[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71FS7T3AWEEFDAXX3BDAA51":3,"skill-same:01M71FS7T3AWEEFDAXX3BDAA51":86},{"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":59,"commitSha":60,"skillDirectory":61,"forksCount":14,"repositoryHtmlUrl":62,"repositoryHomepageUrl":6,"ownerHtmlUrl":63,"ownerBlogUrl":6,"ownerDescription":64,"updatedAt":65,"install":66,"resources":79},"01M71FS7T3AWEEFDAXX3BDAA51","traffic-arkime-detect",null,"Deploy and query Arkime (formerly Moloch) for full packet capture network traffic analysis. Uses the Arkime API v3 to search sessions, download PCAPs, analyze connection patterns, detect beaconing behavior, and identify suspicious network flows. Monitors DNS queries, HTTP traffic, and TLS certificate anomalies across captured traffic.","DCx7C5\u002Fai-marketplace","DCx7C5","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F42419559?v=4","01M71C01G2AZV3NTNGWAWSHJPP","DC","01M71C01GQW6G50S2BYMS7PP3E",0,"MIT","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fnetwork\u002Ftraffic\u002Farkime\u002Fdetect\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"traffic arkime detect","traffic","detect","arkime","analyze","implementing","flows","de","across","query","cm","suspicious","Bash","api","analysis","beaconing","tls","dns","search","cybersecurity","2026-11-10 10:12:30",false,"---\nname: traffic-arkime-detect\ndescription: Deploy and query Arkime (formerly Moloch) for full packet capture network traffic analysis. Uses the Arkime API v3 to search sessions, download PCAPs, analyze connection patterns, detect beaconing behavior, and identify suspicious network flows. Monitors DNS queries, HTTP traffic, and TLS certificate anomalies across captured traffic.\ndomain: cybersecurity\nsubdomain: network-security\ntags:\n- implementing\n- network\n- traffic\n- analysis\nnist_csf:\n- PR.IR-01\n- DE.CM-01\n- ID.AM-03\n- PR.DS-02\nmodel: sonnet\nmaxTurns: 20\ntools: [Read, Bash, Glob, Grep]\ncapec: []\n---\n\n# Implementing Network Traffic Analysis with Arkime\n\n\n## When to Use\n\n- When deploying or configuring implementing network traffic analysis with arkime capabilities in your environment\n- When establishing security controls aligned to compliance requirements\n- When building or improving security architecture for this domain\n- When conducting security assessments that require this implementation\n\n## Prerequisites\n\n- Familiarity with network security 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\n1. Install dependencies: `pip install requests`\n2. Configure Arkime viewer URL and credentials.\n3. Run the agent to query Arkime sessions and analyze traffic:\n   - Search sessions by IP, port, protocol, or expression\n   - Download PCAP data for forensic analysis\n   - Detect C2 beaconing via connection interval analysis\n   - Identify DNS tunneling through query length statistics\n   - Flag connections to known-bad TLS certificate issuers\n\n```bash\npython scripts\u002Fagent.py --arkime-url https:\u002F\u002Farkime.local:8005 --user admin --password secret --output arkime_report.json\n```\n\n## Examples\n\n### Beaconing Detection\n```\nSource: 10.1.2.50 -> 185.220.101.34:443\nSessions: 288 over 24 hours\nAvg interval: 300s, Jitter: 4.2%\nVerdict: HIGH confidence C2 beaconing (jitter \u003C 5%)\n```\n","# Implementing Network Traffic Analysis with Arkime\n\n\n## When to Use\n\n- When deploying or configuring implementing network traffic analysis with arkime capabilities in your environment\n- When establishing security controls aligned to compliance requirements\n- When building or improving security architecture for this domain\n- When conducting security assessments that require this implementation\n\n## Prerequisites\n\n- Familiarity with network security 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\n1. Install dependencies: `pip install requests`\n2. Configure Arkime viewer URL and credentials.\n3. Run the agent to query Arkime sessions and analyze traffic:\n   - Search sessions by IP, port, protocol, or expression\n   - Download PCAP data for forensic analysis\n   - Detect C2 beaconing via connection interval analysis\n   - Identify DNS tunneling through query length statistics\n   - Flag connections to known-bad TLS certificate issuers\n\n```bash\npython scripts\u002Fagent.py --arkime-url https:\u002F\u002Farkime.local:8005 --user admin --password secret --output arkime_report.json\n```\n\n## Examples\n\n### Beaconing Detection\n```\nSource: 10.1.2.50 -> 185.220.101.34:443\nSessions: 288 over 24 hours\nAvg interval: 300s, Jitter: 4.2%\nVerdict: HIGH confidence C2 beaconing (jitter \u003C 5%)\n```\n",{"name":5,"tags":44,"capec":46,"model":47,"tools":48,"domain":38,"maxTurns":52,"nist_csf":53,"subdomain":58,"description":7},[24,45,20,33],"network",[],"sonnet",[49,31,50,51],"Read","Glob","Grep",20,[54,55,56,57],"PR.IR-01","DE.CM-01","ID.AM-03","PR.DS-02","network-security","main","a91f1293287ffa9f4f1b8f486cd6e835a1568c84","skills\u002Fnetwork\u002Ftraffic\u002Farkime\u002Fdetect","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace","https:\u002F\u002Fgithub.com\u002FDCx7C5","#Python","2026-09-01 11:21:00",{"source":8,"skillName":5,"commands":67,"prompt":77,"zipAvailable":78},[68,71,74],{"tool":69,"command":70},"npx","npx