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

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Structure

• Ships 1 executable scriptscripts/agent.py. Review what they do before enabling the skill for agents with tool access.
• The source hub's security checks flagged this skillGen Agent Trust Hub: warn (The skill facilitates Linux memory forensics using LiME and Volatility. Its primary security considerations involve the requirement for root privileges to load kernel modules and the ingestion of potentially malicious data from system memory images, which could impact detection logic.); Snyk: warn (Risk: MEDIUM · 1 issue)

SKILL.md

---
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.

```bash
# 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
```

```python
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

```bash
# 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
```