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/analyzing-security-logs-with-splunk

Leverages Splunk Enterprise Security and SPL (Search Processing Language)

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cybersecurity-skills
28k200 skills
Install
$ npx -y skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-security-logs-with-splunk --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/analyzing-security-logs-with-splunk

Context preview

The summary Claude sees to decide when to auto-load this skill.

Leverages Splunk Enterprise Security and SPL (Search Processing Language)

SKILL.md

analyzing-security-logs-with-splunk.SKILL.md
name: analyzing-security-logs-with-splunk
description: 'Leverages Splunk Enterprise Security and SPL (Search Processing Language)
  to investigate security incidents through log correlation, timeline reconstruction,
  and anomaly detection. Covers Windows event logs, firewall logs, proxy logs, and
  authentication data analysis. Activates for requests involving Splunk investigation,
  SPL queries, SIEM log analysis, security event correlation, or log-based incident
  investigation.

  '
domain: cybersecurity
subdomain: incident-response
tags:
- splunk
- SPL
- SIEM
- log-analysis
- security-monitoring
mitre_attack:
- T1110
- T1550.002
- T1021.001
- T1059.001
- T1003.001
version: 1.0.0
author: mahipal
license: Apache-2.0
atlas_techniques:
- AML.T0070
- AML.T0066
- AML.T0082
d3fend_techniques:
- Executable Denylisting
- Execution Isolation
- File Metadata Consistency Validation
- Content Format Conversion
- File Content Analysis
nist_ai_rmf:
- MEASURE-2.7
- MAP-5.1
- MANAGE-2.4
- MANAGE-3.1
- MEASURE-3.1
nist_csf:
- RS.MA-01
- RS.MA-02
- RS.AN-03
- RC.RP-01

Analyzing Security Logs with Splunk

When to Use

  • Investigating a security incident that requires correlation across multiple log sources
  • Hunting for adversary activity using known TTPs and IOCs
  • Building detection rules for specific attack patterns
  • Reconstructing an incident timeline from disparate log sources
  • Analyzing authentication anomalies, lateral movement, or data exfiltration patterns

**Do not use** for real-time packet-level analysis; use Wireshark or Zeek for full packet capture analysis.

Prerequisites

  • Splunk Enterprise or Splunk Cloud with Enterprise Security (ES) app installed
  • Log sources ingested: Windows Event Logs (via Splunk Universal Forwarder or WEF), firewall, proxy, DNS, EDR, email gateway
  • Splunk CIM (Common Information Model) data models configured for normalized field names
  • SPL proficiency at intermediate level or higher
  • Role-based access with `search` and `accelerate_search` capabilities in Splunk

Workflow

Step 1: Scope the Investigation in Splunk

Define search parameters based on incident triage data:

| Set initial investigation scope
index=windows OR index=firewall OR index=proxy
  earliest="2025-11-14T00:00:00" latest="2025-11-16T00:00:00"
  (host="WKSTN-042" OR src_ip="10.1.5.42" OR user="jsmith")
| stats count by index, sourcetype, host
| sort -count

This query establishes which log sources contain relevant data for the investigation timeframe and affected assets.

Step 2: Analyze Authentication Events

Investigate suspicious authentication patterns using Windows Security Event Logs:

| Detect brute force and credential stuffing
index=windows sourcetype="WinEventLog:Security" EventCode=4625
  earliest=-24h
| stats count as failed_attempts, values(src_ip) as source_ips,
  dc(src_ip) as unique_sources by TargetUserName
| where failed_attempts > 10
| sort -failed_attempts

| Detect pass-the-hash (Logon Type 9 - NewCredentials)
index=windows sourcetype="WinEventLog:Security" EventCode=4624
  Logon_Type=9
| table _time, host, TargetUserName, src_ip, LogonProcessName

| Detect lateral movement via RDP
index=windows sourcetype="WinEventLog:Security" EventCode=4624
  Logon_Type=10
| stats count, values(host) as targets by TargetUserName, src_ip
| where count > 3
| sort -count

Step 3: Trace Process Execution

Use Sysmon logs to reconstruct process execution chains:

| Process creation with parent chain (Sysmon Event ID 1)
index=sysmon EventCode=1 host="WKSTN-042"
  earliest="2025-11-15T14:00:00" latest="2025-11-15T15:00:00"
| table _time, ParentImage, ParentCommandLine, Image, CommandLine, User, Hashes
| sort _time

| Detect suspicious PowerShell execution
index=sysmon EventCode=1 Image="*\\powershell.exe"
  (CommandLine="*-enc*" OR CommandLine="*-encodedcommand*"
   OR CommandLine="*downloadstring*" OR CommandLine="*iex*")
| table _time, host, User, ParentImage, CommandLine
| sort _time

| Detect LSASS credential dumping
index=sysmon EventCode=10 TargetImage="*\\lsass.exe"
  GrantedAccess=0x1010
| table _time, host, SourceImage, SourceUser, GrantedAccess

Step 4: Analyze Network Activity

Correlate network logs with endpoint events:

| Detect C2 beaconing pattern
index=proxy OR index=firewall dest_ip="185.220.101.42"
| timechart span=1m count by src_ip
| where count > 0

| Detect DNS tunneling (high query volume to single domain)
index=dns
| rex field=query "(?<subdomain>[^\.]+)\.(?<domain>[^\.]+\.[^\.]+)$"
| stats count, avg(len(query)) as avg_query_len by domain, src_ip
| where count > 500 AND avg_query_len > 40
| sort -count

| Detect large data transfers (potential exfiltration)
index=proxy action=allowed
| stats sum(bytes_out) as total_bytes by src_ip, dest_ip, dest_host
| eval total_MB=round(total_bytes/1024/1024,2)
| where total_MB > 100
| sort -total_MB

Step 5: Build the Incident Timeline

Reconstruct a unified timeline across all log sources:

| Unified incident timeline
index=windows OR index=sysmon OR index=proxy OR index=firewall
  (host="WKSTN-042" OR src_ip="10.1.5.42" OR user="jsmith")
  earliest="2025-11-15T14:00:00" latest="2025-11-15T16:00:00"
| eval event_summary=case(
    sourcetype=="WinEventLog:Security" AND EventCode==4624, "Logon: ".TargetUserName." from ".src_ip,
    sourcetype=="WinEventLog:Security" AND EventCode==4625, "Failed logon: ".TargetUserName,
    sourcetype=="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" AND EventCode==1,
      "Process: ".Image." by ".User,
    sourcetype=="proxy", "Web: ".http_method." ".url,
    1==1, sourcetype.": ".EventCode)
| table _time, sourcetype, host, event_summary
| sort _time

Step 6: Create Detection Rules

Convert investigation findings into persistent Splunk correlation searches:

| Correlation search: PowerShell spawned by Office applications
index=sysmon EventCode=1
  Image="*\\powershell.exe"
  (ParentIma
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