Detecting how to detect proxies is important for websites to prevent spam and fraud. Typically, a website will block users that visit from a known proxy IP address or location. Some ML models and heuristics are used to identify the use of proxies. These methods are often combined with other tests to ensure the accuracy of a detection system.

Many of these tests look for common HTTP header values that are passed by proxies and VPN connections. This approach works well for detecting transparent proxies and VPNs. More advanced systems use DPI (Deep Packet Inspection) to analyze network traffic at a much more granular level and inspecting data beyond headers. This type of analysis can detect patterns that indicate the presence of a VPN or a proxy, including encrypted traffic patterns that are typical of tunneling protocols.

Proxy and VPN Risk Analysis: Identifying Suspicious Traffic

Other methods of identifying the use of a proxy are to check for IP address rotation, geolocation API, languages and browser extensions. Real user devices tend to remain consistent and do not switch IP addresses frequently. These types of identifiers are also obfuscated and spoofed by antidetect browser applications and proxies.

Another popular method is to utilize IP databases that contain a history of bad proxy IPs. These databases are updated regularly to reflect new proxies and their usage. A third option is to use a dedicated API service that provides a more comprehensive set of unique tests to accurately detect proxies. This allows sites to avoid false positive connections so that legitimate visitors are not penalized, and it reduces the risk of blocking users with valid reasons to use a proxy.