[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6AFRHYFDTH0AK6PWH6RXHEE":3,"skill-same:01M6AFRHYFDTH0AK6PWH6RXHEE":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":60,"commitSha":61,"skillDirectory":62,"forksCount":63,"repositoryHtmlUrl":64,"repositoryHomepageUrl":65,"ownerHtmlUrl":66,"ownerBlogUrl":67,"ownerDescription":68,"updatedAt":69,"install":70,"resources":83},"01M6AFRHYFDTH0AK6PWH6RXHEE","performing-dns-tunneling-detection",null,"Detects DNS tunneling by computing Shannon entropy of DNS query names, analyzing query length distributions, inspecting TXT record payloads, and identifying high subdomain cardinality. Uses scapy for packet capture analysis and statistical methods to distinguish legitimate DNS from covert channels. Use when hunting for data exfiltration.","mukul975\u002FAnthropic-Cybersecurity-Skills","mukul975","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42860185?v=4","01M6ADEQR8T5M4EEG6C67BQCWF","Mahipal","01M6ADJPMYWG1E5GM1FWBE3128",35990,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fperforming-dns-tunneling-detection\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"performing dns tunneling detection","dns","tunneling","detection","scapy","shannon-entropy","analysis","t1059","DNS-analysis","t1078","entropy","security","data","analyzing","threat-detection","dns-tunneling","exfiltration","exfiltration-detection","security-operations","cybersecurity","2026-11-10 10:12:30",false,"---\nname: performing-dns-tunneling-detection\ndescription: 'Detects DNS tunneling by computing Shannon entropy of DNS query names,\n  analyzing query length distributions, inspecting TXT record payloads, and identifying\n  high subdomain cardinality. Uses scapy for packet capture analysis and statistical\n  methods to distinguish legitimate DNS from covert channels. Use when hunting for\n  data exfiltration.\n\n  '\ndomain: cybersecurity\nsubdomain: security-operations\ntags:\n- dns-tunneling\n- exfiltration-detection\n- shannon-entropy\n- dns-analysis\n- threat-detection\n- security-operations\nversion: '1.0'\nauthor: mahipal\nlicense: Apache-2.0\nnist_csf:\n- DE.CM-01\n- RS.MA-01\n- GV.OV-01\n- DE.AE-02\nmitre_attack:\n- T1078\n- T1190\n- T1059\n- T1048\n- T1041\n---\n\n# Performing DNS Tunneling Detection\n\n\n## When to Use\n\n- When conducting security assessments that involve performing dns tunneling detection\n- When following incident response procedures for related security events\n- When performing scheduled security testing or auditing activities\n- When validating security controls through hands-on testing\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\nAnalyze DNS traffic for indicators of DNS tunneling using entropy analysis and\nstatistical methods on query name characteristics.\n\n```python\nimport math\nfrom collections import Counter\n\ndef shannon_entropy(data):\n    if not data:\n        return 0\n    counter = Counter(data)\n    length = len(data)\n    return -sum((c\u002Flength) * math.log2(c\u002Flength) for c in counter.values())\n\n# Legitimate domain: low entropy (~3.0-3.5)\nprint(shannon_entropy(\"www.google.com\"))\n# DNS tunnel: high entropy (~4.0-5.0)\nprint(shannon_entropy(\"aGVsbG8gd29ybGQ.tunnel.example.com\"))\n```\n\nKey detection indicators:\n1. High Shannon entropy in query names (> 3.5 for subdomain labels)\n2. Unusually long query names (> 50 characters)\n3. High volume of TXT record requests to a single domain\n4. High unique subdomain count per parent domain\n5. Non-standard character distribution in labels\n\n## Examples\n\n```python\nfrom scapy.all import rdpcap, DNS, DNSQR\npackets = rdpcap(\"dns_traffic.pcap\")\nfor pkt in packets:\n    if pkt.haslayer(DNSQR):\n        query = pkt[DNSQR].qname.decode()\n        entropy = shannon_entropy(query)\n        if entropy > 4.0:\n            print(f\"Suspicious: {query} (entropy={entropy:.2f})\")\n```\n","# Performing DNS Tunneling Detection\n\n\n## When to Use\n\n- When conducting security assessments that involve performing dns tunneling detection\n- When following incident response procedures for related security events\n- When performing scheduled security testing or auditing activities\n- When validating security controls through hands-on testing\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\nAnalyze DNS traffic for indicators of DNS tunneling using entropy analysis and\nstatistical methods on query name characteristics.