there was a blog post linked on this thread explaining how proxy IP lists (spur, synthient, ipinfo et al) have little actionable value and introducing an alternative real-time approach to detection.

But it got flagged/downvoted into removal (twice!). Someone here has lots of HN accounts and doesn't tolerate free competition.

Disclaimer: I'm the founder and main researcher of the "flagged" company.

I have been part of this community for over a decade, and in my experience the mods do take flagging and voting irregularities seriously when they are reported. If you believe there is manipulation happening on your posts, that is worth raising directly with them, since they have visibility we do not.

---

On the broader point, we process 3 trillion requests last year, have more than 80 employees, and run a dedicated privacy engineering team led by an ex-cybersecurity company founder. We invest in research on new detection methods and stay closely engaged with the developer community. If there are specific gaps you see in our product, I would be glad to hear them and discuss.

---

Whether any dataset, including residential proxy IP data, is valuable depends heavily on the application. Treating a dataset as invalid because it does not fit one particular model can lead to decisions on shaky ground.

We are regarded as one of the more if not the most accurate IP geolocation providers, and we spend considerable effort on education, solutions architecture, and documentation so customers understand what our data can and cannot support. For example, IP geolocation, even at highest level of accuracy, is not a person identifier. It will never be a 1:1 replacement of GPS geolocation.

Many of the largest companies in AI, anti-bot, fingerprinting, KYC, and CDN spaces use our data. If anti-bot systems and CAPTCHAs were fully reliable on their own, there would be less need for additional signals like residential proxy data. We do not assign a score or label an IP as good or bad. That judgment sits with the customer's own threat or analytics model.

Residential proxy IPs are, by and large, mostly used in web scraping operations of many different forms. If a company sees a moderate to high amount of traffic mimicking human behavior, it can struggle to tell bot traffic apart from real users. Anti-bot mechanisms can help, but they add friction to the user experience, and they are not cheap to run at scale.

Residential proxy detection data is one of the easiest zero-knowledge ways to gather intelligence. There is no need for users to solve a puzzle or for multi-page traversal to collect fingerprint data. All that is needed is the IP address.

Our residential proxy data customers tend to be on the more sophisticated side of cybersecurity. Suggesting that this data is a silver bullet for all their security needs would not reflect well on their expertise or ours. We present the data as is, and from there we work with customers on the right solution for their case.

[dead]