[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6AFY013B84ZT5XPJSRN3FQ9":3,"skill-same:01M6AFY013B84ZT5XPJSRN3FQ9":102},{"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":61,"commitSha":62,"skillDirectory":63,"forksCount":64,"repositoryHtmlUrl":65,"repositoryHomepageUrl":66,"ownerHtmlUrl":67,"ownerBlogUrl":68,"ownerDescription":69,"updatedAt":70,"install":71,"resources":84},"01M6AFY013B84ZT5XPJSRN3FQ9","performing-network-traffic-analysis-with-tshark",null,"Automate network traffic analysis using tshark (Wireshark CLI) and pyshark to compute protocol distribution statistics, detect suspicious flows such as port scans and beaconing, extract IOCs (IPs, domains, URLs), and identify DNS tunneling patterns from PCAP files. Use when scripted or repeatable analysis of packet captures is needed rather than interactive inspection.","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-network-traffic-analysis-with-tshark\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"performing network traffic analysis with tshark","tshark","analysis","network","packet-analysis","pyshark","beaconing","tunneling","ips","network-security","Wireshark","cli","network-forensics","dns","forensics","protocol","pr","cybersecurity","security","suspicious","2026-11-10 10:12:30",false,"---\nname: performing-network-traffic-analysis-with-tshark\ndescription: Automate network traffic analysis using tshark (Wireshark CLI) and pyshark to compute protocol distribution statistics, detect suspicious flows such as port scans and beaconing, extract IOCs (IPs, domains, URLs), and identify DNS tunneling patterns from PCAP files. Use when scripted or repeatable analysis of packet captures is needed rather than interactive inspection.\ndomain: cybersecurity\nsubdomain: network-security\ntags:\n- tshark\n- pyshark\n- pcap\n- packet-analysis\n- network-forensics\n- wireshark\n- traffic-analysis\nversion: '1.0'\nauthor: mahipal\nlicense: Apache-2.0\nnist_csf:\n- PR.IR-01\n- DE.CM-01\n- ID.AM-03\n- PR.DS-02\nmitre_attack:\n- T1046\n- T1040\n- T1557\n- T1071\n- T1005\n---\n\n# Performing Network Traffic Analysis with TShark\n\n## Overview\n\nThis skill automates packet capture analysis using tshark (Wireshark CLI) and pyshark (Python wrapper). It extracts protocol distribution statistics, identifies suspicious network flows (port scans, beaconing, data exfiltration), extracts IOCs (IPs, domains, URLs), and detects DNS tunneling patterns from PCAP files.\n\n\n## When to Use\n\n- When conducting security assessments that involve performing network traffic analysis with tshark\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- tshark (Wireshark CLI) installed and in PATH\n- Python 3.8+ with pyshark library\n- PCAP or PCAPNG capture file for analysis\n\n## Steps\n\n1. **Extract Protocol Statistics** — Generate protocol hierarchy and conversation statistics from the capture\n2. **Identify Top Talkers** — Rank source\u002Fdestination IPs by volume and connection count\n3. **Detect Suspicious Flows** — Flag port scanning patterns, unusual port usage, and high-frequency connections\n4. **Extract Network IOCs** — Pull unique IPs, domains from DNS queries, and URLs from HTTP traffic\n5. **Analyze DNS Traffic** — Detect DNS tunneling via high-entropy subdomain queries and excessive TXT records\n6. **Generate Analysis Report** — Produce structured report with flow summaries and threat indicators\n\n## Expected Output\n\n- JSON report with protocol statistics and top talkers\n- Suspicious flow detections with severity ratings\n- Extracted IOCs (IPs, domains, URLs)\n- DNS anomaly analysis results\n","# Performing Network Traffic Analysis with TShark\n\n## Overview\n\nThis skill automates packet capture analysis using tshark (Wireshark CLI) and pyshark (Python wrapper). It extracts protocol distribution statistics, identifies suspicious network flows (port scans, beaconing, data exfiltration), extracts IOCs (IPs, domains, URLs), and detects DNS tunneling patterns from PCAP files.\n\n\n## When to Use\n\n- When conducting security assessments that involve performing network traffic analysis with tshark\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- tshark (Wireshark CLI) installed and in PATH\n- Python 3.8+ with pyshark library\n- PCAP or PCAPNG capture file for analysis\n\n## Steps\n\n1. **Extract Protocol Statistics** — Generate protocol hierarchy and conversation statistics from the capture\n2. **Identify Top Talkers** — Rank source\u002Fdestination IPs by volume and connection count\n3. **Detect Suspicious Flows** — Flag port scanning patterns, unusual port usage, and high-frequency connections\n4. **Extract Network IOCs** — Pull unique IPs, domains from DNS queries, and URLs from HTTP traffic\n5. **Analyze DNS Traffic** — Detect DNS tunneling via high-entropy subdomain queries and excessive TXT records\n6. **Generate Analysis Report** — Produce structured report with flow summaries and threat indicators\n\n## Expected Output\n\n- JSON