Digital Forensics Tools by YogSec – A Comprehensive Guide

Listen to this Post

👉 GitHub Repo: https://lnkd.in/g7zDqGbj

YogSec’s Digital-Forensics-Tools repository is a curated collection of essential tools for digital forensics, investigation, data recovery, and security analysis. The repo covers:

  • 💾 Disk Forensics: Tools like Autopsy, The Sleuth Kit, and FTK Imager for disk imaging & recovery.
  • 🧠 Memory Forensics: Volatility, Rekall, and DumpIt for deep memory analysis.
  • 🔎 File Recovery: Scalpel, TestDisk, and Recuva to retrieve lost data.

You Should Know: Practical Digital Forensics Commands & Tools

1. Disk Forensics

  • FTK Imager (Windows) – Acquire disk images:
    ftkimager --source C: --dest E:\evidence\ --case 001 --e01
    
  • The Sleuth Kit (Linux) – Analyze disk partitions:
    mmls /dev/sda1  List partitions
    fls -r /dev/sda1  Recover deleted files
    

2. Memory Forensics

  • Volatility (Linux/Windows) – Analyze RAM dumps:
    volatility -f memory.dmp imageinfo  Identify OS profile
    volatility -f memory.dmp --profile=Win10x64 pslist  List processes
    
  • Rekall – Extract registry hives:
    rekal -f memory.raw --profile Win10 hooks  Detect kernel hooks
    

3. File Recovery

  • TestDisk (Linux/Windows) – Repair partitions:
    testdisk /dev/sdb  Recover lost partitions
    
  • Scalpel (Linux) – Carve files from disk:
    scalpel -c /etc/scalpel.conf /dev/sdc -o recovered_files/
    

4. Network Forensics

  • Wireshark – Analyze PCAP files:
    wireshark -r traffic.pcap -Y "http.request"  Filter HTTP requests
    
  • Tshark (CLI Alternative):
    tshark -r traffic.pcap -T fields -e ip.src -e ip.dst
    

What Undercode Say

Digital forensics is critical in incident response, malware analysis, and legal investigations. Mastering these tools ensures efficient evidence collection and analysis. Key takeaways:
– Always hash acquired evidence (md5sum image.dd).
– Use write-blockers to prevent evidence tampering.
– Automate forensics with Python scripts (e.g., `pytsk3` for disk parsing).

Expected Output:

A structured forensic report with:

  • Timeline analysis (log2timeline).
  • Malware indicators (YARA rules).
  • Verified file integrity (SHA-256 checksums).

🔗 Explore More: YogSec’s GitHub | Volatility Docs

References:

Reported By: Ouardi Mohamed – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅

Join Our Cyber World:

💬 Whatsapp | 💬 TelegramFeatured Image