevent transaction fraud. Using this feature requires that you use the Startup.Trigger() function as shown above. Without using this function, JavaScript will not properly append data to each request. Accepted fields and values are listed in the table below. If we are unable to locate a specified field, it will be reported in the console logs.
Instead of binding to a form, it is possible to delay the initial fingerprint processing by using Startup.Pause() and later Startup.Resume(). This pre-loads the necessarily JavaScript to fingerprint the user, but waits until Startup.Resume() has been called to process the request. Therefor, user inputted data, not available on the initial page load, can be attached to the initial request as in the example below:
Accepted Order & Transaction Parameters (Optional)Below is a list of optionally accepted parameters for order & transaction support, a brief description and a listing of their required formatting. All fields are optional and should be passed with Startup.FieldStore(). Please note, it is recommended to use our dedicated Transaction Scoring API for more accurate analysis on transaction & user data.
Key | Expected Values | Description |
---|---|---|
billing_first_name | String | The customer's billing first name. |
billing_last_name | String | The customer's billing last name. |
billing_company | String | The customer's billing company. |
billing_country | String | The customer's billing country name or billing country ISO-Alpha2. (EG: United States or US) |
billing_address_1 | String | The customer's billing street address part 1. |
billing_address_2 | String | The customer's billing street address part 2. |
billing_city | String | The customer's billing city. |
billing_region | String | The customer's billing region or state. |
billing_postcode | String / Number | The customer's billing postcode or zipcode. |
billing_email | String | The customer's billing email address. |
billing_phone | Number | The customer's billing 11 to 14 digit phone number. (If less than 10 digits provided, the country code will be guessed by our AI.) |
shipping_first_name | String | The customer's shipping first name. |
shipping_last_name | String | The customer's shipping last name. |
shipping_company | String | The customer's shipping company. |
shipping_country | String | The customer's shipping country name or shipping country ISO-Alpha2. (EG: United States or US) |
shipping_address_1 | String | The customer's shipping street address part 1. |
shipping_address_2 | String | The customer's shipping street address part 2. |
shipping_city | String | The customer's shipping city. |
shipping_region | String | The customer's shipping region or state. |
shipping_postcode | String / Number | The customer's shipping postcode or zipcode. |
shipping_email | String | The customer's shipping email address. |
shipping_phone | Number | The customer's shipping 11 to 14 digit phone number. (If less than 10 digits provided, the country code will be guessed by our AI.) |
username | String | The customer's username. |
password_hash | SHA256 / string | For security reasons and following industry best practices, a SHA256 hash of the user's password for better user analysis. |
credit_card_bin | Number | First six digits of the credit or debit card, referred to ask the Bank Identification Number. |
credit_card_hash | SHA256 / string | For security reasons and following industry best practices, a SHA256 hash of the credit card number is accepted to check against blacklisted cards. |
credit_card_expiration_month | Number | Two letter format of the credit card's expiration month. For example, May would be "05". |
credit_card_expiration_year | Number | Two letter format of the credit card's expiration year. For example, 2022 would be "22". |
avs_code | Number | One letter Address Verification Service (AVS) response code provided by the credit card processor or bank. |
cvv_code | Number | One letter Card Verification Value (CVV2) response code provided by the credit card processor or bank. |
order_amount | Number | Total balance of the entire order without currency symbols. |
order_quantity | Number | Quantity of items for this order. |
recurring | boolean | Is this a recurring order that automatically rebills? |
recurring_times | Number | If this is a recurring order, then how many times has this recurring order rebilled? For example, if this is the third time the user is being billed, please enter this value as "3". If this is the initial recurring order, please leave the value as blank or enter "1". |
Device Fingerprinting APIs profile devices in real-time to calculate a unique device ID and risk profile, based on the behavior and settings of the user's device. IPQS device fingerprinting produces accurate risk scores based on the quality of the user's device and behavior. For example, non-human bot behavior would indicate malicious activity and increase the risk score. Unique device IDs allow a website to accurately identify users with multiple accounts or high risk payments.
Using an Device Fingerprint API is a best practice to detect fraud during registration, payment or checkout, and similar user actions. Retrieve a device risk score as well as a device ID that can be used to track the user across your website. Real-time results provided by the device Application Programming Interface (API) can enrich user accounts and payment data.
Device Fingerprinting is the process of creating a device tracking ID and risk profile based on a user's device behavior and settings. The IPQS device fingerprinting service creates a unique device ID to track users as they interact with your site, and better understand quality based on a user's behavior during login, checkout, account creation, and similar actions.