\n\n```python\nimport math\nfrom collections import Counter\n\ndef shannon_entropy(data):\n    if not data:\n        return 0\n    counter = Counter(data)\n    length = len(data)\n    return -sum((c\u002Flength) * math.log2(c\u002Flength) for c in counter.values())\n\n# Legitimate domain: low entropy (~3.0-3.5)\nprint(shannon_entropy(\"www.google.com\"))\n# DNS tunnel: high entropy (~4.0-5.0)\nprint(shannon_entropy(\"aGVsbG8gd29ybGQ.tunnel.example.com\"))\n```\n\nKey detection indicators:\n1. High Shannon entropy in query names (> 3.5 for subdomain labels)\n2. Unusually long query names (> 50 characters)\n3. High volume of TXT record requests to a single domain\n4. High unique subdomain count per parent domain\n5. Non-standard character distribution in labels\n\n## Examples\n\n```python\nfrom scapy.all import rdpcap, DNS, DNSQR\npackets = rdpcap(\"dns_traffic.pcap\")\nfor pkt in packets:\n    if pkt.haslayer(DNSQR):\n        query = pkt[DNSQR].qname.decode()\n        entropy = shannon_entropy(query)\n        if entropy > 4.0:\n            print(f\"Suspicious: {query} (entropy={entropy:.2f})\")\n```\n",{"name":5,"tags":44,"author":46,"domain":38,"license":15,"version":47,"nist_csf":48,"subdomain":37,"description":53,"mitre_attack":54},[34,36,24,45,33,37],"dns-analysis","mahipal","1.0",[49,50,51,52],"DE.CM-01","RS.MA-01","GV.OV-01","DE.AE-02","Detects DNS tunneling by computing Shannon entropy of DNS query names, analyzing query length distributions, inspecting TXT record payloads, and identifying high subdomain cardinality. Uses scapy for packet capture analysis and statistical methods to distinguish legitimate DNS from covert channels. Use when hunting for data exfiltration.\n",[55,56,57,58,59],"T1078","T1190","T1059","T1048","T1041","main","54a798831d2266a3ca61ce68a7acb80b81160d57","skills\u002Fperforming-dns-tunneling-detection",4395,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills","https:\u002F\u002Fmahipal.engineer\u002FAnthropic-Cybersecurity-Skills\u002F","https:\u002F\u002Fgithub.com\u002Fmukul975","Mahipal.engineer","🔐 Cybersecurity | 💻 Dev | 📷 Street Photographer\r\n🎓 MSc | 📚 Research & AI Security","2026-08-31 12:32:44",{"source":8,"skillName":5,"commands":71,"prompt":81,"zipAvailable":82},[72,75,78],{"tool":73,"command":74},"npx","npx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill performing-dns-tunneling-detection",{"tool":76,"command":77},"bunx","bunx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill performing-dns-tunneling-detection",{"tool":79,"command":80},"pnpm","pnpm dlx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill performing-dns-tunneling-detection","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fperforming-dns-tunneling-detection\u002FSKILL.md",true,[84,89,95],{"path":85,"resourceType":85,"resourceTypeDesc":86,"sizeBytes":87,"sourceHtmlUrl":88},"LICENSE","许可证",11255,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fperforming-dns-tunneling-detection\u002FLICENSE",{"path":90,"resourceType":91,"resourceTypeDesc":92,"sizeBytes":93,"sourceHtmlUrl":94},"references\u002Fapi-reference.md","REFERENCE","参考文档",1596,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fperforming-dns-tunneling-detection\u002Freferences\u002Fapi-reference.md",{"path":96,"resourceType":97,"resourceTypeDesc":98,"sizeBytes":99,"sourceHtmlUrl":100},"scripts\u002Fagent.py","SCRIPT","脚本",6314,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fperforming-dns-tunneling-detection\u002Fscripts\u002Fagent.py",[102,132,156,182,207,234],{"skillNo":103,"name":104,"nameZh":6,"description":105,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":106,"categories":107,"keywords":113,"publishedAt":39},"01M6AGDM3HJXTKXX15ZZ0ZVCJ3","verifying-build-provenance-with-slsa-sigstore","Verifies artifact signatures and SLSA provenance using Sigstore's cosign (verify, verify-attestation, verify-blob-attestation) and slsa-verifier (verify-artifact), enforcing keyless OIDC builder identity and source repo against SLSA Build levels. Use in CI\u002FCD before deploying artifacts, when consuming third-party attestations, establishing a SLSA Build L3 pipeline, or confirming provenance during incident response or admission control.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fverifying-build-provenance-with-slsa-sigstore\u002FSKILL.md",[108],{"categoryNo":109,"categoryName":110,"taxonomyType":111,"taxonomyTypeDesc":112},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[114,115,116,117,30,38,118,119,120,121,122,123,124,125,126,127,128,129,130,131],"sigstore","provenance","slsa","verifying build provenance with slsa sigstore","incident response","identity","pr","code","artifacts","ci","supply-chain","pipeline","supply-chain-security","t1195","attestation","code-signing","cosign","keyless",{"skillNo":133,"name":134,"nameZh":6,"description":135,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":136,"categories":137,"keywords":139,"publishedAt":39},"01M6AGDGBPWYVZ2F11GFKJ4HZ9","validating-tpm-measured-boot-attestation","Verifies TPM 2.0 measured-boot integrity and remote attestation with tpm2-tools -- reading PCRs (tpm2_pcrread), replaying the boot event log, generating and checking signed quotes (tpm2_quote\u002Ftpm2_checkquote), and sealing secrets to a PCR policy. Use to confirm a system booted trusted firmware\u002Fkernel for Zero Trust device posture, detect boot-chain tampering via PCR drift, or build a golden-value baseline for fleet attestation.