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Analyzing Memory Forensics With Lime And Volatility

  • 261 installs
  • 27.3k repo stars
  • Updated August 2, 2026
  • mukul975/anthropic-cybersecurity-skills

Analyzing Memory Forensics with LiME and Volatility is an agent skill that walks through Linux memory acquisition and Volatility-based analysis for security investigations.

About

Analyzing Memory Forensics with LiME and Volatility is an agent skill aimed at builders and small teams who need to investigate suspected compromise on Linux systems using industry-standard memory capture and framework-based analysis. The catalog entry ships under Apache License 2.0 as part of a cybersecurity skills bundle; invoke it when you must preserve volatile evidence, parse process and network artifacts from a RAM image, and document findings for security review. It is advanced, hands-on work—expect kernel modules, analyst tooling, and careful chain-of-custody—not a substitute for a full SOC. Prism lists it so solo operators shipping APIs or internal services have a procedural anchor when escalating from app logs to host memory forensics during Ship-phase security reviews or post-incident validation.

  • Memory forensics workflow oriented around LiME acquisition and Volatility analysis
  • Supports incident response when disk logs are insufficient or malware is memory-resident
  • Fits Anthropic cybersecurity skills collection patterns for structured investigation steps
  • Apache 2.0 licensed skill package suitable for audit and compliance contexts

Analyzing Memory Forensics With Lime And Volatility by the numbers

  • 261 all-time installs (skills.sh)
  • +15 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #661 of 2,203 Security skills by installs in the Skillselion catalog
  • Security screen: MEDIUM risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-memory-forensics-with-lime-and-volatility

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Listed on Skillselion
Installs261
repo stars27.3k
Security audit1 / 3 scanners passed
Last updatedAugust 2, 2026
Repositorymukul975/anthropic-cybersecurity-skills

What it does

Guide memory acquisition with LiME and analysis with Volatility when investigating compromised hosts or validating incident hypotheses.

Who is it for?

Best when you're performing structured Linux memory forensics during a security incident or pre-launch hardening review.

Skip if: Routine application debugging, Cloudflare Worker-only stacks with no OS memory to image, or teams without legal authority to capture host memory.

When should I use this skill?

Investigating Linux host compromise or validating memory-resident threats when LiME capture and Volatility analysis are appropriate.

What you get

You obtain a memory image with LiME-compatible capture and analyze it with Volatility-oriented steps to support incident conclusions and remediation.

  • Memory capture procedure notes
  • Volatility-oriented analysis findings for remediation

Files

SKILL.mdMarkdownGitHub ↗

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

Related skills

How it compares

Forensic investigation workflow for RAM images, not a passive dependency scanner or generic code review skill.

FAQ

Who is analyzing-memory-forensics-with-lime-and-volatility for?

Developers and operators who must perform or oversee Linux memory forensics using LiME and Volatility during security incidents or audits.

When should I use analyzing-memory-forensics-with-lime-and-volatility?

During Ship security work or Operate incident response when you need volatile evidence from a Linux system and structured Volatility analysis.

Is analyzing-memory-forensics-with-lime-and-volatility safe to install?

Treat it as high-privilege forensic tooling—review the Security Audits panel on this page and only run capture/analysis on systems you own or are authorized to examine.

Securityauditappseccompliance

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