security analyst security skill risk: medium
TLS Certificate Transparency Log Analyzer
The prompt provides instructions for querying Certificate Transparency logs via crt.sh and the pycrtsh Python library to detect phishing domains and unauthorized certificates, incl…
- External action: medium
SKILL 4 files · 2 folders
SKILL.md
---
name: analyzing-tls-certificate-transparency-logs
description: "Queries Certificate Transparency logs via crt.sh and pycrtsh to detect phishing domains, unauthorized certificate"
---
# 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.
```python
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
```python
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')}")
```
REQUIRED CONTEXT
- target domain or brand name
OPTIONAL CONTEXT
- specific certificate ID
EXPECTED OUTPUT
- Format
- markdown
- Constraints
- include python code snippets
- list numbered analysis steps
- cover prerequisites and when-to-use scenarios
SUCCESS CRITERIA
- 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
Includes two Python code snippets demonstrating pycrtsh usage for certificate searches.
CAVEATS
- Dependencies
- Python 3.8+ with required dependencies installed
- Access to a test or lab environment
- Missing context
- Desired output format or report structure
- Error handling or rate-limit guidance for crt.sh queries
- How to integrate Levenshtein distance logic (no code provided)
- Ambiguities
- Description text is truncated mid-sentence
- Does not specify how the target domain/brand should be provided as input
QUALITY
- OVERALL
- 0.70
- CLARITY
- 0.80
- SPECIFICITY
- 0.65
- REUSABILITY
- 0.75
- COMPLETENESS
- 0.60
IMPROVEMENT SUGGESTIONS
- Add a clear input parameter section (e.g., 'domain: str') so the prompt can be used as a reusable template
- Specify expected output format (e.g., JSON list of suspicious certificates with fields)
USAGE
Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.
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