[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71FD9MAS4E6VPEZ8VQWP24X":3,"skill-same:01M71FD9MAS4E6VPEZ8VQWP24X":55},{"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":23,"linkOnly":24,"markdownContent":25,"markdownBody":26,"frontMatter":27,"refName":28,"commitSha":29,"skillDirectory":30,"forksCount":14,"repositoryHtmlUrl":31,"repositoryHomepageUrl":6,"ownerHtmlUrl":32,"ownerBlogUrl":6,"ownerDescription":33,"updatedAt":34,"install":35,"resources":48},"01M71FD9MAS4E6VPEZ8VQWP24X","net-flow-beaconing",null,"Net Flow Beaconing.","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\u002Fnet-flow-beaconing\u002FSKILL.md",[],[19,20,21,22],"flow","beaconing","net flow beaconing","cybersecurity","2026-11-10 10:12:30",false,"---\nname: net-flow-beaconing\ndescription: \"Net Flow Beaconing.\"\ndomain: cybersecurity\n---\n\n|\n| RITA (Real Intelligence Threat Analytics) | Automated beacon scoring from Zeek logs |\n| AC-Hunter | Commercial threat hunting platform with beacon detection |\n| Splunk | SPL-based statistical beacon analysis with streamstats |\n| Elastic Security | ML anomaly detection for periodic network behavior |\n| Zeek | Network metadata collection (conn.log, dns.log, ssl.log) |\n| Suricata | Network IDS with JA3\u002FJA4 TLS fingerprint extraction |\n| FLARE | C2 profile and beacon pattern detection |\n| VirusTotal | Domain and IP reputation enrichment |\n\n## Detection Queries\n\n### Splunk -- HTTP\u002FS Beacon Frequency Analysis\n```spl\nindex=proxy OR index=firewall\n| where NOT match(dest, \"(?i)(microsoft|google|amazonaws|cloudflare|akamai)\")\n| bin _time span=1s\n| stats count by src_ip dest _time\n| streamstats current=f last(_time) as prev_time by src_ip dest\n| eval interval=_time-prev_time\n| stats count avg(interval) as avg_interval stdev(interval) as stdev_interval\n  min(interval) as min_interval max(interval) as max_interval by src_ip dest\n| where count > 50\n| eval cv=stdev_interval\u002Favg_interval\n| where cv \u003C 0.20 AND avg_interval > 30 AND avg_interval \u003C 86400\n| sort cv\n| table src_ip dest count avg_interval stdev_interval cv\n```\n\n### KQL -- Microsoft Sentinel Beacon Detection\n```kql\nDeviceNetworkEvents\n| where Timestamp > ago(24h)\n| where RemoteIPType == \"Public\"\n| summarize ConnectionTimes=make_list(Timestamp), Count=count() by DeviceName, RemoteIP, RemoteUrl\n| where Count > 50\n| extend Intervals = array_sort_asc(ConnectionTimes)\n| mv-apply Intervals on (\n    extend NextTime = next(Intervals)\n    | where isnotempty(NextTime)\n    | extend IntervalSec = datetime_diff('second', NextTime, Intervals)\n    | summarize AvgInterval=avg(IntervalSec), StdDev=stdev(IntervalSec)\n)\n| extend CV = StdDev \u002F AvgInterval\n| where CV \u003C 0.2 and AvgInterval > 30\n| sort by CV asc\n```\n\n### Sigma Rule -- Beaconing Pattern Detection\n```yaml\ntitle: Potential C2 Beaconing Pattern Detected\nstatus: experimental\nlogsource:\n    category: proxy\ndetection:\n    selection:\n        dst_ip|cidr: '!10.0.0.0\u002F8'\n    timeframe: 24h\n    condition: selection | count(dst) by src_ip > 50\nlevel: medium\ntags:\n    - attack.command_and_control\n    - attack.t1071.001\n```\n\n## Common Scenarios\n\n1. **Cobalt Strike Beacon**: Default 60-second interval with configurable 0-50% jitter over HTTPS. Malleable C2 profiles can mimic legitimate traffic patterns.\n2. **Sunburst\u002FSUNSPOT**: 12-14 day dormancy period, then beaconing every 12-14 minutes with randomized jitter, designed to evade frequency analysis.\n3. **DNS Tunneling C2**: Encoded data exfiltration via DNS TXT\u002FCNAME queries to attacker-controlled domains, detectable via high subdomain entropy and query volume.\n4. **Sliver C2**: Modern C2 framework with HTTPS, mTLS, and WireGuard protocols, configurable beacon intervals with built-in jitter support.\n5. **Legitimate Service Abuse**: C2 communication over Slack, Discord, Telegram, or cloud storage APIs, making destination-based filtering ineffective.