mirror of
https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git
synced 2026-07-13 19:05:17 +03:00
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)
2.2 KiB
2.2 KiB
name, description, domain, subdomain, tags, version, author, license, atlas_techniques, nist_csf
| name | description | domain | subdomain | tags | version | author | license | atlas_techniques | nist_csf | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| analyzing-tls-certificate-transparency-logs | 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. | cybersecurity | security-operations |
|
1.0 | mahipal | Apache-2.0 |
|
|
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')}")