detecting-lateral-movement-in-network

检测网络中的横向移动

适用场景

• 监控企业网络中入侵后横向移动的模式（哈希传递、RDP 跳转、PsExec）
• 为常见的 MITRE ATT&CK 横向移动技术（T1021、T1570）构建 SIEM 检测规则和警报
• 通过分析内部主机之间的身份验证模式和网络连接，调查疑似安全事件
• 搜寻表明攻击者正在网络中横向跳转的异常东西向流量模式
• 验证网络分段和访问控制是否能有效限制横向移动路径

请勿将其作为端点检测与响应（EDR）工具的替代品；请勿在忽略内部流量的情况下仅监控南北向流量；也请勿在不了解正常内部通信模式基线的情况下使用。

前提条件

• 在内部网络关键节点部署网络安全监控（Zeek、Suricata 或网络 TAP）
• 部署 SIEM 平台（Splunk、Elastic、Microsoft Sentinel），用于收集 Windows 安全事件日志、DNS 和流量数据
• 配置 Windows 安全事件日志转发（4624、4625、4648、4672、4768、4769）
• 建立正常内部身份验证和连接模式的基线
• 了解 MITRE ATT&CK 横向移动战术（TA0008）

工作流

步骤 1：配置用于检测横向移动的日志收集

# Windows Event Logs to collect (via WEF or agent):
# Security Log:
#   4624 - Successful logon (Type 3=Network, Type 10=RemoteInteractive)
#   4625 - Failed logon
#   4648 - Logon using explicit credentials (RunAs, PsExec)
#   4672 - Special privileges assigned (admin logon)
#   4768 - Kerberos TGT request
#   4769 - Kerberos service ticket request
#   4776 - NTLM authentication (credential validation)
# System Log:
#   7045 - New service installed (PsExec indicator)
#   7036 - Service started/stopped

# Configure Windows Event Forwarding (WEF) subscription
# On the collector server (PowerShell):
# wecutil cs lateral-movement-subscription.xml

# Filebeat configuration for Windows Event Log shipping
cat > /etc/filebeat/modules.d/security.yml << 'EOF'
- module: system
  auth:
    enabled: true
    var.paths: ["/var/log/auth.log"]
  syslog:
    enabled: true

- module: zeek
  connection:
    enabled: true
    var.paths: ["/opt/zeek/logs/current/conn.log"]
  dns:
    enabled: true
    var.paths: ["/opt/zeek/logs/current/dns.log"]
  smb_mapping:
    enabled: true
    var.paths: ["/opt/zeek/logs/current/smb_mapping.log"]
  dce_rpc:
    enabled: true
    var.paths: ["/opt/zeek/logs/current/dce_rpc.log"]
EOF

# Zeek configuration for lateral movement detection
# Enable SMB, DCE-RPC, and Kerberos logging
cat >> /opt/zeek/share/zeek/site/local.zeek << 'EOF'
@load policy/protocols/smb
@load policy/protocols/conn/known-hosts
@load policy/protocols/conn/known-services
@load frameworks/intel/seen
EOF

sudo zeekctl deploy

步骤 2：为常见的横向移动技术构建检测规则

# Splunk SPL queries for lateral movement detection

# 1. Detect PsExec usage (new service creation on remote hosts)
# index=wineventlog EventCode=7045 ServiceName="PSEXESVC" OR ServiceName="*psexec*"
# | stats count by ComputerName, ServiceName, ImagePath
# | where count > 0

# 2. Detect Pass-the-Hash (Type 3 logon with NTLM)
# index=wineventlog EventCode=4624 LogonType=3 AuthenticationPackageName="NTLM"
# | where TargetUserName!="ANONYMOUS LOGON" AND TargetUserName!="$"
# | stats count dc(ComputerName) as unique_hosts by TargetUserName, IpAddress
# | where unique_hosts > 3

# 3. Detect RDP lateral movement (Type 10 logon from internal IPs)
# index=wineventlog EventCode=4624 LogonType=10
# | where cidrmatch("10.0.0.0/8", IpAddress) OR cidrmatch("192.168.0.0/16", IpAddress)
# | stats count dc(ComputerName) as rdp_hosts by TargetUserName, IpAddress
# | where rdp_hosts > 2

# Elastic SIEM detection rules (KQL)
# event.code: "4624" and winlog.event_data.LogonType: "3"
#   and winlog.event_data.AuthenticationPackageName: "NTLM"
#   and not winlog.event_data.TargetUserName: *$
#   and source.ip: (10.0.0.0/8 or 172.16.0.0/12 or 192.168.0.0/16)

