Mapping Starlink's global IP transit providers

A while back, I posted about Starlink’s Indian upstream. It’s interesting that now their prefixes are not visible behind routed via Telstra - AS4637 anymore, but it seems like they are testing Mumbai-based Microscan - AS55352.

I have always been curious about how they interconnect globally, particularly with which IP transit providers. To find out, I have to establish a relation between their GeoIP data and their BGP announcements globally. They have 2161 IP pools in the GeoIP sheet while originating an aggregate of 1109 prefixes from Starlink - AS14593.

Hurricane Electric’s Graph_v4 for AS14593 shows a rather complicated graph because they have different upstreams at different locations.

Here’s the logic I can follow to map:

1. Their GeoIP is either /24 or smaller than /24. I created a unique pair for the aggregate /24-city pair and did a lookup only for that. E.g for Luxembourg they have 4 x /27 (87.251.24.0/27, 87.251.24.32/27, 87.251.24.192/27 and 87.251.24.224/27) coming from same /24 (87.251.24.0/24). That way, I match this with the BGP table only once and not 4 times to get the same result.
2. Extract all routes from the global routing table dump I carry in my ClickHouse table for AS14593.
3. Get a subset of routes which are visible behind known transit-free tier 1 networks (to filter out announcements via peering)
4. Break BGP table prefix,as_path mappings to /24 ASNs - AS_PATH mappings to easily map the data.
5. Look for ASN on the left side of AS_PATH as visible from various transit-free tier 1 networks. E.g. a few lines of output for 87.251.24.0/24, I get:

"87.251.24.0/24","[28624,61568,2914,14593]"
"87.251.24.0/24","[262462,12956,1299,14593]"
"87.251.24.0/24","[20253,6762,2914,14593]"
"87.251.24.0/24","[54309,1299,14593]"
"87.251.24.0/24","[398465,3257,1299,14593]"
"87.251.24.0/24","[49544,2914,14593]"
"87.251.24.0/24","[13786,2914,14593]"
"87.251.24.0/24","[199524,3356,2914,14593]"

This means AS2914 and AS1299 are the upstreams here. This is just an example. Actual output has 1005 routes, and I cannot post that long list here.

Result

Since the number of transits is smaller than the number of locations, I mapped each location to a given transit provider. Here’s what it looks like:

The above data has been mapped from raw data which is posted here

Misc notes:

• Some providers are visible in the list as transit players like Tata Comm (AS6453), Vodafone Qatar (AS48728) and Microscan (AS55352), but no PoP is mapped to them. This is either because they are just testing and these are indeed their upstreams, but no mapping found in GeoIP data, OR they are upstream for a large number of prefixes as well as downstreams, which are again not in the GeoIP mapping.
• This table above is simply showing upstream for a PoP. In many cases, the drop is local, while in many cases, the drop is not local. E.g. Arelion (AS1299) seems to be upstream in Starlink Sri Lanka IPs, while actually that’s a drop for Arelion in Singapore.
• This post is going live on 24 Oct 2025, while I worked on most of this data on 14 Oct 2025. Routing might have changed a little bit in the last 10 days.

Disclaimer: This is my personal blog, and hence, posts made here are in my personal capacity. These do not represent the views of my employer.