\n\n## Output Format\n\n```\nHunt ID: TH-BEACON-[DATE]-[SEQ]\nSource IP: [Internal IP]\nSource Host: [Hostname from DHCP\u002FDNS]\nDestination: [Domain\u002FIP]\nProtocol: [HTTP\u002FHTTPS\u002FDNS]\nBeacon Interval: [Average seconds]\nJitter Estimate: [Percentage]\nCoefficient of Variation: [CV value]\nConnection Count: [Total connections in window]\nData Size CV: [Payload consistency metric]\nDomain Age: [Days since registration]\nTI Match: [Yes\u002FNo -- source]\nRisk Score: [0-100]\nRisk Level: [Critical\u002FHigh\u002FMedium\u002FLow]\nIndicators: [List of triggered risk factors]\n```\n","|\n| RITA (Real Intelligence Threat Analytics) | Automated beacon scoring from Zeek logs |\n| AC-Hunter | Commercial threat hunting platform with beacon detection |\n| Splunk | SPL-based statistical beacon analysis with streamstats |\n| Elastic Security | ML anomaly detection for periodic network behavior |\n| Zeek | Network metadata collection (conn.log, dns.log, ssl.log) |\n| Suricata | Network IDS with JA3\u002FJA4 TLS fingerprint extraction |\n| FLARE | C2 profile and beacon pattern detection |\n| VirusTotal | Domain and IP reputation enrichment |\n\n## Detection Queries\n\n### Splunk -- HTTP\u002FS Beacon Frequency Analysis\n```spl\nindex=proxy OR index=firewall\n| where NOT match(dest, \"(?i)(microsoft|google|amazonaws|cloudflare|akamai)\")\n| bin _time span=1s\n| stats count by src_ip dest _time\n| streamstats current=f last(_time) as prev_time by src_ip dest\n| eval interval=_time-prev_time\n| stats count avg(interval) as avg_interval stdev(interval) as stdev_interval\n  min(interval) as min_interval max(interval) as max_interval by src_ip dest\n| where count > 50\n| eval cv=stdev_interval\u002Favg_interval\n| where cv \u003C 0.20 AND avg_interval > 30 AND avg_interval \u003C 86400\n| sort cv\n| table src_ip dest count avg_interval stdev_interval cv\n```\n\n### KQL -- Microsoft Sentinel Beacon Detection\n```kql\nDeviceNetworkEvents\n| where Timestamp > ago(24h)\n| where RemoteIPType == \"Public\"\n| summarize ConnectionTimes=make_list(Timestamp), Count=count() by DeviceName, RemoteIP, RemoteUrl\n| where Count > 50\n| extend Intervals = array_sort_asc(ConnectionTimes)\n| mv-apply Intervals on (\n    extend NextTime = next(Intervals)\n    | where isnotempty(NextTime)\n    | extend IntervalSec = datetime_diff('second', NextTime, Intervals)\n    | summarize AvgInterval=avg(IntervalSec), StdDev=stdev(IntervalSec)\n)\n| extend CV = StdDev \u002F AvgInterval\n| where CV \u003C 0.2 and AvgInterval > 30\n| sort by CV asc\n```\n\n### Sigma Rule -- Beaconing Pattern Detection\n```yaml\ntitle: Potential C2 Beaconing Pattern Detected\nstatus: experimental\nlogsource:\n    category: proxy\ndetection:\n    selection:\n        dst_ip|cidr: '!10.0.0.0\u002F8'\n    timeframe: 24h\n    condition: selection | count(dst) by src_ip > 50\nlevel: medium\ntags:\n    - attack.command_and_control\n    - attack.t1071.001\n```\n\n## Common Scenarios\n\n1. **Cobalt Strike Beacon**: Default 60-second interval with configurable 0-50% jitter over HTTPS. Malleable C2 profiles can mimic legitimate traffic patterns.\n2. **Sunburst\u002FSUNSPOT**: 12-14 day dormancy period, then beaconing every 12-14 minutes with randomized jitter, designed to evade frequency analysis.\n3. **DNS Tunneling C2**: Encoded data exfiltration via DNS TXT\u002FCNAME queries to attacker-controlled domains, detectable via high subdomain entropy and query volume.\n4. **Sliver C2**: Modern C2 framework with HTTPS, mTLS, and WireGuard protocols, configurable beacon intervals with built-in jitter support.\n5. **Legitimate Service Abuse**: C2 communication over Slack, Discord, Telegram, or cloud storage APIs, making destination-based filtering ineffective.