# Sigma rules for lateral movement detection
# Install sigma and convert to target SIEM format
pip3 install sigma-cli

cat > lateral_movement_pth.yml << 'EOF'
title: Pass-the-Hash Lateral Movement Detection
id: f8d98d6c-7a07-4d74-b064-dd4a3c244528
status: experimental
description: Detects network logon with NTLM authentication to multiple hosts
logsource:
    product: windows
    service: security
detection:
    selection:
        EventID: 4624
        LogonType: 3
        AuthenticationPackageName: NTLM
    filter:
        TargetUserName|endswith: '$'
    condition: selection and not filter
    timeframe: 15m
    count:
        field: ComputerName
        min: 3
        group-by: TargetUserName
level: high
tags:
    - attack.lateral_movement
    - attack.t1550.002
EOF

# Convert Sigma rule to Splunk SPL
sigma convert -t splunk lateral_movement_pth.yml

# Convert to Elastic query
sigma convert -t elasticsearch lateral_movement_pth.yml

步骤 3：使用 Zeek 进行网络层检测

# Detect SMB lateral movement (admin$ and c$ share access)
cat /opt/zeek/logs/current/smb_mapping.log | \
  zeek-cut ts id.orig_h id.resp_h path | \
  grep -iE "(admin\$|c\$|ipc\$)" | \
  sort -t$'\t' -k2 | uniq -c | sort -rn

# Detect hosts connecting to many internal hosts on port 445 (SMB spreading)
cat /opt/zeek/logs/current/conn.log | \
  zeek-cut ts id.orig_h id.resp_h id.resp_p | \
  awk '$4 == 445' | \
  awk '{print $2}' | sort | uniq -c | sort -rn | head -10

# Detect WMI lateral movement (DCE-RPC to IWbemServices)
cat /opt/zeek/logs/current/dce_rpc.log | \
  zeek-cut ts id.orig_h id.resp_h operation | \
  grep -i "wbem\|wmi" | sort | uniq -c | sort -rn

# Detect RDP connections between internal hosts
cat /opt/zeek/logs/current/conn.log | \
  zeek-cut ts id.orig_h id.resp_h id.resp_p duration | \
  awk '$4 == 3389 && $5 > 60' | \
  sort -t$'\t' -k2 | head -20

# Detect Kerberos ticket-granting anomalies
cat /opt/zeek/logs/current/kerberos.log | \
  zeek-cut ts id.orig_h id.resp_h client service success error_msg | \
  grep -v "true" | head -20

# Custom Zeek script for lateral movement detection
sudo tee /opt/zeek/share/zeek/site/custom-detections/lateral-movement.zeek << 'ZEEKEOF'
@load base/frameworks/notice
@load base/frameworks/sumstats

module LateralMovement;

export {
    redef enum Notice::Type += {
        SMB_Lateral_Spread,
        RDP_Lateral_Chain
    };
    const smb_host_threshold: count = 5 &redef;
    const smb_time_window: interval = 15min &redef;
}

event zeek_init()
{
    local r1 = SumStats::Reducer(
        $stream="lateral.smb",
        $apply=set(SumStats::UNIQUE)
    );

    SumStats::create([
        $name="detect-smb-lateral",
        $epoch=smb_time_window,
        $reducers=set(r1),
        $threshold_val(key: SumStats::Key, result: SumStats::Result) = {
            return result["lateral.smb"]$unique + 0.0;
        },
        $threshold=smb_host_threshold + 0.0,
        $threshold_crossed(key: SumStats::Key, result: SumStats::Result) = {
            NOTICE([
                $note=SMB_Lateral_Spread,
                $msg=fmt("Host %s connected to %d SMB hosts in %s",
                         key$str, result["lateral.smb"]$unique, smb_time_window),
                $identifier=key$str
            ]);
        }
    ]);
}

event connection_state_remove(c: connection)
{
    if ( c$id$resp_p == 445/tcp && c$id$resp_h in Site::local_nets )
    {
        SumStats::observe("lateral.smb",
            [$str=cat(c$id$orig_h)],
            [$str=cat(c$id$resp_h)]
        );
    }
}
ZEEKEOF

sudo zeekctl deploy

步骤 4：搜寻横向移动指标

# Hunt for authentication anomalies in Windows logs
# Splunk query: Users authenticating from unusual source hosts
# index=wineventlog EventCode=4624 LogonType=3
# | stats values(IpAddress) as source_ips dc(IpAddress) as source_count by TargetUserName
# | where source_count > 5
# | sort -source_count

