L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Design et création · SKILL.md

analyzing-tls-certificate-transparency-logs

analyzing-tls-certificate-transparency-logs

Queries Certificate Transparency logs via crt.sh and pycrtsh to detect phishing domains, unauthorized certificate issuance, and shadow IT. Monitors newly issued certificates for typosquatting and brand impersonation using Levenshtein distance. Use for proactive phishing domain detection and certificate monitoring.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: analyzing-tls-certificate-transparency-logs description: > Queries Certificate Transparency logs via crt.sh and pycrtsh to detect phishing domains, unauthorized certificate issuance, and shadow IT. Monitors newly issued certificates for typosquatting and brand impersonation using Levenshtein distance. Use for proactive phishing domain detection and certificate monitoring. domain: cybersecurity subdomain: security-operations tags: [analyzing, tls, certificate, transparency] version: "1.0" author: mahipal license: Apache-2.0

Analyzing TLS Certificate Transparency Logs

Instructions

Query crt.sh Certificate Transparency database to find certificates issued for domains similar to your organization's brand, detecting phishing infrastructure.

from pycrtsh import Crtsh

c = Crtsh()
# Search for certificates matching a domain
certs = c.search("example.com")
for cert in certs:
    print(cert["id"], cert["name_value"])

# Get full certificate details
details = c.get(certs[0]["id"], type="id")

Key analysis steps:

  1. Query crt.sh for all certificates matching your domain pattern
  2. Identify certificates with typosquatting variations (Levenshtein distance)
  3. Flag certificates from unexpected CAs
  4. Monitor for wildcard certificates on suspicious subdomains
  5. Cross-reference with known phishing infrastructure

Examples

from pycrtsh import Crtsh
c = Crtsh()
certs = c.search("%.example.com")
for cert in certs:
    print(f"Issuer: {cert.get('issuer_name')}, Domain: {cert.get('name_value')}")
Skills enregistrées