Scenario-Based Cybersecurity Analyst Training: Log Analysis & SIEM Alerts Part

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This document is a continuation of the previous post and features training based on real-world use cases. It’s designed for cybersecurity analysts who want to sharpen their investigative skills and improve their ability to analyse logs and respond to SIEM alerts effectively.

You Should Know:

1. Log Analysis Techniques

  • Linux Command for Log Inspection:
    grep "Failed password" /var/log/auth.log # Check failed SSH attempts 
    tail -f /var/log/syslog # Monitor logs in real-time 
    journalctl -u sshd --no-pager # View SSH service logs (systemd) 
    
  • Windows Event Log Analysis:
    Get-WinEvent -FilterHashtable @{LogName='Security'; ID=4625} # Failed login attempts 
    Get-WinEvent -Path C:\Windows\System32\winevt\Logs\Security.evtx | Where-Object {$_.ID -eq 4688} # Process creation logs 
    

2. SIEM Alert Investigation

  • Splunk Query for Suspicious Activity:
    index=main sourcetype=linux_secure "authentication failure" | stats count by src 
    index=win_events EventCode=4625 | table _time, AccountName, Source_Network_Address 
    
  • Elasticsearch Query for Threat Hunting:
    {
    "query": {
    "bool": {
    "must": [
    {"match": {"event.code": "4625"}},
    {"range": {"@timestamp": {"gte": "now-1d/d"}}}
    ]
    }
    }
    }
    

3. Incident Response Steps

  • Isolate Compromised System:
    sudo iptables -A INPUT -s <MALICIOUS_IP> -j DROP # Linux firewall block 
    netsh advfirewall firewall add rule name="Block Attacker" dir=in action=block remoteip=<MALICIOUS_IP> # Windows block 
    
  • Collect Forensic Evidence:
    dd if=/dev/sda of=/evidence/image.img bs=4M # Disk imaging (Linux) 
    volatility -f memory.dump --profile=Win10x64 pslist # Memory analysis 
    

What Undercode Say:

Effective log analysis and SIEM alert handling require familiarity with OS-specific commands, query languages, and incident response protocols. Regular practice with real-world datasets improves detection accuracy. Automation (e.g., scripting log parsing) enhances efficiency.

Expected Output:

  • Enhanced log filtering and correlation.
  • Faster incident triage using SIEM queries.
  • Improved defensive measures via automated blocking.

Relevant URLs:

References:

Reported By: Izzmier Scenario – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass βœ…

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