Extracting Memory Artifacts With Rekall

---
name: extracting-memory-artifacts-with-rekall
description: Use when uses Rekall memory forensics framework to analyze memory dumps
  for process hollowing, injected code via VAD anomalies, hidden processes, and rootkit
  detection. Applies plugins like pslist, psscan, vadinfo, malfind, and dlllist to
  extract forensic artifacts from Windows memory images. Use during incident response
  memory analysis. . Use when working with extracting memory artifacts with rekall.
domain: cybersecurity
tags:
- extracting
- memory
- artifacts
- with
subdomain: security-operations
version: '1.0'
author: oyi77
license: Apache-2.0
nist_csf:
- DE.CM-01
- RS.MA-01
- GV.OV-01
- DE.AE-02
category: cybersecurity
---

# Extracting Memory Artifacts With Rekall

## Overview

Cybersecurity skill for extracting memory artifacts with rekall. Follows industry best practices and security standards.

## When to Use
**Trigger phrases:**
- "extracting memory artifacts with rekall"
- "Uses Rekall memory forensics framework to analyze memory dumps for process hollo"


- When performing authorized security testing that involves extracting memory artifacts with rekall
- When analyzing malware samples or attack artifacts in a controlled environment
- When conducting red team exercises or penetration testing engagements
- When building detection capabilities based on offensive technique understanding


## 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

- Familiarity with security operations concepts and tools
- Access to a test or lab environment for safe execution
- Python 3.8+ with required dependencies installed
- Appropriate authorization for any testing activities

## Workflow

```python
# 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()}
```

1. **Define Objectives** — Clarify the goals and scope for memory artifacts.
2. **Gather Resources** — Collect tools, data, and access needed for memory artifacts.
3. **Execute Process** — Carry out memory artifacts operations methodically.
4. **Verify Quality** — Check results against acceptance criteria.
5. **Document Outcomes** — Record findings, decisions, and next steps.

## Tools

- **rekall** — Primary tool for this skill
- **Analysis Platform** — Data processing and visualization
- **Collaboration Tools** — Team coordination and knowledge sharing


## Process

1. **Prepare** — Gather requirements, verify prerequisites, set up environment
1. **Execute** — Run extracting memory artifacts with rekall workflow with configured parameters
1. **Verify** — Validate output meets requirements, document results

## Verification

- [ ] All memory artifacts procedures executed completely and documented
- [ ] Findings validated against multiple data sources
- [ ] False positives identified and filtered
- [ ] Results documented with evidence and timestamps
- [ ] Recommendations provided with risk-based prioritization

## 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. |