performing-memory-forensics-with-volatility3

name	performing-memory-forensics-with-volatility3
description	Analyze volatile memory dumps using Volatility 3 to extract running processes, network connections, loaded modules, and evidence of malicious activity. Use when analyzeing volatile memory dumps using volatility 3 to extract running.
domain	cybersecurity
tags	["forensics","memory-forensics","volatility","ram-analysis","malware-detection","incident-response"]
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 Memory Forensics With Volatility3

Overview

Cybersecurity skill for performing memory forensics with volatility3. Follows industry best practices and security standards.

When to Use

Trigger phrases:

• "performing memory forensics with volatility3"

• "Analyze volatile memory dumps using Volatility 3 to extract running processes, n"

• When analyzing a RAM dump from a compromised or suspect system

• During incident response to identify running malware, injected code, or rootkits

• When you need to extract credentials, encryption keys, or network connections from memory

• For detecting process hollowing, DLL injection, or hidden processes

• When disk-based forensics alone is insufficient and volatile data is critical

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

• Python 3.7+ installed
• Volatility 3 framework installed (pip install volatility3)
• Memory dump in raw, ELF, or crash dump format
• Appropriate symbol tables (ISF files) for the target OS version
• Sufficient disk space for analysis output (2-3x memory dump size)
• Optional: YARA rules for malware scanning in memory

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()}