LSN โ€” Local Sovereign Network

TI-2026-032: The American Mirror A ยท B ยท C ยท D ยท E ยท F ยท G ยท H

032D โ€” The DigitalOcean Paradox

350 IPs, NYSE-Listed, Developer-Friendly โ€” and One IP at Threat Score 100

Executive Summary

DigitalOcean (AS14061, NYSE: $DOCN) is the largest US provider in our threat intelligence database by raw IP count: 350 tracked IPs across 8 countries. It is also the lowest by average threat score: 25.5. This creates the paradox: a publicly traded company with SEC disclosure obligations, quarterly earnings calls, and institutional shareholders hosts more tracked IPs than any other US provider โ€” but dilutes them across a massive customer base where most IPs are benign.

The paradox dissolves when you look at the top: IP 198.199.106.159 carries threat score 100 โ€” the absolute maximum in our entire scoring system. It belongs to hassh-14b2ddda386a4d10, the same botnet found on ColoCrossing, Psychz, MULTACOM, and Internap. But DigitalOcean also hosts at least five distinct botnet campaigns โ€” more campaign diversity than any provider documented so far.

I. The Volume Game

350IPs Tracked
25.5Avg Threat Score
976Honeypot Hits
117IPs at Abuse=100

DigitalOcean operates in a fundamentally different market than ColoCrossing or Psychz. It's a mass-market cloud provider โ€” the AWS alternative for indie developers, small SaaS companies, and startups. This means millions of droplets, of which only a small percentage are malicious. The low average threat score (25.5) reflects this dilution.

But 117 IPs at abuse_score=100 is not small. That's one-third of all tracked IPs โ€” universally flagged as malicious by independent reporters. On a percentage basis (33.4% at abuse=100), DigitalOcean is comparable to Psychz (91.7%) only if you count the high-threat population alone.

II. The Global Footprint

Unlike every provider in 032A-032C (all US-only), DigitalOcean operates across 8 countries. The abuse profile shifts dramatically by geography:

CountryIPsAvg ThreatProfile
United States24318.8Largest cluster, lowest threat โ€” developer-heavy
India2149.0Bangalore data center, nearly 2ร— US avg threat
Singapore2842.0Asia-Pacific hub, high threat density
Germany3040.6Frankfurt DC, European gateway
United Kingdom1538.7London DC
Canada464.84 IPs, ALL high threat
Netherlands825.9Amsterdam DC
Australia174.0Single IP, very high threat

The India and Singapore data centers produce IPs at 2ร— the threat level of US operations. Canada has only 4 IPs but they average 64.8. Australia: a single IP at 74. The pattern is clear โ€” DigitalOcean's smaller, non-US data centers have proportionally much worse abuse profiles. These facilities likely have smaller trust & safety teams, or route abuse reports through US-based processes with timezone delays.

III. The Registrant Archaeology

RDAP RegistrantIPsAvg ThreatHitsNote
DigitalOcean, LLC29525.2838Primary US entity
digitalocean1631.611Lowercase โ€” informal RDAP entry
Digital Ocean Inc administrator733.929Older corporate name
IRT-DIGITALOCEAN-AP649.66Asia-Pacific incident response team
Network Operations Center557.05Generic entity โ€” who is this?
RIPE-NCC-LEGACY-MNT351.341European legacy allocation
Asia Pacific Network Information Centre312.98APNIC registrations
DigitalOcean London161.05UK entity, single high-threat IP

The "Network Operations Center" entity is notable: 5 IPs at avg threat 57.0 โ€” significantly higher than DigitalOcean's direct registrations (25.2). This generic entity name appears on DigitalOcean's ASN but could represent a customer allocation, a partner agreement, or an internal operations block. Its elevated threat score suggests a cluster of misused infrastructure.

DigitalOcean appears under at least 7 different RDAP entity names: DigitalOcean LLC, digitalocean, Digital Ocean Inc administrator, IRT-DIGITALOCEAN-AP, DIGITALOCEAN-ASN, DigitalOcean London, Network Operations Center. For a public company, this is remarkably fragmented. Each entity corresponds to a different regional registry, a different historical corporate structure, or a different acquisition.

IV. Five Campaigns, One Provider

DigitalOcean is the first provider in TI-2026-032 to host multiple distinct botnet campaigns:

CampaignIPs on DOTop ThreatDescription
hassh-14b2ddda386a4d108+100The 628-IP libssh2_1.11.0 campaign (series-wide)
hassh-f555226df1963d1d4+93Distinct HASSH fingerprint โ€” separate tool/operator
recon-c6700436b9ae291Reconnaissance-specific campaign
hassh-03a80b21afa81068193Yet another distinct SSH client fingerprint
hassh-af8223ac9914f509183Additional fingerprint variant

This is qualitatively different from 032A-032C, where all high-threat IPs belonged to the single hassh-14b2ddda386a4d10 campaign. DigitalOcean's mass-market model attracts diverse criminal operators โ€” not just one botnet purchasing bulk infrastructure, but multiple independent operators choosing DO for different campaigns.

The Threat=100 IP

198.199.106.159 is the only IP in the entire 032 series to hit threat score 100 โ€” the absolute maximum. It's registered directly to "DigitalOcean, LLC," belongs to hassh-14b2ddda386a4d10, and has 72 honeypot hits. This IP has been reported by maximum independent parties (abuse_score=100), carries maximum threat indicators (threat_score=100), and remains operational. A $5/month droplet hosting a botnet node on a NYSE-listed company's infrastructure.

