Anthropic-Cybersecurity-Skills detecting-lateral-movement-with-splunk
Detect adversary lateral movement across networks using Splunk SPL queries against Windows authentication logs,
install
source · Clone the upstream repo
git clone https://github.com/mukul975/Anthropic-Cybersecurity-Skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/detecting-lateral-movement-with-splunk" ~/.claude/skills/mukul975-anthropic-cybersecurity-skills-detecting-lateral-movement-with-splunk && rm -rf "$T"
manifest:
skills/detecting-lateral-movement-with-splunk/SKILL.mdsource content
Detecting Lateral Movement with Splunk
When to Use
- When hunting for adversary movement between compromised systems
- After detecting credential theft to trace subsequent lateral activity
- When investigating unusual authentication patterns across the network
- During incident response to scope the breadth of compromise
- When proactively hunting for TA0008 (Lateral Movement) techniques
Prerequisites
- Splunk Enterprise or Splunk Cloud with Windows event data ingested
- Windows Security Event Logs forwarded (4624, 4625, 4648, 4672, 4768, 4769)
- Sysmon deployed for process creation and network connection data
- Network flow data or firewall logs for SMB/RDP/WinRM correlation
- Active Directory user and group membership reference data
Workflow
- Define Lateral Movement Scope: Identify which lateral movement techniques to hunt (RDP, SMB/Admin Shares, WinRM, PsExec, WMI, DCOM, SSH).
- Query Authentication Events: Use SPL to search for Type 3 (Network) and Type 10 (RemoteInteractive) logons across the environment.
- Build Authentication Graphs: Map source-to-destination authentication relationships to identify unusual connection patterns.
- Detect First-Time Relationships: Identify new source-destination pairs that have not been seen in the historical baseline.
- Correlate with Process Activity: Link authentication events to subsequent process creation on destination hosts.
- Identify Anomalous Patterns: Flag lateral movement to sensitive servers, unusual hours, service account misuse, or rapid multi-host access.
- Report and Contain: Document lateral movement path, affected systems, and coordinate containment response.
Key Concepts
| Concept | Description |
|---|---|
| T1021 | Remote Services (parent technique) |
| T1021.001 | Remote Desktop Protocol (RDP) |
| T1021.002 | SMB/Windows Admin Shares |
| T1021.003 | Distributed COM (DCOM) |
| T1021.004 | SSH |
| T1021.006 | Windows Remote Management (WinRM) |
| T1570 | Lateral Tool Transfer |
| T1047 | Windows Management Instrumentation |
| T1569.002 | Service Execution (PsExec) |
| Logon Type 3 | Network logon (SMB, WinRM, mapped drives) |
| Logon Type 10 | Remote Interactive (RDP) |
| Event ID 4624 | Successful logon |
| Event ID 4648 | Explicit credential logon (runas, PsExec) |
Tools & Systems
| Tool | Purpose |
|---|---|
| Splunk Enterprise | SIEM for log aggregation and SPL queries |
| Splunk Enterprise Security | Threat detection and notable events |
| Windows Event Forwarding | Centralize Windows logs |
| Sysmon | Detailed process and network telemetry |
| BloodHound | AD attack path analysis |
| PingCastle | AD security assessment |
Common Scenarios
- PsExec Lateral Movement: Adversary uses PsExec to execute commands on remote systems via SMB, generating Type 3 logon with ADMIN$ share access.
- RDP Pivoting: Attacker RDPs to internal systems using stolen credentials, creating Type 10 logon events.
- WMI Remote Execution: Adversary uses WMIC process call create to spawn processes on remote hosts.
- WinRM PowerShell Remoting: Attacker uses Enter-PSSession or Invoke-Command to execute code on remote systems.
- Pass-the-Hash via SMB: Compromised NTLM hashes used to authenticate to remote systems without knowing the plaintext password.
Output Format
Hunt ID: TH-LATMOV-[DATE]-[SEQ] Movement Type: [RDP/SMB/WinRM/WMI/DCOM/PsExec] Source Host: [Hostname/IP] Destination Host: [Hostname/IP] Account Used: [Username] Logon Type: [3/10/other] First Seen: [Timestamp] Event Count: [Number of events] Risk Level: [Critical/High/Medium/Low] Lateral Movement Path: [A -> B -> C -> D]