# Hunt for service accounts used interactively
# index=wineventlog EventCode=4624 (LogonType=2 OR LogonType=10)
# | where match(TargetUserName, "^svc-.*")
# | table _time ComputerName TargetUserName IpAddress LogonType

# Network flow analysis for lateral movement patterns
# Look for hosts that suddenly start communicating with many internal hosts
cat /opt/zeek/logs/current/conn.log | \
  zeek-cut ts id.orig_h id.resp_h | \
  awk '{
    key = $2
    targets[key][$3] = 1
  }
  END {
    for (src in targets) {
      count = 0
      for (dst in targets[src]) count++
      if (count > 20) print src, count
    }
  }' | sort -k2 -rn

# Detect credential dumping artifacts (large LSASS reads)
# Look for connections from hosts that suddenly pivot
cat /opt/zeek/logs/current/conn.log | \
  zeek-cut ts id.orig_h id.resp_h id.resp_p orig_bytes | \
  awk '$4 == 445 && $5 > 10000000' | sort -t$'\t' -k5 -rn

# Timeline analysis: map the attack path
# index=wineventlog (EventCode=4624 OR EventCode=7045)
# | eval stage=case(
#     EventCode=4624 AND LogonType=3, "Network Logon",
#     EventCode=4624 AND LogonType=10, "RDP Logon",
#     EventCode=7045, "Service Creation"
#   )
# | timechart span=5m count by stage

步骤 5：自动响应和遏制

# SOAR playbook for lateral movement response (pseudocode)
# When lateral movement alert triggers:

# 1. Enrich the alert with context
# - Query AD for user group membership and role
# - Check if source IP is a known admin workstation
# - Look up recent vulnerability scan results for affected hosts

# 2. Automated containment actions
# Option A: Isolate the host via switch port shutdown
# ssh admin@switch "conf t; interface Gi1/0/5; shutdown"

# Option B: Quarantine via VLAN change (less disruptive)
# ssh admin@switch "conf t; interface Gi1/0/5; switchport access vlan 999"

# Option C: Block at firewall
sudo iptables -I FORWARD -s 10.10.5.23 -j DROP

# 3. Disable the compromised account
# PowerShell: Disable-ADAccount -Identity compromised_user

# 4. Force password reset
# PowerShell: Set-ADAccountPassword -Identity compromised_user -Reset

# 5. Collect forensic evidence before full containment
# velociraptor artifact collect Windows.KapeFiles.Targets --target BasicCollection

步骤 6：构建检测仪表板

# Elastic Kibana dashboard queries for lateral movement monitoring

# Panel 1: Authentication heatmap (source vs destination)
# Aggregation: Terms on source.ip (rows) and destination.ip (columns)
# Metric: Count of event.code:4624

# Panel 2: SMB connections between internal hosts
# Filter: destination.port:445 and source.ip:10.0.0.0/8
# Aggregation: Top 20 source IPs by unique destination count

# Panel 3: RDP sessions timeline
# Filter: destination.port:3389 and event.code:4624 and winlog.event_data.LogonType:10
# Visualization: Timeline by source.ip

# Panel 4: New service installations
# Filter: event.code:7045
# Aggregation: Terms on winlog.event_data.ServiceName

# Panel 5: Failed authentication spike detection
# Filter: event.code:4625
# Aggregation: Date histogram with anomaly detection

# Export Kibana dashboard
# curl -X GET "elastic-siem:5601/api/saved_objects/_export" \
#   -H "kbn-xsrf: true" \
#   -d '{"type":"dashboard","objects":[{"id":"lateral-movement-dashboard","type":"dashboard"}]}' \
#   > lateral_movement_dashboard.ndjson

核心概念

术语	定义
横向移动	MITRE ATT&CK 战术（TA0008），描述攻击者从一台已入侵系统移动到另一台系统时使用的技术
哈希传递（T1550.002）	使用窃取的 NTLM 密码哈希向远程系统进行身份验证，而无需知道明文密码
PsExec（T1569.002）	一种远程服务执行工具，会在目标系统上创建临时服务，可通过事件 ID 7045 检测
东西向流量	内部系统之间的网络通信（与内部网络和外部网络之间的南北向流量相对）
身份验证异常	偏离基线身份验证模式的情况，例如用户登录了以前从未访问过的系统
Kerberoasting（T1558.003）	请求服务帐户的 Kerberos 服务票证并离线破解；可通过事件 ID 4769 异常检测

