The title’s 360-IP, 12-provider results cannot be verified from the available evidence: the related study located sampled 330 IPs across 11 providers, and its figures must not be presented as results from the 360-IP study. That separate study is still useful for understanding why provider-level reverse-DNS rates and a single blocklist total need careful interpretation.
What the available study measured
In a related article published September 28, 2026, the author displayed as zihuama reports sampling 330 IPv4 addresses—30 from each of 11 VPS providers. The sample came from providers’ announced address space, not customer VPS instances. The author describes the result as an estimate of how much of an autonomous system’s space carries reverse DNS (rDNS), not the chance that a customer will receive an address with a PTR record. [Source]
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The method used seed 20260928, selected candidate /24 networks and then one host address within each. The author says all 330 sampled addresses passed a BGP-origin check against the target ASN. A /24 is an approximation of customer allocation granularity, not proof that any particular customer would be assigned one of the sampled addresses.
Those are findings from the 330-address study only. They do not establish the 360-address study’s provider roster, measurement date, methodology, results or meaning of its blocklist figure.
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What the related sample found for reverse DNS
In that study, 163 of 330 sampled addresses (49.4%) had PTR records. Provider results were:
| Provider | Addresses with PTR | Share in the 330-address study |
|---|---|---|
| BandwagonHost | 30/30 | 100% |
| Hetzner | 29/30 | 96.7% |
| Contabo | 29/30 | 96.7% |
| RackNerd | 23/30 | 76.7% |
| Vultr | 18/30 | 60% |
| Linode | 16/30 | 53.3% |
| OVH | 11/30 | 36.7% |
| Oracle Cloud | 4/30 | 13.3% |
| DigitalOcean | 3/30 | 10% |
| Alibaba Cloud | 0/30 | 0% |
| Tencent Cloud | 0/30 | 0% |
Each percentage is based on 30 addresses in the author’s announced-space sample, not on customer machines or a provider-wide guarantee. The author reports that all 30 BandwagonHost PTR names used an 16clouds.com hostname; most Contabo and Hetzner names followed provider-style templates. The three DigitalOcean PTR names used customer domains, which the author describes as user-configured.
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Why a PTR record matters—and what it does not prove
A PTR record maps an IP address to a hostname in reverse DNS. For mail servers, a suitable reverse-DNS name can be part of a sensible configuration, and the related study’s practical advice is to set a hostname using your own domain through the provider’s control panel when possible. Whether that is possible, how it works, and whether a particular IP can be changed are provider-specific questions to confirm before buying.
A PTR name is not proof of who owns or operates the address. In six cases, the related study found PTR records pointing to third-party datacenter domains. Its examples show that the PTR hostname, the registrant information in RDAP and the organization announcing the route through BGP can differ. Treat those as distinct clues, not interchangeable identity records.
Unpack the blocklist total
The related study checked eight lists: all.s5h.net, bl.spamcop.net, dnsbl-1.uceprotect.net, dnsbl.dronebl.org, dnsbl.spfbl.net, hostkarma.junkemailfilter.com, psbl.surriel.com and bl.blocklist.de. It reports that 40 of 330 addresses (12.1%) appeared on at least one checked list. Thirty-six of those 40 hits came from dnsbl.spfbl.net.
That concentration changes how the aggregate should be read: “listed on at least one” does not mean the addresses were distributed evenly across lists or that every listing carries the same implication. RackNerd accounted for 24 of 30 sample hits, all attributed in the provider table to dnsbl.spfbl.net; those addresses appeared one per sampled /24. The author suggests this pattern may reflect an ASN-wide or list-policy effect rather than 24 individually abusive hosts, while noting that the study cannot establish whether the list’s policy is defensible. That is the author’s interpretation, not an independently demonstrated cause.
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The author excluded zen.spamhaus.org, saying it refused queries from public resolvers, and calls its absence a meaningful limitation because of the list’s importance to mail filtering. So the reported 12.1% is not a universal “blocklist rate”: it is the share hitting at least one of those eight queried lists under that study’s conditions.
Neither a listing nor a clean check predicts delivery
The 330-address study did not test mail delivery or real customer VPS machines. A clean result on the queried lists does not establish that messages will reach inboxes; a listing alone does not prove that mail will bounce. Delivery depends on more than a snapshot of a few DNS-based lists, so use a separate delivery test for the actual sending setup and recipient systems.
How to assess an address or provider for outbound mail
Ask questions that connect the provider’s network-level reputation to the address you will actually use:
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- PTR control: Can you set or change reverse DNS for the assigned IP, and can it point to a hostname on your domain?
- Address assignment: Is the IP dedicated, shared, replaceable, or reassigned under stated conditions? Ask how a replacement address is selected.
- Evidence quality: Are reputation checks for an address assigned to a live customer machine, or merely a sample from announced ASN space?
- List coverage: Which exact DNSBLs were queried, when, and what was the result on each—not just the total number of hits?
- Allocation detail: Are results spread across datacenters and network blocks, or concentrated in one ASN, region or /24?
- Support route: What is the process for reporting a listing or requesting an address review?
For your own candidate address, verify its current PTR and query the specific lists relevant to your use case. Record the lookup date and list names, and treat the result as a time-bound check rather than a promise about future mail delivery.
Why denominators and parser checks matter
The related author says an earlier claim that all 330 records had an RDAP abuse role was discarded after a stricter review found 0 of 10 in a recheck. A loose parser had matched the word “abuse” anywhere in JSON, including remarks and email strings, instead of validating an entity’s role. The lesson is practical: a clean-looking percentage is only as meaningful as the field definition and counting logic behind it.
When evaluating a provider comparison, look for the sampling frame, sample size per provider, ASN validation, denominator behind each percentage, query date and exact list composition. These details help distinguish a measurable property of sampled address space from an unsupported prediction about a buyer’s assigned IP.
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