skills/detecting-lateral-movement-with-splunk/SKILL.md
Detect adversary lateral movement across networks using Splunk SPL queries against Windows authentication logs, SMB traffic, and remote service abuse.
npx skillsauth add mukul975/anthropic-cybersecurity-skills detecting-lateral-movement-with-splunkInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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| 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) |
| 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 |
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]
testing
Identifies lateral movement techniques in enterprise networks by analyzing authentication logs, network flows, SMB traffic, and RDP sessions using Zeek, Velociraptor, and SIEM correlation rules to detect attackers moving between systems.
tools
Detect Kerberoasting attacks by monitoring for anomalous Kerberos TGS requests targeting service accounts with SPNs for offline password cracking.
development
Implement User and Entity Behavior Analytics using Elasticsearch/OpenSearch to build behavioral baselines, calculate anomaly scores, perform peer group analysis, and detect insider threat indicators such as data exfiltration, privilege abuse, and unauthorized access patterns.
data-ai
Detect insider threat behavioral indicators including unusual data access, off-hours activity, mass file downloads, privilege abuse, and resignation-correlated data theft.