To further improve the accuracy, transparency, and explainability of our IP purity detection service, we have recently completed a major upgrade to the detection system. Key Improvements Multi-Source Cross-Validation The detection system no longer relies on a single database. Instead, it cross-validates IP network type, geolocation, ASN, Proxy/VPN/Tor status, and security risk signals across multiple independent data sources. Enhanced IP Type Detection We have introduced multi-dimensional signal analysis and confidence levels for different network types, including residential networks, datacenter/hosting networks, business networks, mobile networks, and Anycast/CDN networks. Signals may include: PTR / Reverse DNS ASN and network information Hosting / Datacenter databases RDAP registration data Proxy / VPN / Tor data DNSBL blacklists Abuse / Fraud risk signals The system evaluates the actual detection signals rather than relying solely on an ASN or a single database. Greater Transparency in Detection Evidence Detection reports now include: Detection Evidence Data Sources Cross-Validation Confidence Level Users can directly see why an IP is classified as residential, datacenter/hosting, business, or another network type. IP Purity and IP Type Are Evaluated Separately We have specifically refined the underlying data model: IP Type ≠ IP Purity A datacenter IP does not necessarily indicate malicious activity, and a residential IP does not necessarily mean that it is risk-free. The system therefore evaluates the following separately: IP network type Proxy / VPN / Tor status Blacklist status Abuse risk Fraud risk Estimated shared usage Other security signals These signals are then combined into an overall risk score and IP purity score. Unavailable Data Sources Are Not Treated as Risk Signals If a data source is unavailable, times out, or cannot provide valid information, the system explicitly marks it as unavailable. Missing data is not incorrectly treated as negative evi