Terminal.skills
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censys

Censys search engine for internet-connected hosts, TLS certificates, and domains. Use when: certificate transparency monitoring, finding hosts by certificate fingerprint, alternative to Shodan for TLS/SSL analysis, discovering hosts running specific services, or tracking infrastructure changes via cert issuance.

#censys#certificates#tls#attack-surface#recon
terminal-skillsv1.0.0
Works with:claude-codeopenai-codexgemini-clicursor
Source

Usage

$
✓ Installed censys v1.0.0

Getting Started

  1. Install the skill using the command above
  2. Open your AI coding agent (Claude Code, Codex, Gemini CLI, or Cursor)
  3. Reference the skill in your prompt
  4. The AI will use the skill's capabilities automatically

Example Prompts

  • "Research recent trends in the AI developer tools market"
  • "Compile a competitive analysis report for our product category"

Information

Version
1.0.0
Author
terminal-skills
Category
Research
License
Apache-2.0

Documentation

Overview

Censys continuously scans the entire internet and indexes every reachable host with detailed information about open ports, TLS/SSL certificates, service banners, and configurations. Censys is particularly strong for certificate-based discovery — it indexes certificate transparency logs and lets you pivot from certificate subject names to IP addresses and vice versa. This makes it excellent for finding unknown infrastructure tied to a target organization.

Requires: Censys API key (free account at censys.io gives 250 queries/month).

Instructions

Step 1: Install and configure

bash
pip install censys
python
import os
from censys.search import CensysHosts, CensysCerts
from censys.common.exceptions import CensysRateLimitExceededException, CensysNotFoundException
import json
import time

# Set credentials via environment variables (recommended)
# export CENSYS_API_ID="your-api-id"
# export CENSYS_API_SECRET="your-api-secret"

# Or pass directly
CENSYS_API_ID = os.getenv("CENSYS_API_ID", "YOUR_API_ID")
CENSYS_API_SECRET = os.getenv("CENSYS_API_SECRET", "YOUR_API_SECRET")

# Initialize clients
h = CensysHosts(api_id=CENSYS_API_ID, api_secret=CENSYS_API_SECRET)

# Check account quota
account = h.account()
print(f"Quota: {account.get('quota', {})}")

Step 2: Search for hosts by query

python
def search_hosts(query, max_results=100, fields=None):
    """
    Search Censys for hosts matching a query.
    
    Common query examples:
    - services.tls.certificates.leaf_data.subject.common_name: "example.com"
    - services.port: 3389 and autonomous_system.name: "Company"
    - services.http.response.html_title: "Dashboard"
    - services.service_name: "REDIS" and not ip: "10.0.0.0/8"
    """
    if fields is None:
        fields = ["ip", "services.port", "services.service_name", "autonomous_system.name",
                  "autonomous_system.asn", "location.country", "services.tls.certificates.leaf_data.subject.common_name"]

    print(f"Searching: {query}")
    results = []
    try:
        for hit in h.search(query, fields=fields, pages=max_results // 100 + 1):
            results.append(hit)
            if len(results) >= max_results:
                break
            time.sleep(0.1)  # Gentle rate limiting
    except CensysRateLimitExceededException:
        print("Rate limit reached. Results so far:")

    print(f"Found {len(results)} hosts")
    for r in results[:20]:
        ip = r.get("ip")
        services = r.get("services", [])
        ports = [str(s.get("port", "?")) for s in services]
        asn_name = r.get("autonomous_system", {}).get("name", "N/A")
        country = r.get("location", {}).get("country", "N/A")
        print(f"  {ip:<20} ports: {','.join(ports):<20} {asn_name} ({country})")

    return results

# Find hosts serving TLS certs for a domain
search_hosts('services.tls.certificates.leaf_data.subject.common_name: "*.example.com"')

# Find exposed Redis servers
search_hosts('services.service_name: "REDIS"', max_results=50)

# Find hosts in a specific org
search_hosts('autonomous_system.name: "Example Corporation" and services.port: 443')

Step 3: Look up a specific IP address

python
def lookup_host(ip_address):
    """Get detailed information about a specific IP from Censys."""
    try:
        host = h.view(ip_address)
        print(f"\n=== Censys Host View: {ip_address} ===")
        print(f"IP: {host.get('ip')}")

        asn = host.get("autonomous_system", {})
        print(f"ASN: {asn.get('asn')}{asn.get('name')} ({asn.get('country_code')})")

        loc = host.get("location", {})
        print(f"Location: {loc.get('city')}, {loc.get('country')}")

        print(f"\nServices:")
        for service in host.get("services", []):
            port = service.get("port")
            svc_name = service.get("service_name", "unknown")
            transport = service.get("transport_protocol", "tcp")
            banner = service.get("banner", "")[:80]

            tls = service.get("tls", {})
            cert_cn = ""
            if tls:
                leaf = tls.get("certificates", {}).get("leaf_data", {})
                cert_cn = leaf.get("subject", {}).get("common_name", "")

            print(f"  {port}/{transport}{svc_name}", end="")
            if cert_cn:
                print(f" | cert: {cert_cn}", end="")
            if banner:
                print(f" | banner: {banner}", end="")
            print()

        return host
    except CensysNotFoundException:
        print(f"Host {ip_address} not found in Censys.")
        return None

lookup_host("8.8.8.8")

