Is My Geolocation API Drunk Again? Facing Bizarre Proxy-Related IP Location Issues
0
hey folks, following up on my previous post about my IP geolocation being a bit wonky. itโs still acting like a drunk GPS, but i've narrowed down the suspect.
- The Lingering Problem: My geolocation API is still showing users in completely bizarre locations, often data centers or known VPN/proxy hubs, not their actual residential areas. it's really messing up my analytics and targeting.
- My Suspicions: i'm heavily leaning towards VPNs and proxies messing with the location data. it's like my tool can't tell a real user from a server farm, even when i try some basic VPN detection methods.
- What I've Tried (and Failed At):
- switched geolocation API providers (MaxMind, IPinfo, etc.) - same issue.
- implemented some basic IP blacklist checks, but it's like whack-a-mole.
- tried to flag IPs known for cloud hosting, but it's not catching everything, and i'm getting false positives too.
- The Evidence (Dummy Log): i'm seeing IPs like this in my logs, which I know are not residential, yet the API gives them a random country:
[2023-10-26 10:30:15] INFO: User IP: 104.28.249.123 [2023-10-26 10:30:15] INFO: Geolocation API Response: {"ip":"104.28.249.123","country_code":"PL","country_name":"Poland","city":"Warsaw","is_proxy":false} [2023-10-26 10:30:16] WARN: Suspected non-residential IP (ASN: CLOUDFLARENET) geolocated to residential area. - My Urgent Question: How can I more accurately detect and filter out VPN/proxy IP addresses from my geolocation API results? Are there specific services or techniques for more robust VPN detection to improve location accuracy by identifying these?
- Closing: Anyone faced this before and found a reliable solution?
2 Answers
0
MD Alamgir Hossain Nahid
Answered 2 weeks agoIt appears your geolocation API is indeed struggling with the increasing prevalence of VPNs and proxies. The `is_proxy: false` flag from a standard API for an IP like 104.28.249.123 (a Cloudflare IP, as your log correctly identifies via ASN) is a clear indicator that basic geolocation services are not equipped for robust proxy detection. By the way, a quick grammar note: ensure you're using "I'm" with a capital 'I' for proper capitalization.
The core issue is that standard IP geolocation services primarily map an IP address to a physical location based on network registration and routing. They don't inherently differentiate between a legitimate residential user and a user connecting through a VPN server hosted in a data center, which can then be anywhere in the world. To accurately detect and filter out VPN/proxy IP addresses, you need to leverage specialized IP fraud detection services that go beyond basic lookup.
Hereโs a more robust approach:
- Integrate a Dedicated Proxy/VPN Detection Service: Instead of relying solely on your geolocation API's `is_proxy` flag, integrate a dedicated service designed specifically for this purpose. These services maintain extensive databases of proxy, VPN, TOR, and data center IP ranges, often incorporating real-time threat intelligence and behavioral analysis. Examples include IPQualityScore, FraudLabs Pro, or Proxycheck.io. They provide a more granular "proxy score" or a highly accurate `is_proxy` flag, often detailing the type of proxy (residential proxy, VPN, TOR, etc.).
- Combine Data Sources: While these dedicated services are powerful, you can enhance accuracy by combining their output with your existing data. For instance, if a user IP is flagged by a proxy detection service AND its ASN belongs to a known cloud provider (like Cloudflare, AWS, Google Cloud), your confidence in it being a non-residential connection increases significantly.
- Analyze Connection Type: Many advanced services also categorize the connection type (e.g., residential, mobile, business, hosting/data center). Prioritize filtering out IPs explicitly identified as 'hosting' or 'data center' if they are not expected.
- Implement Dynamic Scoring: Instead of a hard blacklist, consider a dynamic scoring system. An IP with a high proxy score from a dedicated service, combined with a data center ASN, could trigger a higher confidence flag for filtering or further verification, rather than an outright block which might lead to false positives. This helps in more sophisticated bot detection and filtering.
0
Amit Sharma
Answered 2 weeks agoMD Alamgir Hossain Nahid, your advice on dedicated proxy detection services worked a charm tho, really helped clean things up!
Your Answer
You must Log In to post an answer and earn reputation.