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mukul975
efca3ec611
Mapped every skill to NIST CSF 2.0 subcategory IDs (GV/ID/PR/DE/RS/RC functions) based on subdomain and content analysis. Restores 11 skills corrupted during prior rebase, re-enriching with ATLAS, D3FEND, NIST AI RMF, and CSF 2.0 fields. All 754 skills now carry structured mappings for all 5 security frameworks: - MITRE ATT&CK (in tags) - MITRE ATLAS v5.5 (atlas_techniques) - MITRE D3FEND v1.3 (d3fend_techniques) - NIST AI RMF 1.0 (nist_ai_rmf) - NIST CSF 2.0 (nist_csf)
79 lines
2.2 KiB
Markdown
79 lines
2.2 KiB
Markdown
---
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name: analyzing-tls-certificate-transparency-logs
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description: 'Queries Certificate Transparency logs via crt.sh and pycrtsh to detect phishing domains, unauthorized certificate
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issuance, and shadow IT. Monitors newly issued certificates for typosquatting and brand impersonation using Levenshtein
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distance. Use for proactive phishing domain detection and certificate monitoring.
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'
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domain: cybersecurity
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subdomain: security-operations
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tags:
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- analyzing
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- tls
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- certificate
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- transparency
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version: '1.0'
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author: mahipal
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license: Apache-2.0
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atlas_techniques:
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- AML.T0073
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- AML.T0052
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nist_csf:
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- DE.CM-01
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- RS.MA-01
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- GV.OV-01
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- DE.AE-02
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---
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# Analyzing TLS Certificate Transparency Logs
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## When to Use
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- When investigating security incidents that require analyzing tls certificate transparency logs
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- When building detection rules or threat hunting queries for this domain
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- When SOC analysts need structured procedures for this analysis type
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- When validating security monitoring coverage for related attack techniques
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## Prerequisites
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- Familiarity with security operations concepts and tools
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- Access to a test or lab environment for safe execution
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- Python 3.8+ with required dependencies installed
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- Appropriate authorization for any testing activities
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## Instructions
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Query crt.sh Certificate Transparency database to find certificates issued for
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domains similar to your organization's brand, detecting phishing infrastructure.
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```python
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from pycrtsh import Crtsh
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c = Crtsh()
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# Search for certificates matching a domain
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certs = c.search("example.com")
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for cert in certs:
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print(cert["id"], cert["name_value"])
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# Get full certificate details
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details = c.get(certs[0]["id"], type="id")
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```
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Key analysis steps:
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1. Query crt.sh for all certificates matching your domain pattern
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2. Identify certificates with typosquatting variations (Levenshtein distance)
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3. Flag certificates from unexpected CAs
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4. Monitor for wildcard certificates on suspicious subdomains
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5. Cross-reference with known phishing infrastructure
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## Examples
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```python
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from pycrtsh import Crtsh
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c = Crtsh()
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certs = c.search("%.example.com")
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for cert in certs:
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print(f"Issuer: {cert.get('issuer_name')}, Domain: {cert.get('name_value')}")
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```
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