The reported 360-IP, 12-provider results cannot be verified from the available evidence: its dataset, provider list, measurement date, and definition of “blocklist number” are not established. A separate study of 330 IPs across 11 providers offers useful context, but it is not a substitute for those missing results. Its main practical lesson is clear: announced IP-space statistics do not predict what a VPS customer will receive, and a blocklist total means little without knowing which lists produced the hits.
What the 360-IP headline does—and does not—establish
The headline describes a sample of 360 addresses from 12 VPS providers, with reverse-DNS rates ranging from 0% to 100%. But the available supporting material does not establish the underlying dataset, measurement date, provider roster, sampling method, or what the reported blocklist number counts. Those details matter: without them, the 360-IP figures cannot be independently assessed or responsibly expanded into provider-by-provider claims.
A related, separately reported study by zihuama, published September 28, 2026, sampled 330 IPs across 11 providers. It can illustrate how reverse-DNS and blocklist results should be interpreted, but its findings are not the results of the 360-IP sample.
What a separate 330-IP study found
In the 330-IP study, the author sampled 30 addresses per provider from announced IPv4 space, selecting candidate /24s and then one host address within each. A BGP-origin check matched the target ASN for all 330 addresses. The author describes the results as measuring how much of an ASN’s announced space carried reverse DNS—not a customer’s likelihood of receiving a particular kind of address. The /24 was used as an approximation of customer allocation granularity, not as proof of how providers assign VPS addresses. Read the study and its method.
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PTR records varied sharply by provider
The author reported PTR records on 163 of 330 sampled addresses (49.4%). Provider results in that separate sample were:
| Provider | Addresses with PTR | Rate |
|---|---|---|
| BandwagonHost | 30 of 30 | 100% |
| Hetzner | 29 of 30 | 96.7% |
| Contabo | 29 of 30 | 96.7% |
| RackNerd | 23 of 30 | 76.7% |
| Vultr | 18 of 30 | 60% |
| Linode | 16 of 30 | 53.3% |
| OVH | 11 of 30 | 36.7% |
| Oracle Cloud | 4 of 30 | 13.3% |
| DigitalOcean | 3 of 30 | 10% |
| Alibaba Cloud | 0 of 30 | 0% |
| Tencent Cloud | 0 of 30 | 0% |
These counts describe the study’s selected announced addresses, not all addresses belonging to those providers and not the odds for a particular customer. The study’s 30-address samples also do not establish that every provider’s allocation practices or address pools behave alike.
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A PTR hostname is not an ownership record
Having a PTR record and controlling its hostname are different questions. In the related sample, all 30 BandwagonHost PTR names used an 16clouds.com hostname; most Contabo and Hetzner records followed provider-style templates. The three DigitalOcean PTR names were customer-domain hostnames that the author characterized as user-configured.
A PTR record is a reverse-DNS name associated with an IP address. It does not prove who owns or operates the address: the PTR name, the organization shown in RDAP registration data, and the network announcing the address in BGP can differ. The study reported six PTR records pointing to third-party datacenter domains, illustrating why the hostname alone is not reliable evidence of ownership.
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Why a blocklist total needs its list-by-list breakdown
The separate study checked eight DNS-based blocklists and reported that 40 of 330 addresses (12.1%) appeared on at least one. Thirty-six of those 40 hits came from dnsbl.spfbl.net. That concentration changes how the aggregate should be read: “12.1% listed” does not mean the addresses were broadly listed across eight services. It means that, in this sample and at query time, at least one of the checked lists returned a hit for that share of addresses, with most hits attributable to one list.
RackNerd had 24 of 30 sampled addresses flagged, all attributed in the study’s per-provider results to dnsbl.spfbl.net; the addresses appeared one per sampled /24. The author interpreted this clustering as suggestive of an ASN-wide or list-policy effect, rather than evidence that 24 individual VPS hosts had behaved abusively. That is the author’s interpretation, not an independently established explanation, and the author said the list’s policy could not be assessed externally.
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The eight lists checked were 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. The study excluded zen.spamhaus.org because, according to the author, it refused queries from public resolvers. The author called that a meaningful gap because of the list’s importance to mail filtering.
What these measurements mean if you plan to send email
Neither a clean DNSBL lookup nor a listing settles whether mail from an address will reach inboxes. The related study did not run live delivery tests or test actual VPS customer machines. A clean result on the queried lists does not prove inbox placement; a listing by itself does not prove that messages will bounce. Deliverability depends on factors these address-space lookups did not measure.
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Check reverse-DNS control before choosing a VPS for mail
If your mail setup needs a matching reverse-DNS hostname, verify that you can configure the PTR record for the specific address assigned to your VPS. The study’s practical recommendation is to set a hostname using your own domain through the provider’s control panel, rather than assuming a provider-generated template will meet your needs. Confirm the provider’s current process and restrictions before relying on this for a production mail server.
Compare the address and support policies, not just a percentage
For a meaningful provider comparison, ask whether the assigned address has customer-configurable PTR, how addresses are assigned or replaced, which exact lists are checked and what each reports, how addresses are distributed across datacenters, and how abuse or delisting requests are escalated. Also establish whether the evidence concerns an actual assigned VPS address or only announced ASN space. The related study supports asking these questions; it does not establish a comparative verdict for the 12-provider headline sample.
How to judge whether a provider study is trustworthy
Before treating a percentage or blocklist aggregate as a buying signal, check the definitions and denominator behind it. The related study recounts a useful warning about measurement logic: an earlier claim that all 330 addresses had an RDAP abuse role was discarded after a stricter recheck of ten records found zero. A loose parser had matched the word “abuse” anywhere in the JSON—including remarks and email strings—instead of validating that an entity’s role was actually abuse.
- Sample frame: Does the study query announced address space, assigned VPS addresses, or live customer machines?
- Provider and ASN mapping: Are sampled IPs shown to originate from the intended provider network?
- Denominator: Are rates calculated from addresses actually queried, with the sample size stated for each provider?
- PTR definition: Does the count mean a PTR exists, or that the hostname follows a particular policy or belongs to a customer?
- Blocklist composition: Are the exact lists named, with per-list counts rather than only a combined total?
- Parser and field validation: Do automated checks verify the meaning of a structured field instead of matching a word anywhere in a response?
- Time and scope: Are the measurement date and any unavailable or excluded services disclosed?
These checks help distinguish a measurement of provider address space from evidence about the address a customer will actually receive. They also prevent a broad aggregate from concealing a result driven by one list or a counting error.
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