[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6HBY2NTFPC6K72YHGHZX6EM":3,"skill-same:01M6HBY2NTFPC6K72YHGHZX6EM":101},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":62,"commitSha":63,"skillDirectory":64,"forksCount":65,"repositoryHtmlUrl":66,"repositoryHomepageUrl":6,"ownerHtmlUrl":67,"ownerBlogUrl":6,"ownerDescription":68,"updatedAt":69,"install":70,"resources":83},"01M6HBY2NTFPC6K72YHGHZX6EM","analyzing-tls-certificate-transparency-logs",null,"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....","HenriqueMC17\u002Fagente-core","HenriqueMC17","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F206460478?v=4","01M6HB63HBBF18AC4H09XTB549","Henrique Monteiro Cardoso","01M6HB63NGSQXWKWCFWW2B20W0",1,"Apache-2.0","https:\u002F\u002Fgithub.com\u002FHenriqueMC17\u002Fagente-core\u002Fblob\u002Fmain\u002Fmodules\u002Fanalyzing-tls-certificate-transparency-logs\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"logs","transparency","certificate","tls","analyzing tls certificate transparency logs","analyzing","phishing","crt-sh","ct-logs","certificate-transparency","security-operations","t1566","monitoring","brand","aml","cm","cybersecurity","domains","ov","for","2026-11-10 10:12:30",false,"---\nname: analyzing-tls-certificate-transparency-logs\ndescription: 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....\ndomain: cybersecurity\nsubdomain: security-operations\ntags:\n- certificate-transparency\n- ct-logs\n- crt-sh\n- phishing-detection\n- tls-monitoring\n- security-operations\nversion: '1.0'\nauthor: mahipal\nlicense: Apache-2.0\natlas_techniques:\n- AML.T0073\n- AML.T0052\nnist_csf:\n- DE.CM-01\n- RS.MA-01\n- GV.OV-01\n- DE.AE-02\nmitre_attack:\n- T1583.001\n- T1566.002\n- T1598.003\n- T1583.006\ncategory: analyzing-tls-certificate-transparency-logs\n---\n# Analyzing-Tls-Certificate-Transparency-Logs\n\n## Overview\nQueries 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.\n\n\n\n# Analyzing TLS Certificate Transparency Logs\n\n\n## When to Use\n\n- When investigating security incidents that require analyzing tls certificate transparency logs\n- When building detection rules or threat hunting queries for this domain\n- When SOC analysts need structured procedures for this analysis type\n- When validating security monitoring coverage for related attack techniques\n\n## Prerequisites\n\n- Familiarity with security operations concepts and tools\n- Access to a test or lab environment for safe execution\n- Python 3.8+ with required dependencies installed\n- Appropriate authorization for any testing activities\n\n## Instructions\n\nQuery crt.sh Certificate Transparency database to find certificates issued for\ndomains similar to your organization's brand, detecting phishing infrastructure.\n\n```python\nfrom pycrtsh import Crtsh\n\nc = Crtsh()\n# Search for certificates matching a domain\ncerts = c.search(\"example.com\")\nfor cert in certs:\n    print(cert[\"id\"], cert[\"name_value\"])\n\n# Get full certificate details\ndetails = c.get(certs[0][\"id\"], type=\"id\")\n```\n\nKey analysis steps:\n1. Query crt.sh for all certificates matching your domain pattern\n2. Identify certificates with typosquatting variations (Levenshtein distance)\n3. Flag certificates from unexpected CAs\n4. Monitor for wildcard certificates on suspicious subdomains\n5. Cross-reference with known phishing infrastructure\n\n## Examples\n\n```python\nfrom pycrtsh import Crtsh\nc = Crtsh()\ncerts = c.search(\"%.example.com\")\nfor cert in certs:\n    print(f\"Issuer: {cert.get('issuer_name')}, Domain: {cert.get('name_value')}\")\n```\n","# Analyzing-Tls-Certificate-Transparency-Logs\n\n## Overview\nQueries 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.\n\n\n\n# Analyzing TLS Certificate Transparency Logs\n\n\n## When to Use\n\n- When investigating security incidents that require analyzing tls certificate transparency logs\n- When building detection rules or threat hunting queries for this domain\n- When SOC analysts need structured procedures for this analysis type\n- When validating security monitoring coverage for related attack techniques\n\n## Prerequisites\n\n- Familiarity with security operations concepts and tools\n- Access to a test or lab environment for safe execution\n- Python 3.8+ with required dependencies installed\n- Appropriate authorization for any testing activities\n\n## Instructions\n\nQuery crt.sh Certificate Transparency database to find certificates issued for\ndomains similar to your organization's brand, detecting phishing infrastructure.\n\n```python\nfrom pycrtsh import Crtsh\n\nc = Crtsh()\n# Search for certificates matching a domain\ncerts = c.search(\"example.com\")\nfor cert in certs:\n    print(cert[\"id\"], cert[\"name_value\"])\n\n# Get full certificate details\ndetails = c.get(certs[0][\"id\"], type=\"id\")\n```\n\nKey analysis steps:\n1. Query crt.sh for all certificates matching your domain pattern\n2. Identify certificates with typosquatting variations (Levenshtein distance)\n3. Flag certificates from unexpected CAs\n4. Monitor for wildcard certificates on suspicious subdomains\n5. Cross-reference with known phishing infrastructure\n\n## Examples\n\n```python\nfrom pycrtsh import Crtsh\nc = Crtsh()\ncerts = c.search(\"%.example.com\")\nfor cert in certs:\n    print(f\"Issuer: {cert.get('issuer_name')}, Domain: {cert.get('name_value')}\")\n```\n",{"name":5,"tags":44,"author":47,"domain":35,"license":15,"version":48,"category":5,"nist_csf":49,"subdomain":29,"description":7,"mitre_attack":54,"atlas_techniques":59},[28,27,26,45,46,29],"phishing-detection","tls-monitoring","mahipal","1.0",[50,51,52,53],"DE.CM-01","RS.MA-01","GV.OV-01","DE.AE-02",[55,56,57,58],"T1583.001","T1566.002","T1598.003","T1583.006",[60,61],"AML.T0073","AML.T0052","main","5eea5b3296f4673b5f481e8bcc1ba76281149f16","modules\u002Fanalyzing-tls-certificate-transparency-logs",0,"https:\u002F\u002Fgithub.com\u002FHenriqueMC17\u002Fagente-core","https:\u002F\u002Fgithub.com\u002FHenriqueMC17","Qualquer tecnologia suficientemente avançada é indistinguível da mágica.","2026-09-28 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