Step 4: Certificate-based discovery

python
def find_hosts_by_domain_cert(domain, include_subdomains=True):
    """
    Find all IP addresses serving TLS certificates for a domain.
    This is highly effective for finding unknown/shadow infrastructure.
    """
    if include_subdomains:
        query = f'services.tls.certificates.leaf_data.names: "{domain}"'
    else:
        query = f'services.tls.certificates.leaf_data.subject.common_name: "{domain}"'

    fields = [
        "ip",
        "services.port",
        "services.tls.certificates.leaf_data.subject.common_name",
        "services.tls.certificates.leaf_data.names",
        "services.tls.certificates.leaf_data.issuer.common_name",
        "autonomous_system.name",
        "location.country",
    ]

    print(f"Finding hosts with TLS certs for: {domain}")
    results = []
    for hit in h.search(query, fields=fields, pages=5):
        results.append(hit)

    print(f"\n{len(results)} hosts found:\n")
    for r in results:
        ip = r.get("ip")
        asn = r.get("autonomous_system", {}).get("name", "?")
        country = r.get("location", {}).get("country", "?")
        services = r.get("services", [])
        for svc in services:
            tls = svc.get("tls", {})
            if tls:
                leaf = tls.get("certificates", {}).get("leaf_data", {})
                cn = leaf.get("subject", {}).get("common_name", "")
                names = leaf.get("names", [])
                issuer = leaf.get("issuer", {}).get("common_name", "")
                port = svc.get("port")
                print(f"  {ip}:{port} | CN: {cn} | SAN: {names[:3]} | Issuer: {issuer} | {asn} ({country})")

    return results

find_hosts_by_domain_cert("example.com")

Step 5: Aggregation queries

python
def aggregate_query(query, field, num_buckets=10):
    """
    Aggregate Censys results to get a distribution overview.
    Useful for understanding what products/versions/countries/orgs are common.
    """
    result = h.aggregate(query, field, num_buckets=num_buckets)

    print(f"\nAggregation: {query}")
    print(f"Field: {field}")
    print(f"Total matching: {result.get('total', 0):,}")
    print(f"\nTop {num_buckets} values:")
    for bucket in result.get("buckets", []):
        print(f"  {bucket['key']:<50} {bucket['count']:>10,}")

# Distribution of countries for Apache servers on port 80
aggregate_query("services.http.response.headers.Server: Apache", "location.country", 15)

# Distribution of services for a specific ASN
aggregate_query("autonomous_system.asn: 15169", "services.service_name", 20)

# TLS version distribution
aggregate_query("services.tls: *", "services.tls.version_selected", 10)

Step 6: Export results to file

python
def export_hosts_to_json(query, output_file, max_results=500):
    """Export Censys search results to a JSON file for offline analysis."""
    print(f"Exporting up to {max_results} hosts for query: {query}")
    results = []

    for hit in h.search(query, pages=max_results // 100 + 1):
        results.append(hit)
        if len(results) >= max_results:
            break

    with open(output_file, "w") as f:
        json.dump(results, f, indent=2)

    print(f"Exported {len(results)} records to {output_file}")
    return results

# Export all exposed Elasticsearch instances
export_hosts_to_json(
    'services.service_name: "ELASTICSEARCH" and services.elasticsearch.indices_count > 0',
    "exposed_elasticsearch.json",
    max_results=200
)

Censys Query Language Reference

QueryDescription
services.port: 443Hosts with port 443 open
services.service_name: "HTTP"Hosts running HTTP
services.tls.certificates.leaf_data.subject.common_name: "*.example.com"Wildcard cert for domain
services.tls.certificates.leaf_data.names: "example.com"Any cert naming the domain
autonomous_system.name: "Amazon"Hosts in Amazon ASN
autonomous_system.asn: 16509Hosts in ASN 16509
location.country: "Germany"Hosts in Germany
ip: "8.8.8.0/24"Hosts in CIDR range
services.http.response.html_title: "Kibana"Exposed Kibana instances
labels: "cloud"Cloud-hosted infrastructure

Guidelines

  • Certificate pivoting: The most powerful Censys use case is pivoting from a known domain → certificate → IPs → more domains. This often reveals shadow IT and forgotten assets.
  • Quota management: Free accounts have 250 queries/month. Use aggregation queries to preview result counts before pulling full data.
  • Combine with Shodan: Censys and Shodan index different things. Use both for complete coverage. Censys is stronger on TLS/certificate data; Shodan is stronger on IoT and raw service banners.
  • Historical data: Censys Search 2.0 does not provide historical data by default. Use the Censys Data platform for historical snapshots.
  • SDK vs REST: The Python SDK handles authentication, pagination, and rate limiting automatically. Prefer it over raw REST calls.