What it does. 'Performs Linux memory acquisition using LiME (Linux Memory Extractor) Part of mukul975/Anthropic-Cybersecurity-Skills (817 security skills) (mukul975/Anthropic-Cybersecurity-Skills).

Install

• npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-memory-forensics-with-lime-and-volatility, or copy the skill folder into ~/.claude/skills/analyzing-memory-forensics-with-lime-and-volatility/.
• Raw file: curl -sL https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/HEAD/skills/analyzing-memory-forensics-with-lime-and-volatility/SKILL.md

SKILL.md (verbatim)

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.

  '
domain: cybersecurity
subdomain: security-operations
tags:
- memory-forensics
- linux-forensics
- lime
- volatility
- incident-response
- kernel-modules
version: '1.0'
author: mahipal
license: Apache-2.0
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:

1. Acquire memory with LiME (format=lime or format=raw)
2. List processes with linux.pslist, compare with linux.psscan
3. Extract bash command history with linux.bash
4. List network connections with linux.sockstat
5. 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

Other files in this skill

• LICENSE
• references/api-reference.md
• scripts/agent.py

references/api-reference.md (verbatim)

API Reference: Analyzing Memory Forensics with LiME and Volatility

LiME (Linux Memory Extractor)

# Build LiME module
cd LiME/src && make

# Acquire memory (lime format - includes metadata)
insmod lime-$(uname -r).ko "path=/evidence/mem.lime format=lime"

# Acquire memory (raw format)
insmod lime-$(uname -r).ko "path=/evidence/mem.raw format=raw"

# Acquire over network
insmod lime.ko "path=tcp:4444 format=lime"
# On forensic workstation: nc target 4444 > mem.lime

Volatility 3 Linux Plugins

Volatility 3 CLI

vol3 -f memory.lime linux.pslist
vol3 -f memory.lime linux.bash
vol3 -f memory.lime linux.sockstat
vol3 -f memory.lime linux.malfind
vol3 -f memory.lime linux.lsmod
vol3 -f memory.lime linux.check_afinfo

Hidden Process Detection

# Compare pslist (linked list) vs psscan (brute force)
vol3 -f mem.lime linux.pslist > pslist.txt
vol3 -f mem.lime linux.psscan > psscan.txt
diff pslist.txt psscan.txt

References

• LiME: https://github.com/504ensicsLabs/LiME
• Volatility 3: https://github.com/volatilityfoundation/volatility3
• Volatility 3 docs: https://volatility3.readthedocs.io/

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