\n\n## Output Format\n\n```\nHunt ID: TH-BEACON-[DATE]-[SEQ]\nSource IP: [Internal IP]\nSource Host: [Hostname from DHCP\u002FDNS]\nDestination: [Domain\u002FIP]\nProtocol: [HTTP\u002FHTTPS\u002FDNS]\nBeacon Interval: [Average seconds]\nJitter Estimate: [Percentage]\nCoefficient of Variation: [CV value]\nConnection Count: [Total connections in window]\nData Size CV: [Payload consistency metric]\nDomain Age: [Days since registration]\nTI Match: [Yes\u002FNo -- source]\nRisk Score: [0-100]\nRisk Level: [Critical\u002FHigh\u002FMedium\u002FLow]\nIndicators: [List of triggered risk factors]\n```\n",{"name":5,"domain":22,"description":7},"main","a91f1293287ffa9f4f1b8f486cd6e835a1568c84","skills\u002Fnet-flow-beaconing","https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace","https:\u002F\u002Fgithub.com\u002FDCx7C5","#Python","2026-09-01 11:21:00",{"source":8,"skillName":5,"commands":36,"prompt":46,"zipAvailable":47},[37,40,43],{"tool":38,"command":39},"npx","npx skills add DCx7C5\u002Fai-marketplace --skill net-flow-beaconing",{"tool":41,"command":42},"bunx","bunx skills add DCx7C5\u002Fai-marketplace --skill net-flow-beaconing",{"tool":44,"command":45},"pnpm","pnpm dlx skills add DCx7C5\u002Fai-marketplace --skill net-flow-beaconing","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fnet-flow-beaconing\u002FSKILL.md",true,[49],{"path":50,"resourceType":51,"resourceTypeDesc":52,"sizeBytes":53,"sourceHtmlUrl":54},"index.json","REFERENCE","参考文档",472,"https:\u002F\u002Fgithub.com\u002FDCx7C5\u002Fai-marketplace\u002Fblob\u002Fmain\u002Fskills\u002Fnet-flow-beaconing\u002Findex.json",[56,81,104,126,148,164],{"skillNo":57,"name":58,"nameZh":6,"description":59,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":60,"categories":61,"keywords":62,"publishedAt":23},"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",[],[63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,22,80],"services","detect","services wmi persistence detect","wmi","persistence","de","cm","process","activescript","event","subscriptions","commandline-consumer","repository","subscription","event-subscription","t1546.003","forensics","process-forensics",{"skillNo":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":85,"categories":86,"keywords":87,"publishedAt":23},"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",[],[88,63,89,66,90,91,92,22,93,94,95,96,97,98,68,99,100,101,102,103],"exploit","services wmi exec exploit","exec","remote","traffic","Bash","analysis","team","across","crackmapexec","native","command","lateral movement","read","lateral-movement","Impacket",{"skillNo":105,"name":106,"nameZh":6,"description":107,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":108,"categories":109,"keywords":110,"publishedAt":23},"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",[],[111,112,113,114,115,116,22,93,117,94,118,119,68,101,120,121,122,123,124,125],"artifact","registry","registry artifact extract","extract","evidence-collection","artifact-analysis","collection","analyze","uncover","software","activity","digital-forensics","windows-registry","regripper","sonnet",{"skillNo":127,"name":128,"nameZh":6,"description":129,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":130,"categories":131,"keywords":132,"publishedAt":23},"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",[],[64,133,134,135,136,137,138,69,139,22,80,140,141,142,143,144,145,146,147,68],"processes token impersonate detect","token","processes","attacks","windows","escalation","techniques","privilege-escalation","seimpersonate","token-impersonation","printspoofer","exploitation","potato","impersonation","via",{"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":23},"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",[],[155,156,64,157,135,137,158,69,159,139,22,80,94,160,161,162,163,147,68,70],"thread","processes thread injection detect","injection","memory","process-injection","api","apc-injection","thread-injection","nt-api",{"skillNo":165,"name":166,"nameZh":6,"description":167,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":168,"categories":169,"keywords":170,"publishedAt":23},"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",[],[171,64,135,172,158,69,173,174,22,80,175,176,177,178,179,180,68,70,181,182],"processes hollow technique detect","tree","memory-forensics","process-hollow","peb","runpe","image","pe-header","in memory","with","mismatched","headers"]