performing-log-analysis-for-forensic-investigation

name	performing-log-analysis-for-forensic-investigation
description	Collect, parse, and correlate system, application, and security logs to reconstruct events and establish timelines during forensic investigations. Use when working with performing log analysis for forensic investigation.
domain	cybersecurity
tags	["forensics","log-analysis","siem","event-correlation","timeline-analysis","evidence-collection"]
subdomain	digital-forensics
version	1.0
author	oyi77
license	Apache-2.0
nist_csf	["RS.AN-01","RS.AN-03","DE.AE-02","RS.MA-01"]

Performing Log Analysis For Forensic Investigation

Overview

Cybersecurity skill for performing log analysis for forensic investigation. Follows industry best practices and security standards.

When to Use

Trigger phrases:

• "performing log analysis for forensic investigation"

• "Collect, parse, and correlate system, application, and security logs to reconstr"

• When reconstructing the timeline of a security incident from available log sources

• During post-breach investigation to identify initial access, lateral movement, and exfiltration

• When correlating events across multiple systems and log sources

• For establishing evidence of unauthorized access or policy violations

• When preparing forensic reports requiring detailed event chronology

When NOT to Use

• When you lack proper authorization for testing
• For production systems without change management
• When the task requires legal or compliance expertise beyond technical scope

Prerequisites

• Access to collected log files (Windows Event Logs, syslog, application logs)
• Log parsing tools (LogParser, jq, awk, or ELK stack)
• Understanding of log formats (EVTX, syslog, JSON, CSV)
• NTP-synchronized timestamps across all log sources for correlation
• Sufficient storage for log aggregation and indexing
• Timeline analysis tools (log2timeline, Plaso)

Workflow

# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v  IOC_PATTERNS.items()}