工具与系统

• Zeek：网络安全监控器，可生成 SMB、Kerberos、DCE-RPC 和连接日志，用于分析横向移动
• Splunk/Elastic SIEM：日志聚合平台，用于关联整个企业中的身份验证事件、网络流量和服务创建记录
• Sigma：与供应商无关的检测规则格式，可编写适用于多种 SIEM 平台的通用横向移动检测规则
• Velociraptor：端点取证工具，用于从涉及横向移动链的主机收集证据
• BloodHound：Active Directory 攻击路径分析工具，可在攻击者利用潜在横向移动路径之前识别这些路径

常见场景

场景：检测勒索软件操作者的横向移动

背景：SOC 收到一条警报，指出文件服务器（10.10.20.15）于凌晨 2:00 创建了 PsExec 服务。该警报触发了一项横向移动调查。组织使用 Zeek 进行网络监控，并将 Windows 事件日志转发到 Splunk。

方法：

1. 在 Splunk 中查询 10.10.20.15 上的事件 ID 7045（服务创建），确认 PsExec 已执行，并确定源 IP（10.10.5.23）
2. 追踪 10.10.5.23 的身份验证历史：查找事件 ID 4624、类型 3 的登录记录，发现该主机在过去一小时内使用 NTLM 向 8 台服务器进行身份验证（传递哈希模式）
3. 检查 Zeek 的 conn.log 中 10.10.5.23 的记录：识别出与 12 台内部主机的 SMB 连接（端口 445），以及向外部 IP 传输的大量文件
4. 构建攻击时间线：凌晨 1:15 通过钓鱼邮件初始入侵，凌晨 1:25 转储凭据，凌晨 1:30 至 2:00 期间横向移动至 8 台服务器
5. 通过追踪身份验证链识别所有失陷主机：10.10.5.23 -> 10.10.20.15 -> 10.10.20.16 -> 10.10.20.17
6. 将所有已识别主机隔离到 VLAN 999、禁用失陷账户并阻止外部 C2 IP，以遏制攻击
7. 报告完整攻击链，包括时间线、受影响主机和检测盲点

注意事项：

• 只调查单条警报，而未追踪所有主机上的完整横向移动链
• 宣布遏制完成前，未检查每台失陷主机上的持久化机制
• 仅依赖 Windows 事件日志而未关联网络流量数据，因而遗漏了使用不会生成 Windows 事件的工具进行的横向移动
• 未建立正常内部身份验证模式的基线，导致无法检测异常

输出格式

## Lateral Movement Investigation Report

**Case ID**: IR-2024-0312
**Initial Alert**: PsExec on 10.10.20.15 at 02:00 UTC
**Investigation Period**: 2024-03-15 01:00 to 03:00 UTC

### Attack Timeline

| Time (UTC) | Source | Destination | Technique | Evidence |
|------------|--------|-------------|-----------|----------|
| 01:15 | External | 10.10.5.23 | Initial Access (Phishing) | Email log + HTTP download |
| 01:25 | 10.10.5.23 | Local | Credential Dumping | LSASS access (Sysmon EID 10) |
| 01:32 | 10.10.5.23 | 10.10.20.15 | Pass-the-Hash (SMB) | EID 4624 Type 3 NTLM |
| 01:38 | 10.10.5.23 | 10.10.20.16 | PsExec | EID 7045 + Zeek SMB |
| 01:45 | 10.10.20.16 | 10.10.20.17 | RDP | EID 4624 Type 10 |
| 02:00 | 10.10.20.17 | 10.10.20.15 | PsExec (triggered alert) | EID 7045 |
| 02:10 | 10.10.5.23 | 203.0.113.50 | Data Exfiltration | Zeek conn.log 2.3 GB |

### Affected Systems
- 10.10.5.23 (workstation-045) - Initial compromise
- 10.10.20.15 (file-server-01) - Data accessed
- 10.10.20.16 (app-server-02) - Pivoted through
- 10.10.20.17 (db-server-01) - Final target

### Detection Gaps
1. Initial phishing email not blocked by email gateway
2. Credential dumping not detected (no LSASS monitoring)
3. 30-minute gap between first lateral movement and alert