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Prompts TLS Certificate Transparency Log Analyzer

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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