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fvalidating-tpm-measured-boot-attestation\u002FSKILL.md",[138],{"categoryNo":109,"categoryName":110,"taxonomyType":111,"taxonomyTypeDesc":112},[140,128,141,142,30,143,38,120,144,145,146,147,148,149,150,151,152,153,154,155],"boot","TPM","validating tpm measured boot attestation","policy","verification","ZeRO","firmware","Tools","measured-boot","PCR","integrity","secrets","remote-attestation","tpm2-tools","integrity-verification","trusted-computing",{"skillNo":157,"name":158,"nameZh":6,"description":159,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":160,"categories":161,"keywords":166,"publishedAt":39},"01M6AGDCW0Y4FXZ3362GT1941M","validating-backup-integrity-for-recovery","Validates backup integrity through cryptographic hash verification, automated restore testing, corruption detection, and recoverability checks to confirm backups are reliable for disaster recovery and ransomware response. Use before relying on backups for recovery, when building post-backup validation pipelines, auditing backup infrastructure for compliance, or checking immutable\u002Fair-gapped backups for silent corruption or tampering.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fvalidating-backup-integrity-for-recovery\u002FSKILL.md",[162,165],{"categoryNo":163,"categoryName":164,"taxonomyType":111,"taxonomyTypeDesc":112},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":109,"categoryName":110,"taxonomyType":111,"taxonomyTypeDesc":112},[150,167,168,169,170,38,171,172,144,173,174,175,176,177,22,28,178,179,180,181],"backup","recovery","validating backup integrity for recovery","testing","infrastructure","validation","compliance","hash-verification","incident-response","ransomware","cryptocurrency","t1490","immutable","disaster-recovery","restore-testing",{"skillNo":183,"name":184,"nameZh":6,"description":185,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":186,"categories":187,"keywords":189,"publishedAt":39},"01M6AGD9GBG2KZ336AE763J3WH","triaging-windows-with-kape","Runs KAPE (Kroll Artifact Parser and Extractor) to collect targeted forensic artifacts (registry hives, $MFT, event logs, prefetch, browser data) via Targets and parse them with Modules wrapping Eric Zimmerman's EZ Tools (PECmd, MFTECmd, RECmd). Use during early incident containment\u002Ftriage when full disk imaging is impractical but a defensible, parseable Windows artifact set is needed quickly, including at-scale remote collection.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Ftriaging-windows-with-kape\u002FSKILL.md",[188],{"categoryNo":109,"categoryName":110,"taxonomyType":111,"taxonomyTypeDesc":112},[190,191,192,38,193,194,195,196,197,198,199,31,200,201,202,203,147,204,205,206],"windows","kape","triaging windows with kape","registry","browser","logs","windows-forensics","dfir","mft","mftecmd","prefetch","eric-zimmerman","digital-forensics","SET","collection","pecmd","artifact-collection",{"skillNo":208,"name":209,"nameZh":6,"description":210,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":211,"categories":212,"keywords":214,"publishedAt":39},"01M6AGD5PW5J4EVZM958WD74ZQ","triaging-vulnerabilities-with-ssvc-framework","Triages and prioritizes vulnerabilities with CISA's Stakeholder-Specific Vulnerability Categorization (SSVC) decision tree, weighing exploitation status (via the CISA KEV catalog and FIRST EPSS API), technical impact, automatability, and mission prevalence to output Track\u002FTrack*\u002FAttend\u002FAct decisions. Use when prioritizing vulnerability scan results (OpenVAS, Nessus, Qualys) for remediation planning beyond raw CVSS scores.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Ftriaging-vulnerabilities-with-ssvc-framework\u002FSKILL.md",[213],{"categoryNo":109,"categoryName":110,"taxonomyType":111,"taxonomyTypeDesc":112},[215,216,217,38,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233],"vulnerabilities","framework","triaging vulnerabilities with ssvc framework","status","planning","CISA","vulnerability-management","risk-management","nessus","qualys","openvas","cvss","remediation","risk","vulnerability","api","prioritization","ssvc","decision-tree",{"skillNo":235,"name":236,"nameZh":6,"description":237,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":238,"categories":239,"keywords":241,"publishedAt":39},"01M6AGD24TTQQM4CXG69E3B9TJ","triaging-security-incident","Performs initial triage of security incidents using the NIST SP 800-61r3 and SANS PICERL frameworks, classifying incident type, assigning priority by business impact, and routing to the appropriate response team. Use when a SIEM\u002FEDR alert needs human classification, concurrent alerts must be prioritized, or a user report or threat-intel IOC match requires initial incident categorization.","https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Ftriaging-security-incident\u002FSKILL.md",[240],{"categoryNo":109,"categoryName":110,"taxonomyType":111,"taxonomyTypeDesc":112},[30,242,38,243,244,245,246,247,248,249,250,28,251,178,25,252,253,254,255,256],"triaging security incident","siem","file","ioc","soc","NIST-800-61","NIST","severity","edr","execution","classification","severity-classification","incident-triage","SANS-PICERL","SOC-operations"]