IPQS
Best Practices
Pass Additional Info

The following API inputs significantly improve scoring and the overall user experience while analyzing clicks, users, and transactions with IPQS:

  • user_agent (string): We strongly recommend passing the user_agent string associated with the IP address. This data point allows our scoring algorithms to better detect bots, abusive users, and high-risk IPs by analyzing the browser information. Including the full user agent can improve scoring by over 20%.
  • user_language (string): Further enhances scoring based on the user's device.
  • mobile (true/false): If you cannot pass the user agent but know that the request originated from a mobile device, we recommend setting this value as true to improve scoring accuracy.


Example request with recommended starting options

Replace IP_ADDRESS , USER_AGENT , and USER_LANGUAGE  with the appropriate values. 

Customize Scoring Settings

Customize IPQS scoring engines to better fit your audience based on how strictly we score IP addresses and the threshold to determine active proxy connections. The following settings are available to adjust scoring:

  • allow_public_access_points=true: Allows corporate and public connections such as Institutions, Hotels, Businesses, and Universities.
  • mobile=true: Forces the IP to be scored as a mobile device. Passing the user_agent will automatically detect the device type.
  • strictness=0: Uses the lowest strictness (0-3) for Fraud Scoring. Increasing this value will expand the tests we perform. Levels 2+ have a higher risk of false positives. Start with level 0 and increase as needed for the best results.
  • lighter_penalties=true: Lowers scoring and proxy detection for mixed-quality IP addresses to prevent false positives.
Minimize False Positives

If you experience any results that are not satisfactory, contact us and include the IP addresses and any other relevant data for the requests. We will examine these results and optimize your account's scoring settings. Once your account has received a settings optimization, all future requests will provide a much more accurate analysis. Out-of-the-box settings tend to work for 90% of clients, so if you find our default settings are a good fit, then optimization is not necessary.

Use the Postback API to Retrieve Past Lookups

The IPQS Postback API allows you to mark requests as converted and retrieve past data by associating them with a unique identifier. For example, you can pull the last request that matched a userID, transactionID, or similar tracking variable.

To perform the example requests below, make sure your initial API request passed a valid userID value (or any variable of your choice) and that you set this variable name in your custom tracking variables.

 

Example request to retrieve latest request by UserID

 

Example request to retrieve multiple requests with the Request List API and also search by IP Address

Analyze Results

Fraud Scores: The overall score is from 0 to 100, which indicates how likely the IP address belongs to an abusive user or is associated with malicious behavior. Fraud Scores for proxy & VPN connections with average risk are in the 70-75 range. Some clients may find IP addresses with scores in these ranges not problematic. However, IP addresses with scores >= 85 indicate suspicious activity, while scores >= 90 represent abusive and malicious behavior. We strongly recommend blocking requests associated with Fraud Scores >= 90. Simply filtering traffic, users, and transactions by the Fraud Score is the easiest way to analyze results quickly.

  • Abuse Velocity: Indicates frequent abusive behavior over the past 24-48 hours. Values can be "high", "medium", "low", or "none". "High" and "medium" levels are usually associated with poor reputation IP addresses.
  • Recent Abuse: This data point will be true for all users with recent abusive behavior detected among our honeypots, traps, and live sites across the IPQS network that report real-time data back to our scoring engines.
  • Bot Status: This data point will be true when this IP address has recently been involved in a botnet or made automated, non-human requests.
  • Risk Score (Transaction & User Data)


Analyze payment details and user data to produce an overall risk score from 0 to 100. This value identifies abusive user data, such as disposable phone numbers and emails, stolen credentials, unauthorized payment details, and similar reputation issues. Risk Scores >= 90 are "high risk".

Enhance Detection for Residential Proxies

Upgrading your account improves the detection of abusive IP addresses and residential proxies, which are today's biggest threats. Premium plans and above have access to exclusive blocklists and IP intelligence data, while Enterprise plans include enhanced residential proxy detection and protection with Fraud Fusion™.

Use Additional User & Transaction Scoring

If you have additional information, such as user and transaction data, we strongly recommend passing that data with your API request. These features are extensions of the base Proxy & VPN Detection API and do not consume an additional usage credit.

  • User, Order, & Transaction Scoring: Analyze a wealth of user and order data risk analysis for account details, phone numbers, physical addresses, and payment details.
  • Phone Reputation: Score the user's phone number by flagging invalid, disposable, and throwaway phone numbers to improve the detection of fake accounts and invalid user data.
  • Address Validation: Validate a user's physical address as further checks for data quality.


The IPQS User & Transaction Scoring API also allows you to bundle phone reputation and address validation into one check.

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