Skill Market

analyzing windows registry for artifacts

Extract and analyze Windows Registry hives to uncover user activity, installed software, autostart entries, and

GitHub
githubcommunityai-agentsclaude-codecloud-securitycybersecuritydevsecopsethical-hacking
0.0
0 installs33.4K GitHub starsby mukul975

Skill Introduction

Overview
Extract and analyze Windows Registry hives to uncover user activity, installed software, autostart entries, and

Core value

Turns reusable Debugging know-how into an installable skill, helping users complete github, community, ai-agents, claude-code work faster.

Target users

  • Developers, testers, and maintainers who handle Debugging tasks in Focus Code.
  • Teams that already trust workflows or content from mukul975.
  • Users who want standardized prompts, steps, or conventions instead of repeating setup work.

Best practices

  • Read the skill content first to confirm required inputs, expected outputs, and dependencies.
  • Try it on a small task before relying on it for critical work.
  • Add project-specific constraints such as coding style, target platform, test expectations, and delivery format.
  • For external sources, verify the source link, version, and recent maintenance activity.

Best use cases

  • Tasks related to github, community, ai-agents, claude-code that need a reusable execution flow.
  • Converting a community repo, team convention, or personal workflow into day-to-day assistance.
  • Starting from a proven skill instead of writing prompts or procedures from scratch.

Limits and boundaries

  • Results depend on the quality of the original skill content and may need human correction.
  • It does not replace code review, tests, security review, or professional judgment.
  • External tools, APIs, account permissions, and local dependencies still need separate setup.

Differentiation

  • Structured around Debugging, making it easier to discover and reuse than loose prompt snippets.
  • Marked as GitHub, which helps users judge trust and maintenance expectations.
  • Keeps the original source link available for repository, documentation, or discussion follow-up.
  • Tagged with github, community, ai-agents, claude-code, so it can be filtered by concrete task intent.

Install and use

Install
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SKILL.md

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name: analyzing-windows-registry-for-artifacts description: Extract and analyze Windows Registry hives to uncover user activity, installed software, autostart entries, and evidence of system compromise. domain: cybersecurity subdomain: digital-forensics tags:

  • forensics
  • windows-registry
  • artifact-analysis
  • regripper
  • registry-explorer
  • evidence-collection version: '1.0' author: mahipal license: Apache-2.0 nist_csf:
  • RS.AN-01
  • RS.AN-03
  • DE.AE-02
  • RS.MA-01

Analyzing Windows Registry for Artifacts

When to Use

  • When investigating user activity on a Windows system during an incident
  • For identifying autorun/persistence mechanisms used by malware
  • When tracing installed software, USB devices, and network connections
  • During insider threat investigations to reconstruct user actions
  • For correlating registry timestamps with other forensic artifacts

Prerequisites

  • Forensic image or extracted registry hive files
  • RegRipper, Registry Explorer (Eric Zimmerman), or python-registry
  • Access to registry hive locations (SAM, SYSTEM, SOFTWARE, NTUSER.DAT, UsrClass.dat)
  • Understanding of Windows Registry structure (hives, keys, values)
  • SIFT Workstation or forensic analysis environment

Workflow

Step 1: Extract Registry Hives from the Forensic Image

# Mount the forensic image read-only
mkdir /mnt/evidence
mount -o ro,loop,offset=$((2048*512)) /cases/case-2024-001/images/evidence.dd /mnt/evidence

# Copy system registry hives
cp /mnt/evidence/Windows/System32/config/SAM /cases/case-2024-001/registry/
cp /mnt/evidence/Windows/System32/config/SYSTEM /cases/case-2024-001/registry/
cp /mnt/evidence/Windows/System32/config/SOFTWARE /cases/case-2024-001/registry/
cp /mnt/evidence/Windows/System32/config/SECURITY /cases/case-2024-001/registry/
cp /mnt/evidence/Windows/System32/config/DEFAULT /cases/case-2024-001/registry/

# Copy user-specific hives
cp /mnt/evidence/Users/*/NTUSER.DAT /cases/case-2024-001/registry/
cp /mnt/evidence/Users/*/AppData/Local/Microsoft/Windows/UsrClass.dat /cases/case-2024-001/registry/

# Copy transaction logs (for dirty hive recovery)
cp /mnt/evidence/Windows/System32/config/*.LOG* /cases/case-2024-001/registry/logs/

