| 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"
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"Build comprehensive forensic super-timelines using Plaso (log2timeline) to corre"
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When building a comprehensive forensic timeline from multiple evidence sources
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For correlating events across file system metadata, event logs, browser history, and registry
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During complex investigations requiring chronological reconstruction of activities
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When standard log analysis is insufficient to establish the sequence of events
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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
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()}
