analyzing-tls-certificate-transparency-logs

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	["certificate-transparency","ct-logs","crt-sh","phishing-detection","tls-monitoring","security-operations"]
version	1.0
author	mahipal
license	Apache-2.0
atlas_techniques	["AML.T0073","AML.T0052"]
nist_csf	["DE.CM-01","RS.MA-01","GV.OV-01","DE.AE-02"]
mitre_attack	["T1583.001","T1566.002","T1598.003","T1583.006"]
source	https://github.com/mukul975/Anthropic-Cybersecurity-Skills
source_commit	04450304b12645cb2b974ab96d28c0664758a88d

Analyzing TLS Certificate Transparency Logs

When to Use

• When investigating security incidents that require analyzing tls certificate transparency logs
• When building detection rules or threat hunting queries for this domain
• When SOC analysts need structured procedures for this analysis type
• When validating security monitoring coverage for related attack techniques

Prerequisites

• Familiarity with security operations concepts and tools
• Access to a test or lab environment for safe execution
• Python 3.8+ with required dependencies installed
• Appropriate authorization for any testing activities

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()}")