V. The Public Company Problem

DigitalOcean (NYSE: $DOCN) files 10-K annual reports with the SEC. It has a trust & safety team. It publishes abuse reporting procedures. It has legal, compliance, and investor relations departments. And yet:

  • 117 IPs at abuse_score=100 (maximum independent reporting)
  • 1 IP at threat_score=100 (maximum threat assessment)
  • 5+ distinct botnet campaigns operating simultaneously
  • 976 honeypot hits from tracked infrastructure

This is not a ColoCrossing that can claim ignorance. This is not an Internap in bankruptcy. This is a company that trades on the New York Stock Exchange, raises capital from institutional investors, and employs hundreds of engineers. The question isn't whether DigitalOcean knows about abuse on its network โ€” the question is whether knowing about it creates a legal obligation to act on it faster.

VI. The Developer Economy

DigitalOcean's business model โ€” $5/month droplets, instant provisioning, no questions asked โ€” is optimized for developers. It's also optimized for abuse. The same frictionless experience that makes a student deploy their first web app makes a botnet operator deploy a scanning node.

The economic math for DigitalOcean is challenging:

~$60/yrRevenue per Droplet
~$200Cost to Investigate Abuse Report
3.3ร—Investigation Cost vs Annual Revenue
117IPs Needing Investigation

If investigating and acting on a single abuse report costs $200 in staff time (reading the report, investigating the customer, issuing a warning, following up, potentially terminating the account), and the customer pays $60/year โ€” every abuse investigation is a net loss. For 117 IPs at abuse=100, that's approximately $23,400 in investigation costs against $7,020 in annual revenue. The rational economic decision is to do nothing.

VII. The Conspiratorial Reading

Read Between the Lines

Why does DigitalOcean have 5 campaigns while others have 1?

ColoCrossing, Psychz, MULTACOM, and Internap all host a single dominant campaign (hassh-14b2ddda386a4d10). DigitalOcean hosts at least five. The difference: DigitalOcean is a marketplace. Multiple independent criminal operators choose it because it's cheap, fast, and globally distributed. The single-campaign providers suggest a single buyer purchasing bulk โ€” a procurement operation. DigitalOcean's diversity suggests retail criminal hosting โ€” individual operators independently selecting the same provider.

Is the developer brand the actual product?

DigitalOcean's reputation as a developer-friendly platform may itself be what attracts abuse. Security tools that blocklist by ASN are reluctant to flag AS14061 because it hosts millions of legitimate developer projects. The brand is a shield โ€” not for DigitalOcean, but for the criminals using it.

The India-Singapore cluster

India (avg threat 49.0) and Singapore (42.0) both produce IPs at roughly twice the US average. Are these data centers genuinely hosting more abuse, or are they easier targets for stolen payment credentials used to provision droplets? Stolen credit cards from South/Southeast Asia provisioning infrastructure in regional data centers would explain the geographic threat disparity.

Who is "Network Operations Center"?

Five IPs at avg threat 57.0 under a generic entity name on a NYSE-listed company's ASN. This is either a customer-facing allocation that should have been registered properly, or an internal operations block that's been compromised. Either way, the name provides zero accountability โ€” which may be the point.

The quarterly earnings question

DigitalOcean reports quarterly earnings. Has any analyst ever asked about abuse metrics? Has any 10-K disclosure mentioned the 117 IPs at AbuseIPDB score 100? Public company disclosure requirements theoretically cover material risks โ€” but "hosting botnet infrastructure" is apparently not material enough to mention.

VIII. Conclusions

DigitalOcean demonstrates that scale creates its own accountability gap. With 350 tracked IPs, the company can point to a low average threat score (25.5) while simultaneously hosting the highest individual threat score in the entire series (100), the most campaign diversity (5+), and the most geographic spread (8 countries). The average conceals the peaks.

After four letters of TI-2026-032:

ProviderIPsAvg ThreatAt Abuse=100Campaigns
ColoCrossing/HostPapa (032A)7447.5461
Psychz + MULTACOM (032B)6758.3601
SingleHop/Internap (032C)4070.5361
DigitalOcean (032D)35025.51175+
TOTAL53135.7259โ€”

531 tracked IPs across four US provider groups, 259 at abuse_score=100. DigitalOcean alone contributes more IPs than the other three combined. The distinction between "volume hosting with abuse problems" and "abuse hosting" is semantic when the affected IP count reaches this scale.

Next: FranTech/BuyVM โ€” a provider that philosophically defends the right to privacy hosting, where the line between principle and complicity gets genuinely complicated.

Methodology & Sources

Data sources: LSN Threat Intelligence Platform (8,000+ IPs), Cowrie SSH honeypot, ARIN/RIPE/APNIC RDAP, PeeringDB AS14061, AbuseIPDB, DigitalOcean SEC filings (10-K/10-Q via EDGAR), HASSH campaign correlation. All cross-referenced with TI-2026-032A/032B/032C.

โš  Personal capacity. Research published independently โ€” not reflecting employer views. Derived from passive observation of attacks against personal infrastructure. Full disclaimer โ†’
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