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Find Hidden Subdomains

Organization
UseOSINT
find-hidden-subdomains

Enumerate an organisation's subdomains and sibling domains from Certificate Transparency logs and passive DNS, without sending traffic to the target. Covers crt.sh and CT log queries, certificate SAN fields, subfinder and amass, and newly issued TLS certificates. Use when looking for staging, dev, admin or VPN hosts, mapping the full hostname footprint of a domain, or spotting infrastructure a company forgot it had. Applies to attack-surface mapping, vendor and supply-chain security review, brand-infringement discovery, and M&A technical diligence. Reference at useosint.com/skills/find-hidden-subdomains.

Overview

PublisherUseOSINT
RepositorySkills
Skill namefind-hidden-subdomains
Stars
49
Forks
5
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by UseOSINT on GitHub. Read the source before you install it.

Installation

Install the Find Hidden Subdomains AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/UseOSINT/Skills/tree/main/skills/find-hidden-subdomains
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/UseOSINT/Skills.git /tmp/Skills
mkdir -p .claude/skills
cp -r /tmp/Skills/skills/find-hidden-subdomains .claude/skills/find-hidden-subdomains
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Find Hidden Subdomains in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Find Hidden Subdomains on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Find Hidden Subdomains is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Find hidden subdomains

The hosts an organization forgot about are the ones worth finding, and most of them announced themselves the moment someone requested a TLS certificate. Certificate Transparency turns that into a searchable, permanent, historical index — free and completely passive. The beginner's mistake is treating a CT hit as a live host: most of what you pull back does not resolve, and that is information too, not noise.

Which source first

You holdStart withWhy
An apex domaincrt.sh wildcard queryBroadest free coverage, includes long-dead names
A domain behind a wildcard certPassive DNS, then archivesCT will only show you *.example.com
A guess at a naming conventionCT to learn the convention, then a wordlistLearn the pattern before brute-forcing anything
An org name, not a domainCertificate search by subject organizationFinds domains you did not know they owned
A cert you already haveIts SANs, then its serial and issuerSANs give siblings; serial finds the exact cert elsewhere
A need for current hosts onlyResolve the candidate listCT is historical by nature; DNS is the liveness oracle

How CT actually works

CAs submit every certificate they issue to append-only, cryptographically verifiable public logs. The log returns a Signed Certificate Timestamp, and mainstream browsers refuse to trust a publicly-trusted certificate that does not carry SCTs from qualified logs. So participation is not voluntary: if the certificate works in a browser, it is in the logs.

Three consequences that matter to you:

  • Nothing is removed. Logs are append-only. A hostname that appeared in a cert five years ago is still there after the host is gone.
  • You see precertificates and certificates. CAs log a precertificate first, then the final cert, so most names appear at least twice. Deduplicate.
  • Only publicly-trusted certs are covered. A private/internal CA, a self-signed cert, or a Cloudflare origin certificate never reaches a log. CT is blind to those hosts entirely.

crt.sh

The web UI takes ?q=, where % is a wildcard, and output=json gives you machine-readable results.

bash
# every name ever seen in a cert covering example.com or a subdomain
curl -s 'https://crt.sh/?q=%25.example.com&output=json' \
  | jq -r '.[].name_value' | sed 's/^\*\.//' | sort -u

# skip expired certs when you want a bias toward current infrastructure
curl -s 'https://crt.sh/?q=%25.example.com&output=json&exclude=expired' | jq -r '.[].name_value'

# an identity search on an organization string, which finds unknown domains
curl -s 'https://crt.sh/?q=Example+Corporation&output=json' | jq -r '.[].name_value'

The q parameter is an identity search: it matches domain names, and it also matches subject fields such as the organization name, which is how you find domains the brief never mentioned.

Useful JSON fields: name_value (all names on the cert, newline-separated), common_name, issuer_name, not_before / not_after, serial_number, entry_timestamp, and id (open https://crt.sh/?id=<id> to read the cert).

crt.sh also exposes its database read-only over Postgres — host crt.sh, port 5432, user guest, database certwatch. That lets you write real SQL against the certificate index instead of paginating JSON. It is a shared free service: keep queries bounded and expect to be cut off if you hammer it.