report with protocol statistics and top talkers\n- Suspicious flow detections with severity ratings\n- Extracted IOCs (IPs, domains, URLs)\n- DNS anomaly analysis results\n",{"name":5,"tags":44,"author":48,"domain":36,"license":15,"version":49,"nist_csf":50,"subdomain":28,"description":7,"mitre_attack":55},[20,24,45,23,31,46,47],"pcap","wireshark","traffic-analysis","mahipal","1.0",[51,52,53,54],"PR.IR-01","DE.CM-01","ID.AM-03","PR.DS-02",[56,57,58,59,60],"T1046","T1040","T1557","T1071","T1005","main","54a798831d2266a3ca61ce68a7acb80b81160d57","skills\u002Fperforming-network-traffic-analysis-with-tshark",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":72,"prompt":82,"zipAvailable":83},[73,76,79],{"tool":74,"command":75},"npx","npx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill performing-network-traffic-analysis-with-tshark",{"tool":77,"command":78},"bunx","bunx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill performing-network-traffic-analysis-with-tshark",{"tool":80,"command":81},"pnpm","pnpm dlx skills add mukul975\u002FAnthropic-Cybersecurity-Skills --skill performing-network-traffic-analysis-with-tshark","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fperforming-network-traffic-analysis-with-tshark\u002FSKILL.md",true,[85,90,96],{"path":86,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":88,"sourceHtmlUrl":89},"LICENSE","许可证",11255,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fperforming-network-traffic-analysis-with-tshark\u002FLICENSE",{"path":91,"resourceType":92,"resourceTypeDesc":93,"sizeBytes":94,"sourceHtmlUrl":95},"references\u002Fapi-reference.md","REFERENCE","参考文档",2117,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fperforming-network-traffic-analysis-with-tshark\u002Freferences\u002Fapi-reference.md",{"path":97,"resourceType":98,"resourceTypeDesc":99,"sizeBytes":100,"sourceHtmlUrl":101},"scripts\u002Fagent.py","SCRIPT","脚本",8391,"https:\u002F\u002Fgithub.com\u002Fmukul975\u002FAnthropic-Cybersecurity-Skills\u002Fblob\u002Fmain\u002Fskills\u002Fperforming-network-traffic-analysis-with-tshark\u002Fscripts\u002Fagent.py",[103,132,156,184,210,237],{"skillNo":104,"name":105,"nameZh":6,"description":106,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":107,"categories":108,"keywords":114,"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",[109],{"categoryNo":110,"categoryName":111,"taxonomyType":112,"taxonomyTypeDesc":113},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[115,116,117,118,37,36,119,120,35,121,122,123,124,125,126,127,128,129,130,131],"sigstore","provenance","slsa","verifying build provenance with slsa sigstore","incident response","identity","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":110,"categoryName":111,"taxonomyType":112,"taxonomyTypeDesc":113},[140,128,141,142,37,143,36,35,144,145,146,147,148,149,150,151,152,153,154,155],"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":112,"taxonomyTypeDesc":113},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":110,"categoryName":111,"taxonomyType":112,"taxonomyTypeDesc":113},[150,167,168,169,170,36,171,172,144,173,174,175,176,177,178,179,180,181,182,183],"backup","recovery","validating backup integrity for recovery","testing","infrastructure","validation","compliance","hash-verification","incident-response","ransomware","cryptocurrency","detection","t1078","t1490","immutable","disaster-recovery","restore-testing",{"skillNo":185,"name":186,"nameZh":6,"description":187,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":188,"categories":189,"keywords":191,"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",[190],{"categoryNo":110,"categoryName":111,"taxonomyType":112,"taxonomyTypeDesc":113},[192,193,194,36,195,196,197,198,199,200,201,202,203,204,205,206,147,207,208,209],"windows","kape","triaging windows with kape","registry","browser","logs","windows-forensics","dfir","mft","mftecmd","data","prefetch","eric-zimmerman","digital-forensics","SET","collection","pecmd","artifact-collection",{"skillNo":211,"name":212,"nameZh":6,"description":213,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":214,"categories":215,"keywords":217,"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",[216],{"categoryNo":110,"categoryName":111,"taxonomyType":112,"taxonomyTypeDesc":113},[218,219,220,36,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236],"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":238,"name":239,"nameZh":6,"description":240,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":241,"categories":242,"keywords":244,"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",[243],{"categoryNo":110,"categoryName":111,"taxonomyType":112,"taxonomyTypeDesc":113},[37,245,36,246,247,248,249,250,251,252,253,179,254,180,21,255,256,257,258,259],"triaging security incident","siem","file","ioc","soc","NIST-800-61","NIST","severity","edr","execution","classification","severity-classification","incident-triage","SANS-PICERL","SOC-operations"]