用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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基于 SOC 职业分类
| name | hunting-for-beaconing-with-frequency-analysis |
| description | 通过对网络流量应用统计频率分析、抖动计算和变异系数评分,识别命令与控制(C2)信标模式,检测被攻陷终端的周期性回调行为。 |
| domain | cybersecurity |
| subdomain | threat-hunting |
| tags | ["threat-hunting","beaconing","c2-detection","frequency-analysis","network-traffic","RITA","jitter-detection","mitre-t1071"] |
| version | 1.0 |
| author | mahipal |
| license | Apache-2.0 |
| 概念 | 描述 |
|---|---|
| T1071.001 | 应用层协议:Web 协议——HTTP/HTTPS 信标 |
| T1071.004 | 应用层协议:DNS——基于 DNS 的 C2 隧道 |
| T1573 | 加密通道——TLS/SSL 加密的 C2 通信 |
| T1568.002 | 动态解析:域名生成算法(DGA) |
| 变异系数(CV) | 标准差除以均值;低于 0.20 表示周期性 |
| 抖动(Jitter) | 向信标间隔添加的随机变化,用于规避检测 |
| RITA 信标评分 | 综合连接规律性、数据量一致性和连接数的评分 |
| JA3/JA4 指纹 | TLS 客户端指纹,用于识别 C2 框架签名 |
| Fast-Flux DNS | 快速变化的 DNS 解析,用于保护 C2 基础设施 |
| 工具 | 用途 |
|---|---|
| RITA(Real Intelligence Threat Analytics) | 基于 Zeek 日志的自动化信标评分 |
| AC-Hunter | 带信标检测的商业威胁狩猎平台 |
| Splunk | 使用 streamstats 进行基于 SPL 的统计信标分析 |
| Elastic Security | 周期性网络行为的 ML 异常检测 |
| Zeek | 网络元数据收集(conn.log、dns.log、ssl.log) |
| Suricata | 带 JA3/JA4 TLS 指纹提取的网络 IDS |
| FLARE | C2 配置文件和信标模式检测 |
| VirusTotal | 域名和 IP 信誉丰富化 |
index=proxy OR index=firewall
| where NOT match(dest, "(?i)(microsoft|google|amazonaws|cloudflare|akamai)")
| bin _time span=1s
| stats count by src_ip dest _time
| streamstats current=f last(_time) as prev_time by src_ip dest
| eval interval=_time-prev_time
| stats count avg(interval) as avg_interval stdev(interval) as stdev_interval
min(interval) as min_interval max(interval) as max_interval by src_ip dest
| where count > 50
| eval cv=stdev_interval/avg_interval
| where cv < 0.20 AND avg_interval > 30 AND avg_interval < 86400
| sort cv
| table src_ip dest count avg_interval stdev_interval cv
DeviceNetworkEvents
| where Timestamp > ago(24h)
| where RemoteIPType == "Public"
| summarize ConnectionTimes=make_list(Timestamp), Count=count() by DeviceName, RemoteIP, RemoteUrl
| where Count > 50
| extend Intervals = array_sort_asc(ConnectionTimes)
| mv-apply Intervals on (
extend NextTime = next(Intervals)
| where isnotempty(NextTime)
| extend IntervalSec = datetime_diff('second', NextTime, Intervals)
| summarize AvgInterval=avg(IntervalSec), StdDev=stdev(IntervalSec)
)
| extend CV = StdDev / AvgInterval
| where CV < 0.2 and AvgInterval > 30
| sort by CV asc
title: Potential C2 Beaconing Pattern Detected
status: experimental
logsource:
category: proxy
detection:
selection:
dst_ip|cidr: '!10.0.0.0/8'
timeframe: 24h
condition: selection | count(dst) by src_ip > 50
level: medium
tags:
- attack.command_and_control
- attack.t1071.001
Hunt ID: TH-BEACON-[DATE]-[SEQ]
Source IP: [内部 IP]
Source Host: [来自 DHCP/DNS 的主机名]
Destination: [域名/IP]
Protocol: [HTTP/HTTPS/DNS]
Beacon Interval: [平均秒数]
Jitter Estimate: [百分比]
Coefficient of Variation: [变异系数值]
Connection Count: [时间窗口内的总连接数]
Data Size CV: [Payload 一致性指标]
Domain Age: [注册以来的天数]
TI Match: [是/否——来源]
Risk Score: [0-100]
Risk Level: [Critical/High/Medium/Low]
Indicators: [触发的风险因素列表]