Alternatives and other CT front-ends, with their coverage and access models, are in reference/subdomain-sources.md.

The SAN field is the prize

Browsers ignore the Common Name; the subjectAltName extension holds the real list of covered hostnames. Read it as a statement about what one team deployed together:

  • A cert with a handful of related names is an intentional grouping — those hosts belong to the same service and probably the same admin.
  • A cert with dozens of unrelated names is a hosting provider's or CDN's bundled certificate. Those names are other customers, not your target's assets. This is the single biggest false-positive source in CT-based enumeration.
  • Names from different registrable domains on one cert are the good find: it means one operator manages both, which surfaces acquisitions, rebrands and undisclosed sibling brands. Verify before concluding — see the bundling trap above.
  • Internal names leak here constantly: jira, owa, vpn, *.corp.example.com, hostnames with rack or datacenter codes, and product codenames that never shipped publicly.

Wildcards hide, they don't reveal

*.example.com covers every subdomain and names none of them. An org that switched to a wildcard, typically alongside DNS-01 ACME automation, effectively went dark in CT from that point. When you see a wildcard:

  • Mine CT for the period before the wildcard, when per-host certs existed.
  • Move to passive DNS, which records answers rather than certificates.
  • Check archives and search indexes for hostnames (read-deleted-pages, google-like-a-spy).
  • Look for hosts that must still have their own cert for technical reasons: a deeper label than the wildcard covers (a.b.example.com needs its own), and anything on a different apex.

Combining sources, then resolving

CT gives you history. Passive DNS gives you observed reality. Wordlists give you names nobody published. Use all three, and keep them labelled by origin, because the confidence you can assign depends on where a name came from.

bash
subfinder -d example.com -all -silent -o passive.txt   # aggregates many passive sources
amass enum -passive -d example.com                     # different source mix, slower
dnsx -l passive.txt -a -resp -silent                   # resolve candidates to A records

Resolution turns candidates into three buckets: resolves to an address, resolves to a CNAME (read the target — it names the vendor, and a dangling one is a takeover candidate to report), or does not resolve at all. Dead names are still findings: they date the infrastructure, expose naming conventions, and sometimes resolve again later.

Detect wildcard DNS before you trust any brute-force result. Resolve a random name that cannot exist, such as zzq7x-nonexistent.example.com. If it answers, the zone resolves everything and your entire brute-force list is false positives.

Draw the line clearly: querying CT, passive DNS, search engines and archives never touches the target. Resolving candidate names through a public recursive resolver is effectively invisible but does generate lookups. Wordlist brute-forcing is high-volume DNS traffic, visible to the target's DNS provider and sometimes rate-limited or blocked. HTTP-probing the results with a tool like httpx is active — you are connecting to the target's servers. Flag brute-forcing and probing in your scope notes, and skip them if the engagement is passive-only.

What a name pattern implies

Do not treat all discovered hosts as equal. dev, staging, uat, vpn, legacy, old, and admin panels carry very different risk and follow-up than www. The triage table is in reference/name-pattern-triage.md.

Where this goes wrong

  • Bundled and multi-tenant certs. Shared hosting and CDN certificates put unrelated customers on one cert. Always check whether the other names on a cert plausibly belong to your target before adopting them.
  • CT is not an asset inventory. It is a record of certificate requests. Hosts behind internal CAs, self-signed certs, origin certificates, or plain HTTP are absent. Never report a CT-derived list as complete.
  • Names outlive hosts. Most historical CT names are dead. A list of 400 subdomains, unresolved, is a list of 400 unverified claims.
  • Names outlive ownership. A cert issued for a hostname while the domain belonged to a previous owner still shows up under the current owner's query. Check not_before against the domain's registration and transfer history via who-owns-this-domain.
  • CNAME'd third parties are not the target's assets. A hostname the target owns pointing at a SaaS tenant is the target's relationship, not its infrastructure. Do not treat vendor exposure as the target's exposure.
  • Aggregators disagree, and quietly. Each tool queries a different set of sources; free tiers truncate results without telling you. Two tools returning the same 50 names may both be reading the same one source.
  • Deliberate poisoning. Nothing stops anyone from getting a certificate for a name they control on a domain that looks like the target's. Typosquats show up in CT searches looking like the target's own hosts. Check the registrable domain character by character.

