Consumer connections resold as proxy exits.

Home addresses enrolled into proxy networks, with how often we saw them, how persistent they are, and how many networks resell the same address.

Schema at a glance.

See documentation →

The database's schema and metadata are documented carefully. Multiple formats are available, including CSVGZ and MMDB.

ipproviderfirst_seenlast_seenhitshits_days_pctproviders_num
138.97.217.21netnut2026-06-232026-09-06827
113.188.74.104dataimpulse2026-08-092026-08-131762
45.173.157.0netnut2026-06-152026-07-31212
191.127.13.37netnut2026-06-222026-06-23513
2804:2980:f651:2b00:8a7f:a380:8e43:db1aanyip2026-08-142026-08-14111
ID
resproxy_ip_90d_v1
IP addresses
126,162,954
Refresh
Daily
CSVGZ
1.58 GB

Downloading it from code.

Database API reference →

One call gets you the current Residential Proxy IP build. Every official client wraps it three ways — straight to disk, a signed link you hand to your own runner, or bytes in memory — and each verifies the published checksum before it hands the build back.

download(path)
Streams the current build to disk and verifies the published checksum before it returns.
url(expires)
A time-limited signed link — hand it to your own downloader, a job runner or a CDN pull.
bytes()
The build in memory, for pipelines that never touch a filesystem.
build()
Build id, published time, row count, byte size and all four checksums.
format
csvgz, or mmdb where Residential Proxy IP publishes it.
since(build)
Poll the build id first and fetch only when it changed; an unchanged poll costs nothing.
from vpndetection import Client
client = Client(os.environ["VPNDETECTION_API_KEY"])
db = client.database("resproxy_ip_90d_v1", format="csvgz")
db.download("resproxy_ip_90d_v1.csv.gz") # to disk
url = db.url(expires=3600) # signed link
blob = db.bytes() # in memory
db.build().published # last build
download.pypip install vpndetection
Also available for C#, Ruby, Rust, Swift, Erlang, Zig and Perl. See all on GitHub →

Getting your hands on it.

Where Residential Proxy IP earns its place in a risk stack — and what each of these decisions needs from the data rather than from a score.

The hardest traffic to catch

Residential proxies look exactly like customers because they are customers, rented out. Persistence data is what separates them.

Score by persistence, not presence

An address seen once in ninety days is a different signal from one seen daily across seven networks. Both are in here with the counts to tell them apart.

Know who is reselling

providers_num tells you how many networks resell the same address — a strong indicator of a committed node.

Licence the full database
Sales will quote on volume, term and whether you need redistribution rights.
Checksums published per file — md5, sha1, sha256 and sha512.
Every published build stays fetchable, so you can pin a version and roll forward when you choose.
Samples are cut from the current build, not a synthetic extract.

An official client for every major language.

All SDKs on GitHub →

Twelve official clients for the languages you ship in, each wrapping the database endpoints as well as the lookup — list what you are licensed for, poll a build, follow the download redirect. Install commands are in the docs.

On this page

How often does this dataset rebuild?

Every dataset publishes its own cadence and its last build date. The proxy datasets additionally carry a rolling 90-day observation window, so first seen and last seen are relative to that window.

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Start without signing up.

Paste it into a terminal — no account needed. 1k daily allowance per user, answering ip and is_vpn.

curl "https://api.vpndetection.io/45.83.91.1"
{
"ip": "45.83.91.1",
"is_vpn": true
}
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Every request flags VPN IPs.
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