# Hash all extracted hives
sha256sum /cases/case-2024-001/registry/* > /cases/case-2024-001/registry/hive_hashes.txt

Step 2: Analyze with RegRipper for Automated Artifact Extraction

# Install RegRipper
git clone https://github.com/keydet89/RegRipper3.0.git /opt/regripper

# Run RegRipper against NTUSER.DAT (user profile)
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/NTUSER.DAT \
   -f ntuser > /cases/case-2024-001/analysis/ntuser_report.txt

# Run against SYSTEM hive
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SYSTEM \
   -f system > /cases/case-2024-001/analysis/system_report.txt

# Run against SOFTWARE hive
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SOFTWARE \
   -f software > /cases/case-2024-001/analysis/software_report.txt

# Run against SAM hive (user accounts)
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SAM \
   -f sam > /cases/case-2024-001/analysis/sam_report.txt

# Run specific plugins
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/NTUSER.DAT \
   -p userassist > /cases/case-2024-001/analysis/userassist.txt

perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SYSTEM \
   -p usbstor > /cases/case-2024-001/analysis/usbstor.txt

Step 3: Extract Persistence and Autorun Entries

# Using python-registry for targeted extraction
pip install python-registry

python3 << 'PYEOF'
from Registry import Registry

# Open SOFTWARE hive
reg = Registry.Registry("/cases/case-2024-001/registry/SOFTWARE")

# Check Run keys (autostart)
autorun_paths = [
    "Microsoft\\Windows\\CurrentVersion\\Run",
    "Microsoft\\Windows\\CurrentVersion\\RunOnce",
    "Microsoft\\Windows\\CurrentVersion\\RunServices",
    "Microsoft\\Windows\\CurrentVersion\\Policies\\Explorer\\Run",
    "Wow6432Node\\Microsoft\\Windows\\CurrentVersion\\Run"
]

for path in autorun_paths:
    try:
        key = reg.open(path)
        print(f"\n=== {path} (Last Modified: {key.timestamp()}) ===")
        for value in key.values():
            print(f"  {value.name()}: {value.value()}")
    except Registry.RegistryKeyNotFoundException:
        pass

# Check installed services
key = reg.open("Microsoft\\Windows NT\\CurrentVersion\\Svchost")
print(f"\n=== Svchost Groups ===")
for value in key.values():
    print(f"  {value.name()}: {value.value()}")
PYEOF

# Check NTUSER.DAT for user-specific autorun
python3 << 'PYEOF'
from Registry import Registry

reg = Registry.Registry("/cases/case-2024-001/registry/NTUSER.DAT")

user_autorun = [
    "Software\\Microsoft\\Windows\\CurrentVersion\\Run",
    "Software\\Microsoft\\Windows\\CurrentVersion\\RunOnce",
    "Software\\Microsoft\\Windows\\CurrentVersion\\Explorer\\StartupApproved\\Run"
]

for path in user_autorun:
    try:
        key = reg.open(path)
        print(f"\n=== {path} (Last Modified: {key.timestamp()}) ===")
        for value in key.values():
            print(f"  {value.name()}: {value.value()}")
    except Registry.RegistryKeyNotFoundException:
        pass
PYEOF

Step 4: Analyze User Activity Artifacts

# Extract UserAssist data (program execution history with ROT13 encoding)
python3 << 'PYEOF'
from Registry import Registry
import codecs, struct, datetime

reg = Registry.Registry("/cases/case-2024-001/registry/NTUSER.DAT")

ua_path = "Software\\Microsoft\\Windows\\CurrentVersion\\Explorer\\UserAssist"
key = reg.open(ua_path)

for guid_key in key.subkeys():
    count_key = guid_key.subkey("Count")
    print(f"\n=== {guid_key.name()} ===")
    for value in count_key.values():
        decoded_name = codecs.decode(value.name(), 'rot_13')
        data = value.value()
        if len(data) >= 16:
            run_count = struct.unpack('<I', data[4:8])[0]
            focus_count = struct.unpack('<I', data[8:12])[0]
            timestamp = struct.unpack('<Q', data[60:68])[0] if len(data) >= 68 else 0
            if timestamp > 0:
                ts = datetime.datetime(1601,1,1) + datetime.timedelta(microseconds=timestamp//10)
                print(f"  {decoded_name}: Runs={run_count}, Focus={focus_count}, Last={ts}")
            else:
                print(f"  {decoded_name}: Runs={run_count}, Focus={focus_count}")
PYEOF

# Extract Recent Documents (MRU lists)
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/NTUSER.DAT \
   -p recentdocs > /cases/case-2024-001/analysis/recentdocs.txt

