| name | analyzing-prefetch-files-for-execution-history |
| description | Parse Windows Prefetch files to determine program execution history including run counts, timestamps, and referenced files for forensic investigation. Use when working with analyzing prefetch files for execution history. |
| domain | cybersecurity |
| tags | ["forensics","prefetch","windows-artifacts","execution-history","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"] |
Analyzing Prefetch Files For Execution History
Overview
Cybersecurity skill for analyzing prefetch files for execution history. Follows industry best practices and security standards.
When to Use
Trigger phrases:
-
"analyzing prefetch files for execution history"
-
"Parse Windows Prefetch files to determine program execution history including ru"
-
When determining which programs were executed on a Windows system and when
-
During malware investigations to confirm execution of suspicious binaries
-
For establishing a timeline of application usage during an incident
-
When correlating program execution with other forensic artifacts
-
To identify anti-forensic tools or unauthorized software that was run
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 Windows Prefetch directory (C:\Windows\Prefetch) from forensic image
- PECmd (Eric Zimmerman), WinPrefetchView, or python-prefetch parser
- Understanding of Prefetch file format (versions 17, 23, 26, 30)
- Windows system with Prefetch enabled (default on client OS, disabled on servers)
- Knowledge of Prefetch naming conventions (APPNAME-HASH.pf)
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 in IOC_PATTERNS.items()}
