v1.0 to v1.0
17 added, 7 removed. Audit A to A.
---
name: extracting-memory-artifacts-with-rekall
- description: 'Uses Rekall memory forensics framework to analyze memory dumps for process hollowing, injected code via VAD
- anomalies, hidden processes, and rootkit detection. Applies plugins like pslist, psscan, vadinfo, malfind, and dlllist to
- extract forensic artifacts from Windows memory images. Use during incident response memory analysis.
+ description: 'Uses Rekall memory forensics framework to analyze memory dumps for process
+ hollowing, injected code via VAD anomalies, hidden processes, and rootkit detection.
+ Applies plugins like pslist, psscan, vadinfo, malfind, and dlllist to extract forensic
+ artifacts from Windows memory images. Use during incident response memory analysis.
'
domain: cybersecurity
subdomain: security-operations
tags:
- - extracting
- - memory
- - artifacts
- - with
+ - memory-forensics
+ - rekall
+ - process-hollowing
+ - code-injection
+ - vad-analysis
+ - incident-response
+ - security-operations
version: '1.0'
author: mahipal
license: Apache-2.0
nist_csf:
- DE.CM-01
- RS.MA-01
- GV.OV-01
- DE.AE-02
+ mitre_attack:
+ - T1078
+ - T1190
+ - T1059
+ - T1055
+ - T1005
---
# Extracting Memory Artifacts with Rekall
## When to Use
- When performing authorized security testing that involves extracting memory artifacts with rekall
- When analyzing malware samples or attack artifacts in a controlled environment
- When conducting red team exercises or penetration testing engagements
- When building detection capabilities based on offensive technique understanding
## 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
Use Rekall to analyze memory dumps for signs of compromise including process
injection, hidden processes, and suspicious network connections.
```python
from rekall import session
from rekall import plugins
# Create a Rekall session with a memory image
s = session.Session(
filename="/path/to/memory.raw",
autodetect=["rsds"],
profile_path=["https://github.com/google/rekall-profiles/raw/master"]
)
# List processes
for proc in s.plugins.pslist():
print(proc)
# Detect injected code
for result in s.plugins.malfind():
print(result)
```
Key analysis steps:
1. Load memory image and auto-detect profile
2. Run pslist and psscan to find hidden processes
3. Use malfind to detect injected/hollowed code in process VADs
4. Examine network connections with netscan
5. Extract suspicious DLLs and drivers with dlllist/modules
## Examples
```python
from rekall import session
s = session.Session(filename="memory.raw")
# Compare pslist vs psscan for hidden processes
pslist_pids = set(p.pid for p in s.plugins.pslist())
psscan_pids = set(p.pid for p in s.plugins.psscan())
hidden = psscan_pids - pslist_pids
print(f"Hidden PIDs: {hidden}")
```