Confidence grading

  • Confirmed asset — the name resolves, and it is under a domain whose registration you have verified, on infrastructure consistent with the target's other hosts (same ASN, same cert issuer, same naming convention).
  • Probable asset — a CT name under a verified target domain that no longer resolves, or a name that resolves into a vendor's shared platform. Real name, unproven current state.
  • Unconfirmed — a name from a cert bundled with unrelated customers, a brute-force hit in a wildcard-DNS zone, a name on a different registrable domain with no corroborating link, or an aggregator result you have not seen the underlying cert or DNS answer for.

Record for every host: where the name came from, the cert id or passive-DNS source, the not_before date, and the resolution result with a timestamp.

Worked example

Target: example-health.test, scope is passive-only.

crt.sh with %25.example-health.test returns 61 unique names. Deduplicating precert/cert pairs cuts it to 38. Three are interesting immediately: vpn-uat.example-health.test, jira.internal.example-health.test, and billing-legacy.example-health.test.

One cert carries 44 names across nine unrelated companies — a managed hosting provider's bundle. Discard the 43 that are not the target's. That is the dead end, and it would have inflated the report by more than the real findings.

Resolving the 38: 12 answer. jira.internal does not resolve publicly, but its existence in a cert confirms an internal naming convention and a Jira instance — worth noting even though there is no host to look at. vpn-uat resolves to an appliance vendor's netblock, which goes to find-exposed-servers.

An identity search on the organization name from one of the certs returns two certs for examplehealth-group.test, a domain nobody mentioned in the brief. WHOIS via who-owns-this-domain shows the same registrant organization. That is the pivot that expanded the engagement.

Grade: 12 resolving hosts confirmed, jira.internal probable (real name, not publicly reachable), the sibling domain probable pending a corporate filing.

Pivots

New selectorGoes to
Live hostnames and their IPsfind-exposed-servers
Sibling and acquired domainswho-owns-this-domain, who-really-owns-it
Organization name from a cert subjectx-ray-a-company
Dead hostnames with historical contentread-deleted-pages
Dev/staging hostnames, repo-looking namessecrets-in-git-history
Indexed files on newly found hostsgoogle-like-a-spy
A large host/domain/IP set to structuregraph-the-network

Legal and ToS notes

Reading CT logs and passive DNS is publishing-by-design: the data exists to be read. Two limits are real. First, free services like crt.sh are shared infrastructure — heavy automated querying gets you blocked and is discourteous; use bounded queries and cache results. Second, DNS brute-forcing and HTTP probing send traffic to the target and, depending on volume and jurisdiction, can be argued as unauthorized activity; keep them inside written scope per ../../ETHICS.md. Discovering a dangling CNAME or an exposed staging host obliges you to report it, not to test it.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Find Hidden Subdomains AI skill do?

Enumerate an organisation's subdomains and sibling domains from Certificate Transparency logs and passive DNS, without sending traffic to the target. Covers crt.sh and CT log queries, certificate SAN fields, subfinder and amass, and newly issued TLS certificates. Use when looking for staging, dev, admin or VPN hosts, mapping the full hostname footprint of a domain, or spotting infrastructure a company forgot it had. Applies to attack-surface mapping, vendor and supply-chain security review, brand-infringement discovery, and M&A technical diligence. Reference at useosint.com/skills/find-hidd...

Why use Find Hidden Subdomains on TypingMind?

Because you install it once and use it with any model. Find Hidden Subdomains is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Find Hidden Subdomains in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/UseOSINT/Skills/tree/main/skills/find-hidden-subdomains. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Find Hidden Subdomains?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Find Hidden Subdomains?

As many as you like. As long as a model supports skills, you can use Find Hidden Subdomains with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Find Hidden Subdomains AI skill free?

Yes. It is published on GitHub by UseOSINT under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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