Extract DPAPI-protected secrets such as credentials and browser data offline and online.
The English summary is being prepared. Showing the original description.
andycungkrinx91/konoha10Updated Oct 21, 2026
FreePublished on GitHub
analyzing-memory-forensics-with-lime-and-volatility
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.
The English summary is being prepared. Showing the original description.
See how to installFiles included (3)
- SKILL.md2.5 KB
- references/api-reference.md1.6 KB
- scripts/agent.py7.2 KB
SKILL.md (original)
Review the instructions the agent will receive before you install.
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
Reviews
No reviews yet. Tell others what you thought.
Comments
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
More skills from this repository
Audit, detect, and remediate Shadow Credentials misconfigurations on msDS-KeyCredentialLink in Active Directory. Focuses on access-controls, monitoring Event ID 5136, and credential-management hygiene.
The English summary is being prepared. Showing the original description.
andycungkrinx91/konoha10Updated Oct 21, 2026
Prepare a defense-contractor environment for CMMC Level 2 certification: scope CUI and FCI, implement the 110 NIST SP 800-171 Rev 2 security requirements across 14 families, compute the SPRS score with the DoD Assessment Methodology, manage a compliant POA&M, and ready the organization for a C3PAO assessment. Use when an organization handles Controlled Unclassified Information (CUI) under a DoD contract, when a contract carries DFARS clause 252.204-7012/7019/7020/7021, when preparing for or responding to a CMMC assessment, when computing or improving an SPRS score, when building a System Security Plan or POA&M for 800-171, or when scoping which systems are in the CUI boundary. Keywords: CMMC, CMMC Level 2, NIST 800-171, SP 800-171 Rev 2, CUI, FCI, SPRS, DFARS 7012, C3PAO, POA&M, System Security Plan, DoD Assessment Methodology, 110 controls, defense industrial base, DIB, FedRAMP equivalency.
The English summary is being prepared. Showing the original description.
andycungkrinx91/konoha10Updated Oct 21, 2026
Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
The English summary is being prepared. Showing the original description.
andycungkrinx91/konoha10Updated Oct 21, 2026
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
The English summary is being prepared. Showing the original description.
andycungkrinx91/konoha10Updated Oct 21, 2026
Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.
The English summary is being prepared. Showing the original description.
andycungkrinx91/konoha10Updated Oct 21, 2026