IPinfo - IP Data Provider

The Residential Proxy Problem: Shared Infrastructure and Rapid Rotation We analyzed 170+ million residential proxy IPs and discovered two patterns that explain why fraud detection is so hard.

For you or your team, when residential proxy signals conflict, what tends to influence the final decision?

We break this down in even more detail here → ipinfo.io/blog/residen...

So what actually works instead?

When infrastructure is shared and rotation is fast, context matters more than history.

Signals like last_seen and percent_days_seen provide far more value than reputation scores alone.

These things break reputation-based detection.

Residential proxy IPs constantly rotate between three states:

• Acting as a proxy
• Going dormant
• Returning to normal residential use

The same IP can look abusive one moment and legitimate shortly after.

2. Rapid IP rotation

Most residential proxy IPs don’t stick around long enough to build reputation.

A majority are seen only once in a 90-day window, especially in IPv6 environments where churn is extreme.

1. Shared infrastructure

Some residential proxy IPs appear in many provider networks at once.

Fraudsters don’t need new infrastructure.
→ They simply switch which provider they access it through.

This is why provider-based blocking alone cannot keep up.

Are you blocking residential proxies but still seeing abuse?

It’s not a coverage issue.
It’s this 🧵👇

#ResidentialProxies #FraudPrevention #IPData

Fraud prevention isn’t just about detecting risk.
It’s about having enough context to make the right decision.

What finally pushes a signal from “monitor” to “intervene” for you?

#FraudPrevention #IPData #Cybersecurity

This is a great example of IP data being used thoughtfully inside a product. Nice work on the map integration, Kevin!

🤘 We’re AMP’D to announce that IPinfo is an official Torq AMP partner! Together, we’re transforming how security teams operate and empowering our customers to detect and defend against threats, faster.

More about our partnership: https://kb.torq.io/en/articles/9139725-ipinfo

The internet changes fast. In fact, IP behavior shifts daily across mobile, cloud, and privacy networks.

This myth explores why update frequency matters and how freshness shapes IP data accuracy.

#IPData #DataAccuracy #ProbeNet

IP data adds context across fraud prevention workflows, from login risk to payments, especially when signals conflict or infrastructure changes fast.

See how teams use IP data for fraud prevention →
https://ipinfo.io/use-cases/ip-data-for-fraud-prevention

#FraudPrevention #IPData #Cybersecurity

In Q4 2025, we expanded ProbeNet, our internet measurement platform, to deepen coverage, add redundancy, and diversify infrastructure where measurement matters most.

https://ipinfo.io/blog/probenet-q4-2025-expansion

#ProbeNet #IPData #InternetInfrastructure

​​Let’s raise a glass to our newest PoP in Bordeaux 🇫🇷🍷

Strengthening our coverage in Western Europe with more accurate, regionally grounded IP data.

#IPData #InternetInfrastructure #NetworkIntelligence

In a webinar with IPXO, our Head of Research Oliver Gasser broke down geolocation data, accuracy, & how measurement helps validate what’s real.

Full discussion→ https://ipinfo.io/blog/geolocation-data-explained-accuracy-signals-and-real-world-use

#IPGeolocation #IPData #NetworkIntelligence

If your IP consistently appears as part of a residential proxy pool, contacting your ISP is the next step.

For organizations, this should trigger an internal investigation into compromised devices or unauthorized routing.

This activity isn’t always malicious, but it’s not something to ignore.

What you can & can’t control:

You can reduce risk by removing unnecessary apps, being cautious w/ free tools, and monitoring traffic.

But there are limits.
You don’t fully control your public IP, especially on shared networks or CGNAT. Other users on the same network can affect your IP reputation.

Home IPs end up in proxy networks through:

• Proxyware or “share your connection” apps
• Free VPNs or utility software that routes traffic through you
• Malware or botnets that quietly turn devices into proxy nodes

For innocent users, this often leads to:

👎 More frequent CAPTCHA challenges
👎 Blocked access to websites or APIs
👎 Email delivery issues for services you run

In most cases, this isn’t about what you did.
It’s about how your IP is being used.

Why this is a problem:

Many online services rely on IP-based reputation to assess risk. When an IP is associated with a residential proxy network, platforms may limit access to protect themselves.

This can happen even if your behavior hasn’t changed.

Your home IP address might be part of a residential proxy network.

Here’s what you can (and can’t) do about it 🧵👇

#ResidentialProxies #IPData #Cybersecurity

We recently published our VPN Location Mismatch Report: ipinfo.io/vpnreport

Below is a breakdown of the VPN providers we analyzed and how often their claimed country coverage aligns with where traffic actually exits.

Did any of these results catch you off guard?

#VPNs #IPData #Cybersecurity

Speaking of migrating data infrastructure…
(If you missed it, our last post breaks down how we approached it with BigQuery)

If you have gone through a migration, what was harder than expected? Performance, cost control, changing existing workflows?

#DataEngineering #BigQuery #GoogleCloudPartner

From Fighting Infrastructure to Building Products with BigQuery We took our most painful internal query and ran it in Google BigQuery. 1 minute later, it was done for a few dollars. That changed everything.

BigQuery made it possible for IPinfo to scale without increasing headcount.

Those same benefits now power our native BigQuery integration, letting customers enrich data directly with SQL inside Google Cloud.

Learn more about how BigQuery powers IPinfo→ ipinfo.io/blog/ipinfo-...

Today, BigQuery powers IPinfo’s data platform.

We process billions of IP data points daily, experiment faster, and deliver fresher, more accurate IP data to customers.

The migration was incremental.

High pain workloads first.
New projects built on BigQuery.
Legacy systems migrated only when it made sense.

No downtime. No risky all at once migration.

BigQuery delivered more than speed. It also gave us:

• Pay only for what you query
• Massive parallel performance
• Minimal migration effort from existing SQL

Infrastructure stopped being the limiting factor.

The breakthrough: We tested one of our most painful data jobs in Google Cloud BigQuery.

A six hour query finished in about one minute.
The cost was just a few dollars.

The PostgreSQL wall: PostgreSQL worked well early on, until datasets grew into the billions of rows. Then query times became painful.

Even expert optimizations only delivered temporary relief.

The problem: As we scaled, internal data queries slowed dramatically. Jobs that once took an hour stretched to ten hours.

Engineers were spending more time optimizing databases than building products.

How IPinfo went from fighting infrastructure to building products with Google Cloud BigQuery 👇

#BigQuery #DataEngineering #IPData #GoogleCloudPartner