performing-timeline-reconstruction-with-plaso

name	performing-timeline-reconstruction-with-plaso
description	Build comprehensive forensic super-timelines using Plaso (log2timeline) to correlate events across file systems, logs, and artifacts into a unified chronological view. Use when building comprehensive forensic super-timelines using plaso (log2timeline) to correlate events.
domain	cybersecurity
tags	["forensics","timeline-analysis","plaso","log2timeline","super-timeline","event-correlation"]
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 Timeline Reconstruction With Plaso

Overview

Cybersecurity skill for performing timeline reconstruction with plaso. Follows industry best practices and security standards.

When to Use

Trigger phrases:

• "performing timeline reconstruction with plaso"

• "Build comprehensive forensic super-timelines using Plaso (log2timeline) to corre"

• When building a comprehensive forensic timeline from multiple evidence sources

• For correlating events across file system metadata, event logs, browser history, and registry

• During complex investigations requiring chronological reconstruction of activities

• When standard log analysis is insufficient to establish the sequence of events

• For presenting investigation findings in a visual, chronological format

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

• Plaso (log2timeline/psort) installed on forensic workstation
• Forensic disk image(s) in raw (dd), E01, or VMDK format
• Sufficient storage for Plaso output (can be 10x+ the image size)
• Minimum 8GB RAM (16GB+ recommended for large images)
• Timeline Explorer (Eric Zimmerman) or Timesketch for visualization
• Understanding of timestamp types (MACB: Modified, Accessed, Changed, Born)

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()}