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

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

github.com/mukul975Security35.2k321 installsUpdated 8w ago
Repository

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

A procedure for security analysts to acquire Linux memory with LiME and inspect the image using Volatility 3. It outlines process, shell-history, network, and kernel-module checks.

Key features

  1. 01Acquire Linux memory with LiME
  2. 02Analyze images with Volatility 3
  3. 03Compare process lists and scans
  4. 04Extract Bash command history
  5. 05Inspect network connections and modules

Use cases

  1. 01Collecting memory during incident response
  2. 02Checking for hidden or unexpected processes
  3. 03Reviewing command history and network activity
  4. 04Investigating suspicious kernel modules

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-memory-forensics-with-lime-and-volatility

After installing, type/analyzing-memory-forensics-with-lime-and-volatilityin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

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

Details

From the project README

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

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