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
# 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 in IOC_PATTERNS.items()}
- Scope the Analysis — Define what prefetch files artifacts or data sources to examine and the investigation timeline.
- Preserve Evidence — Create forensic copies of relevant data. Maintain chain of custody documentation.
- Extract Key Indicators — Use execution history to parse and extract relevant prefetch files data points from collected artifacts.
- Correlate Findings — Cross-reference extracted data with other sources (threat intel, logs, timelines).
- Build Timeline — Construct a chronological sequence of events related to prefetch files.
- Document Analysis — Write findings report with evidence, conclusions, and recommendations.
Tools
- execution history — Primary tool for this skill
- Forensic Toolkit — Evidence collection and analysis
- Timeline Tools — Chronological event reconstruction
- Log Analysis Platform — Centralized log parsing and search
Process
- Scope — Define research questions, identify data sources, set time boundaries
- Gather — Collect data from primary sources, APIs, and public records
- Synthesize — Analyze findings, identify patterns, produce actionable report
Verification
Anti-Rationalization Table
| Rationalization |
Reality |
| "We are too small to be targeted" |
Automated attacks target everyone. Size does not matter. |
| "Security slows us down" |
A breach slows you down 100x more. Build security in from the start. |
| "We will fix it after launch" |
Vulnerabilities in production are exploited within hours. Fix before deploy. |
1---2name: analyzing-prefetch-files-for-execution-history3description: Use when 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.4license: Apache-2.05---67# Analyzing Prefetch Files For Execution History89## Overview1011Cybersecurity skill for analyzing prefetch files for execution history. Follows industry best practices and security standards.1213## When to Use14**Trigger phrases:**15- "analyzing prefetch files for execution history"16- "Parse Windows Prefetch files to determine program execution history including ru"1718- When determining which programs were executed on a Windows system and when19- During malware investigations to confirm execution of suspicious binaries20- For establishing a timeline of application usage during an incident21- When correlating program execution with other forensic artifacts22- To identify anti-forensic tools or unauthorized software that was run232425## When NOT to Use2627- When you lack proper authorization for testing28- For production systems without change management29- When the task requires legal or compliance expertise beyond technical scope303132## Prerequisites33- Access to Windows Prefetch directory (C:\Windows\Prefetch\) from forensic image34- PECmd (Eric Zimmerman), WinPrefetchView, or python-prefetch parser35- Understanding of Prefetch file format (versions 17, 23, 26, 30)36- Windows system with Prefetch enabled (default on client OS, disabled on servers)37- Knowledge of Prefetch naming conventions (APPNAME-HASH.pf)3839## Workflow4041```python42# Example: IOC detection43import re4445IOC_PATTERNS = {46 "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",47 "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",48 "hash_md5": r"\b[a-f0-9]{32}\b",49 "hash_sha256": r"\b[a-f0-9]{64}\b",50}5152def extract_iocs(text: str) -> dict:53 return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}54```55561. **Scope the Analysis** — Define what prefetch files artifacts or data sources to examine and the investigation timeline.572. **Preserve Evidence** — Create forensic copies of relevant data. Maintain chain of custody documentation.583. **Extract Key Indicators** — Use execution history to parse and extract relevant prefetch files data points from collected artifacts.594. **Correlate Findings** — Cross-reference extracted data with other sources (threat intel, logs, timelines).605. **Build Timeline** — Construct a chronological sequence of events related to prefetch files.616. **Document Analysis** — Write findings report with evidence, conclusions, and recommendations.6263## Tools6465- **execution history** — Primary tool for this skill66- **Forensic Toolkit** — Evidence collection and analysis67- **Timeline Tools** — Chronological event reconstruction68- **Log Analysis Platform** — Centralized log parsing and search697071## Process72731. **Scope** — Define research questions, identify data sources, set time boundaries741. **Gather** — Collect data from primary sources, APIs, and public records751. **Synthesize** — Analyze findings, identify patterns, produce actionable report7677## Verification7879- [ ] All prefetch files procedures executed completely and documented80- [ ] Findings validated against multiple data sources81- [ ] False positives identified and filtered82- [ ] Results documented with evidence and timestamps83- [ ] Recommendations provided with risk-based prioritization8485## Anti-Rationalization Table8687| Rationalization | Reality |88|---|---|89| "We are too small to be targeted" | Automated attacks target everyone. Size does not matter. |90| "Security slows us down" | A breach slows you down 100x more. Build security in from the start. |91| "We will fix it after launch" | Vulnerabilities in production are exploited within hours. Fix before deploy. |