analyzing-tls-certificate-transparency-logs
Helps your agent find phishing domains and unauthorized certificates. It monitors new certificates to detect fakes and brand theft.
What it does
This tool searches public security certificate (TLS) logs to find domains that look like yours but were created to deceive people (phishing) or for unauthorized activities. It helps protect your brand and detect threats.
When to use it
- ✓When you suspect someone is trying to create a fake website using your company's name.
- ✓To check if security certificates were improperly issued for domains similar to yours.
- ✓When investigating security incidents related to digital certificates.
Example of what to ask your AI
“Search for certificates issued for domains similar to 'mycompany.com' that might be fake.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool queries public certificate databases (crt.sh) and uses a calculation (Levenshtein distance) to find domain names that are very similar to yours. It checks who issued the certificate and if it looks suspicious.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-tls-certificate-transparency-logsOr download just the file:
curl -L https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/main/skills/analyzing-tls-certificate-transparency-logs/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
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:
- Query crt.sh for all certificates matching your domain pattern
- Identify certificates with typosquatting variations (Levenshtein distance)
- Flag certificates from unexpected CAs
- Monitor for wildcard certificates on suspicious subdomains
- 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')}")
FAQ
What are Certificate Transparency logs?
These are public records of all security certificates (TLS/SSL) issued by certificate authorities. They help ensure certificates are issued legitimately.
What is 'typosquatting'?
It's when someone registers a domain name that is a spelling variation of a popular name, aiming to trick users who mistype the name.
Do I need technical knowledge to use this?
Some familiarity with digital security is helpful, but the tool is designed to simplify the analysis of these logs.
Details
Original description by the author
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. '
Popularity
- GitHub stars
- 35k
- Ranking position
- #5497
- License
- Apache-2.0
- Updated
- 8/31/2026
Comments
- …
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