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analyzing-memory-forensics-with-lime-and-volatility

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Atualizado11 de junho de 2026 às 20:28

Performs Linux memory acquisition using LiME (Linux Memory Extractor) kernel module and analysis with Volatility 3 framework. Extracts process lists, network connections, bash history, loaded kernel modules, and injected code from Linux memory images. Use when performing incident response on compromised Linux systems.

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b3belov

b3belov/security-superpowers

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Ocupações relacionadasSOC

Baseado na classificação ocupacional SOC

Analistas de segurança da informaçãoInformática e Matemática·SOC 15-1212

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SKILL.md

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name	analyzing-memory-forensics-with-lime-and-volatility
description	Performs Linux memory acquisition using LiME (Linux Memory Extractor) kernel module and analysis with Volatility 3 framework. Extracts process lists, network connections, bash history, loaded kernel modules, and injected code from Linux memory images. Use when performing incident response on compromised Linux systems.
license	Apache-2.0
metadata	{"domain":"cybersecurity","subdomain":"security-operations","tags":["memory-forensics","linux-forensics","lime","volatility","incident-response","kernel-modules"],"version":"1.0","author":"mahipal","nist_csf":["DE.CM-01","RS.MA-01","GV.OV-01","DE.AE-02"],"mitre_attack":["T1055","T1003.001","T1620","T1564.001"]}

Analyzing Memory Forensics with LiME and Volatility

When to Use

When investigating security incidents that require analyzing memory forensics with lime and volatility
When building detection rules or threat hunting queries for this domain
When SOC analysts need structured procedures for this analysis type
When validating security monitoring coverage for related attack techniques

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

Instructions

Acquire Linux memory using LiME kernel module, then analyze with Volatility 3 to extract forensic artifacts from the memory image.

# LiME acquisition
insmod lime-$(uname -r).ko "path=/evidence/memory.lime format=lime"

# Volatility 3 analysis
vol3 -f /evidence/memory.lime linux.pslist
vol3 -f /evidence/memory.lime linux.bash
vol3 -f /evidence/memory.lime linux.sockstat

import volatility3
from volatility3.framework import contexts, automagic
from volatility3.plugins.linux import pslist, bash, sockstat

# Programmatic Volatility 3 usage
context = contexts.Context()
automagics = automagic.available(context)

Key analysis steps:

Acquire memory with LiME (format=lime or format=raw)
List processes with linux.pslist, compare with linux.psscan
Extract bash command history with linux.bash
List network connections with linux.sockstat
Check loaded kernel modules with linux.lsmod for rootkits

Examples

# Full forensic workflow
vol3 -f memory.lime linux.pslist | grep -v "\[kthread\]"
vol3 -f memory.lime linux.bash
vol3 -f memory.lime linux.malfind
vol3 -f memory.lime linux.lsmod

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name	analyzing-memory-forensics-with-lime-and-volatility
description	Performs Linux memory acquisition using LiME (Linux Memory Extractor) kernel module and analysis with Volatility 3 framework. Extracts process lists, network connections, bash history, loaded kernel modules, and injected code from Linux memory images. Use when performing incident response on compromised Linux systems.
license	Apache-2.0
metadata	{"domain":"cybersecurity","subdomain":"security-operations","tags":["memory-forensics","linux-forensics","lime","volatility","incident-response","kernel-modules"],"version":"1.0","author":"mahipal","nist_csf":["DE.CM-01","RS.MA-01","GV.OV-01","DE.AE-02"],"mitre_attack":["T1055","T1003.001","T1620","T1564.001"]}

Analyzing Memory Forensics with LiME and Volatility

When to Use

When investigating security incidents that require analyzing memory forensics with lime and volatility
When building detection rules or threat hunting queries for this domain
When SOC analysts need structured procedures for this analysis type
When validating security monitoring coverage for related attack techniques

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

Instructions

Acquire Linux memory using LiME kernel module, then analyze with Volatility 3 to extract forensic artifacts from the memory image.

# LiME acquisition
insmod lime-$(uname -r).ko "path=/evidence/memory.lime format=lime"

# Volatility 3 analysis
vol3 -f /evidence/memory.lime linux.pslist
vol3 -f /evidence/memory.lime linux.bash
vol3 -f /evidence/memory.lime linux.sockstat

import volatility3
from volatility3.framework import contexts, automagic
from volatility3.plugins.linux import pslist, bash, sockstat

# Programmatic Volatility 3 usage
context = contexts.Context()
automagics = automagic.available(context)

Key analysis steps:

Acquire memory with LiME (format=lime or format=raw)
List processes with linux.pslist, compare with linux.psscan
Extract bash command history with linux.bash
List network connections with linux.sockstat
Check loaded kernel modules with linux.lsmod for rootkits

Examples

# Full forensic workflow
vol3 -f memory.lime linux.pslist | grep -v "\[kthread\]"
vol3 -f memory.lime linux.bash
vol3 -f memory.lime linux.malfind
vol3 -f memory.lime linux.lsmod