skills add DCx7C5\u002Fai-marketplace --skill traffic-arkime-detect",{"tool":72,"command":73},"bunx","bunx skills add DCx7C5\u002Fai-marketplace --skill traffic-arkime-detect",{"tool":75,"command":76},"pnpm","pnpm dlx skills add DCx7C5\u002Fai-marketplace --skill traffic-arkime-detect","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fnetwork\u002Ftraffic\u002Farkime\u002Fdetect\u002FSKILL.md",true,[80],{"path":81,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":84,"sourceHtmlUrl":85},"index.json","REFERENCE","参考文档",678,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fnetwork\u002Ftraffic\u002Farkime\u002Fdetect\u002Findex.json",[87,109,128,148,170,185],{"skillNo":88,"name":89,"nameZh":6,"description":90,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":91,"categories":92,"keywords":93,"publishedAt":39},"01M71HAPZ01KQ30RKTB0FFSQ05","services-wmi-persistence-detect","Detect WMI event subscription persistence by enumerating ActiveScriptEventConsumer, CommandLineEventConsumer, and permanent subscriptions in the WMI repository.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fservices\u002Fwmi\u002Fpersistence\u002Fdetect\u002FSKILL.md",[],[94,21,95,96,97,26,29,98,99,100,101,102,103,104,105,106,107,38,108],"services","services wmi persistence detect","wmi","persistence","process","activescript","event","subscriptions","commandline-consumer","repository","subscription","event-subscription","t1546.003","forensics","process-forensics",{"skillNo":110,"name":111,"nameZh":6,"description":112,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":113,"categories":114,"keywords":115,"publishedAt":39},"01M71HAK6JTTTS229T17WJMMCG","services-wmi-exec-exploit","Perform lateral movement across Windows networks using WMI-based remote execution techniques including Impacket wmiexec.py, CrackMapExec, and native WMI commands for stealthy post-exploitation during red team engagements.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fservices\u002Fwmi\u002Fexec\u002Fexploit\u002FSKILL.md",[],[116,94,117,96,118,119,20,38,31,33,120,27,121,122,26,123,124,125,126,127],"exploit","services wmi exec exploit","exec","remote","team","crackmapexec","native","command","lateral movement","read","lateral-movement","Impacket",{"skillNo":129,"name":130,"nameZh":6,"description":131,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":132,"categories":133,"keywords":134,"publishedAt":39},"01M71HAG6MHKNQV8KDZKMT4886","registry-artifact-extract","Extract and analyze Windows Registry hives to uncover user activity, installed software, autostart entries, and evidence of system compromise.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fregistry\u002Fartifact\u002Fextract\u002FSKILL.md",[],[135,136,137,138,139,140,38,31,141,33,23,142,26,125,143,144,145,146,147,47],"artifact","registry","registry artifact extract","extract","evidence-collection","artifact-analysis","collection","uncover","software","activity","digital-forensics","windows-registry","regripper",{"skillNo":149,"name":150,"nameZh":6,"description":151,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":152,"categories":153,"keywords":154,"publishedAt":39},"01M71HACR4A8XTWTTSXK4124AA","processes-token-impersonate-detect","Detect Windows token impersonation and privilege abuse including SeImpersonatePrivilege exploitation via Potato attacks and token stealing techniques.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fprocesses\u002Ftoken\u002Fimpersonate\u002Fdetect\u002FSKILL.md",[],[21,155,156,157,158,159,160,29,161,38,108,162,163,164,165,166,167,168,169,26],"processes token impersonate detect","token","processes","attacks","windows","escalation","techniques","privilege-escalation","seimpersonate","token-impersonation","printspoofer","exploitation","potato","impersonation","via",{"skillNo":171,"name":172,"nameZh":6,"description":173,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":174,"categories":175,"keywords":176,"publishedAt":39},"01M71HAABSB4Z6QFSXEG00R4RK","processes-thread-injection-detect","Detect Windows thread injection techniques including CreateRemoteThread, QueueUserAPC, NtCreateThreadEx, and thread hijacking via process memory analysis.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fprocesses\u002Fthread\u002Finjection\u002Fdetect\u002FSKILL.md",[],[177,178,21,179,157,159,180,29,181,161,38,108,33,32,182,183,184,169,26,98],"thread","processes thread injection detect","injection","memory","process-injection","apc-injection","thread-injection","nt-api",{"skillNo":186,"name":187,"nameZh":6,"description":188,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":189,"categories":190,"keywords":191,"publishedAt":39},"01M71HA7H311V5G14WMX58HQSS","processes-hollow-technique-detect","Detect process hollowing (RunPE) by identifying processes with mismatched image paths between PEB and VAD tree, or unmapped PE headers in memory.","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fwindows\u002Fprocesses\u002Fhollow\u002Ftechnique\u002Fdetect\u002FSKILL.md",[],[192,21,157,193,180,29,194,195,38,108,196,197,198,199,200,201,26,98,202,203],"processes hollow technique detect","tree","memory-forensics","process-hollow","peb","runpe","image","pe-header","in memory","with","mismatched","headers"]