# Extract typed URLs (browser)
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/NTUSER.DAT \
   -p typedurls > /cases/case-2024-001/analysis/typedurls.txt

# Extract typed paths in Explorer
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/NTUSER.DAT \
   -p typedpaths > /cases/case-2024-001/analysis/typedpaths.txt

Step 5: Extract System and Network Information

# Computer name and OS version from SYSTEM hive
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SYSTEM \
   -p compname > /cases/case-2024-001/analysis/system_info.txt

# Network interfaces and configuration
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SYSTEM \
   -p nic2 >> /cases/case-2024-001/analysis/system_info.txt

# Wireless network history
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SOFTWARE \
   -p networklist > /cases/case-2024-001/analysis/network_history.txt

# Timezone configuration
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SYSTEM \
   -p timezone > /cases/case-2024-001/analysis/timezone.txt

# Shutdown time
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SYSTEM \
   -p shutdown > /cases/case-2024-001/analysis/shutdown.txt

# Installed software from Uninstall keys
perl /opt/regripper/rip.pl -r /cases/case-2024-001/registry/SOFTWARE \
   -p uninstall > /cases/case-2024-001/analysis/installed_software.txt

Key Concepts

ConceptDescription
Registry hiveBinary file storing a section of the registry (SAM, SYSTEM, SOFTWARE, NTUSER.DAT)
MRU (Most Recently Used)Lists tracking recently accessed files, commands, and search terms
UserAssistROT13-encoded registry entries tracking program execution with timestamps
ShimCacheApplication compatibility cache recording executed programs
AmCacheDetailed execution history including SHA-1 hashes of executables
BAM/DAMBackground/Desktop Activity Moderator tracking program execution in Win10+
Last Write TimeTimestamp on registry keys indicating when they were last modified
Transaction logsJournal files allowing recovery of registry state after improper shutdown

Tools & Systems

ToolPurpose
RegRipperAutomated registry artifact extraction with plugin architecture
Registry ExplorerEric Zimmerman GUI tool for interactive registry analysis
python-registryPython library for programmatic registry hive parsing
RECmdEric Zimmerman command-line registry analysis tool
yarpYet Another Registry Parser for Python-based analysis
AppCompatCacheParserDedicated ShimCache/AppCompatCache parser
AmcacheParserDedicated AmCache.hve analysis tool
ShellBags ExplorerSpecialized tool for analyzing ShellBag artifacts

Common Scenarios

Scenario 1: Malware Persistence Investigation Extract SOFTWARE and NTUSER.DAT hives, check all Run/RunOnce keys for unauthorized entries, examine services for suspicious additions, check scheduled tasks registry keys, correlate autorun timestamps with malware execution timeline.

Scenario 2: User Activity Reconstruction Analyze UserAssist for program execution history, examine RecentDocs for accessed files, check TypedPaths for Explorer navigation, extract ShellBags for folder access patterns, build a timeline of user activity around the incident window.

Scenario 3: Unauthorized Software Detection Parse Uninstall keys for all installed applications, compare against approved software baseline, check BAM/DAM for recently executed programs not in approved list, examine AppCompatCache for execution evidence even after uninstallation.

Scenario 4: USB Data Exfiltration Investigation Extract USBSTOR entries from SYSTEM hive for connected devices, correlate device serial numbers with MountedDevices, check NTUSER.DAT MountPoints2 for user access to removable media, examine SetupAPI logs for first-connection timestamps.

Output Format

Registry Analysis Summary:
  System: DESKTOP-ABC123 (Windows 10 Pro Build 19041)
  Timezone: Eastern Standard Time (UTC-5)
  Last Shutdown: 2024-01-18 23:45:12 UTC

  Autorun Entries:
    HKLM Run:     5 entries (1 suspicious: "updater.exe" -> C:\ProgramData\svc\updater.exe)
    HKCU Run:     3 entries (all legitimate)
    Services:     142 entries (2 unknown: "WinDefSvc", "SysMonAgent")

  User Activity (NTUSER.DAT):
    UserAssist Programs:  234 entries
    Recent Documents:     89 entries
    Typed URLs:           45 entries
    Typed Paths:          12 entries

  USB Devices Connected:
    - Kingston DataTraveler (Serial: 0019E06B4521) - First: 2024-01-10, Last: 2024-01-18
    - WD My Passport (Serial: 575834314131) - First: 2024-01-15, Last: 2024-01-15

  Installed Software:     127 applications
  Suspicious Findings:    3 items flagged for review

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