Volatility Named
Volatility names memory forensics framework literacy — parse RAM dumps on YOUR $DFIR_LAB; not live RAM capture of stranger machines.
Visual · t26_volatility_named
Volatility literacy. $DFIR_LAB only. Original Cyberlium.
RAM holds processes, DLLs, and connections Volatility-class tools parse — authority and volatile-first order still apply.
Volatility 3 (and legacy Volatility 2) analyze memory dumps: processes, cmdline, DLLs, network sockets, registry in memory, malware injection indicators — plugin/model based. Requires correct OS profile/symbol context. Live capture (WinPMEM, LiME-class) needs authority and volatile-first planning. Cyberlium treats Volatility as tool literacy on YOUR $DFIR_LAB memory dumps — course.mem files, VM snapshots — never capturing neighbor laptop RAM without legal scope. Next: Process Artifacts.
1. Volatility workflow (named)
Obtain authorized memory dump → verify hash → select framework (Volatility 3 vs 2) → choose symbol table / ISF for OS build → run plugins (pslist, netscan, cmdline class names) → document findings with UTC timestamps.
On $DFIR_LAB, list three plugin classes and what artifact type each reveals — no live capture required in this lesson.
Command guide
Try these commands — Volatility workflow (named)
═══ LINUX / FORENSICS (Volatility 3 Syntax) ═══
List active processes from raw memory dump
Command — copy this
python3 vol.py -f memory.raw windows.pslist
Scan for hidden injected code in process memory
Command — copy this
python3 vol.py -f memory.raw windows.malfind
Enumerate network sockets from memory capture
Command — copy this
python3 vol.py -f memory.raw windows.netscan
Primary tools to practice this lesson: curl, python3. Reference sites: Volatility Foundation (https://www.volatilityfoundation.org/); Volatility 3 docs (https://volatility3.readthedocs.io/); RFC 3227 (https://www.rfc-editor.org/rfc/rfc3227). Run every command in the box — install first, then the usage lines — only on YOUR lab / program scope.
2. What memory tools need
Matching OS version symbols — wrong profile yields garbage. Dump must be intact — hash verify like disk images. Memory is volatile source — capture before reboot when incident policy allows.
Defenders pair memory with disk and logs — single-source stories are weak.
3. Tool literacy boundary
Forbidden: live RAM capture on unauthorized hosts, sharing memory dumps with credentials in public chat, or 'finding' injected processes you simulated dishonestly. Allowed: Volatility literacy card — dump source, OS, three plugin purposes.
Ship: Volatility literacy card for $DFIR_LAB memory dump. Next: Process Artifacts.
4. What you ship: Volatility literacy card for $DFIR_LAB
Dump source, OS build, three plugin purposes. $DFIR_LAB named. NO unauthorized live capture. chmod 600.
5. What you record before the next lesson
Date. Volatility card. $DFIR_LAB named. File t26-m05-l01-volatility-named.txt chmod 600.
6. Wrong vs right: tampering evidence vs chain of custody
Worked failure — same MSF word, opposite target. Right never needs a café Wi-Fi or classmate laptop.
- Wrong: Capture classmate RAM without permission. Run plugins with wrong OS profile and report anyway.
- Right: Write Volatility literacy card for YOUR $DFIR_LAB dump. Next: Process Artifacts.
Mission: name Volatility plugins on YOUR dump
1) Cite dump source and OS. 2) List three plugin classes. 3) Tie to CoC exhibit if separate from disk. 4) chmod 600.
Stuck? Ask Cyberlium AI Mentor
OS build mismatch is the #1 student Volatility failure — verify first.
APPLY: Volatility literacy on Cyberlium means:
APPLY: True or False: Memory dumps should be hash-verified like disk images.
APPLY: Wrong OS symbol profile typically yields:
Process Artifacts
Part of Digital Forensics (DFIR) with AI — Memory Literacy.
Memory Order
Part of Digital Forensics (DFIR) with AI — Memory Literacy.
Lab — Memory
Part of Digital Forensics (DFIR) with AI — Memory Literacy.