Communitygithub.com

analyzing-windows-shellbag-artifacts

Analyze Windows Shellbag (BagMRU) registry artifacts with SBECmd and

analyzing-windows-shellbag-artifacts 是什麼?

analyzing-windows-shellbag-artifacts is a Claude Code agent skill that analyze Windows Shellbag (BagMRU) registry artifacts with SBECmd and.

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-windows-shellbag-artifacts

在你喜歡的 AI 中提問

開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

Analyzing Windows Shellbag Artifacts

Overview

Shellbags are Windows registry artifacts that track how users interact with folders through Windows Explorer, storing view settings such as icon size, window position, sort order, and view mode. From a forensic perspective, Shellbags provide definitive evidence of folder access -- even folders that no longer exist on the system. When a user browses to a folder via Windows Explorer, the Open/Save dialog, or the Control Panel, a Shellbag entry is created or updated in the user's registry hive. These entries persist after folder deletion, drive disconnection, and even across user profile resets, making them invaluable for proving that a user navigated to specific directories on local drives, USB devices, network shares, or zip archives.

When to Use

  • When investigating security incidents that require analyzing windows shellbag artifacts
  • When building detection rules or threat hunting queries for this domain
  • When SOC analysts need structured procedures for this analysis type
  • When validating security monitoring coverage for related attack techniques

Prerequisites

  • Familiarity with digital forensics 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

Registry Locations

Windows 7/8/10/11

HiveKey PathStores
NTUSER.DATSoftware\Microsoft\Windows\Shell\BagMRUFolder hierarchy tree
NTUSER.DATSoftware\Microsoft\Windows\Shell\BagsView settings per folder
UsrClass.datLocal Settings\Software\Microsoft\Windows\Shell\BagMRUDesktop/Explorer shell
UsrClass.datLocal Settings\Software\Microsoft\Windows\Shell\BagsAdditional view settings

BagMRU Structure

The BagMRU key contains a hierarchical tree of numbered subkeys representing the directory structure. Each subkey value contains a Shell Item (SHITEMID) binary blob encoding the folder identity:

  • Root (BagMRU): Desktop namespace root
  • BagMRU\0: Typically "My Computer"
  • BagMRU\0\0: First drive (e.g., C:)
  • BagMRU\0\0\0: First subfolder on C:

Each Shell Item contains:

  • Item type (folder, drive, network, zip, control panel)
  • Short name (8.3 format)
  • Long name (Unicode)
  • Creation/modification timestamps
  • MFT entry/sequence for NTFS folders

Analysis with EZ Tools

SBECmd (Command Line)

# Parse shellbags from a directory of registry hives
SBECmd.exe -d "C:\Evidence\Registry" --csv C:\Output --csvf shellbags.csv

# Parse from a live system (requires admin)
SBECmd.exe --live --csv C:\Output --csvf live_shellbags.csv

# Key output columns:
# AbsolutePath - Full reconstructed path
# CreatedOn - When the folder was first browsed
# ModifiedOn - When view settings were last changed
# AccessedOn - Last access timestamp
# ShellType - Type of shell item (Directory, Drive, Network, etc.)
# Value - Raw shell item data

ShellBags Explorer (GUI)

# Launch GUI tool for interactive analysis
ShellBagsExplorer.exe

# Load registry hives: File > Load Hive
# Navigate the tree structure to see folder hierarchy
# Right-click entries for detailed shell item properties

Forensic Investigation Scenarios

Proving USB Device Browsing

Shellbag Path: My Computer\E:\Confidential\Project_Files
ShellType: Directory (on removable volume)
CreatedOn: 2025-03-15 09:30:00 UTC

This proves the user navigated to E:\Confidential\Project_Files
via Windows Explorer, even if the USB drive is no longer connected.
The volume letter E: and directory timestamps can be correlated
with USBSTOR and MountPoints2 registry entries.

Detecting Network Share Access

Shellbag Path: \\FileServer01\Finance\Q4_Reports
ShellType: Network Location
AccessedOn: 2025-02-20 14:15:00 UTC

This proves the user browsed to a network share, even if
the share has been decommissioned or access revoked.

Identifying Deleted Folder Knowledge

Shellbag Path: C:\Users\suspect\Documents\Exfiltration_Staging
ShellType: Directory
CreatedOn: 2025-01-10 08:00:00 UTC

Even though C:\Users\suspect\Documents\Exfiltration_Staging
no longer exists, the Shellbag entry proves the user
created and navigated to this folder.

Limitations

  • Shellbags only record folder-level interactions, not individual file access
  • Only created through Windows Explorer shell and Open/Save dialogs
  • Command-line access (cmd, PowerShell) does not generate Shellbag entries
  • Programmatic file access via APIs does not generate Shellbag entries
  • Timestamps may reflect view setting changes, not necessarily folder access
  • Windows may batch-update Shellbag entries during Explorer shutdown

References

Example Output

$ SBECmd.exe -d "C:\Evidence\Users\jsmith" --csv /analysis/shellbag_output

SBECmd v2.1.0 - ShellBags Explorer (Command Line)
====================================================
Processing hives for user: jsmith
  NTUSER.DAT:  C:\Evidence\Users\jsmith\NTUSER.DAT
  UsrClass.dat: C:\Evidence\Users\jsmith\AppData\Local\Microsoft\Windows\UsrClass.dat

[+] NTUSER.DAT shellbag entries:   456
[+] UsrClass.dat shellbag entries: 1,234
[+] Total shellbag entries:        1,690

--- Folder Access Timeline (Incident Window) ---
Last Accessed (UTC)     | Folder Path                                             | Type        | Access Count
------------------------|---------------------------------------------------------|-------------|-------------
2024-01-15 14:34:05     | C:\Users\jsmith\Downloads                               | File System | 45
2024-01-15 14:36:25     | C:\ProgramData\Updates                                  | File System | 3
2024-01-15 15:05:00     | \\FILESERV01\Finance                                    | Network     | 2
2024-01-15 15:12:30     | \\FILESERV01\Finance\Q4_Reports                          | Network     | 1
2024-01-15 15:30:00     | E:\                                                     | Removable   | 4
2024-01-15 15:30:45     | E:\Backup                                               | Removable   | 3
2024-01-15 15:31:20     | E:\Backup\Corporate_Data                                | Removable   | 2
2024-01-15 16:12:45     | \\FILESERV01\HR\Employees                                | Network     | 1
2024-01-15 16:15:00     | \\FILESERV01\HR\Employees\Records_2024                   | Network     | 1
2024-01-16 02:35:00     | C:\Windows\Temp                                         | File System | 5
2024-01-17 02:44:00     | C:\ProgramData\svc                                     | File System | 2
2024-01-18 01:10:00     | C:\Users\jsmith\AppData\Local\Temp                      | File System | 8

--- Network Share Access ---
  \\FILESERV01\Finance             First: 2023-09-10  Last: 2024-01-15
  \\FILESERV01\Finance\Q4_Reports  First: 2024-01-15  Last: 2024-01-15  (NEW)
  \\FILESERV01\HR\Employees        First: 2024-01-15  Last: 2024-01-15  (NEW)
  \\DC01\SYSVOL                    First: 2023-03-15  Last: 2024-01-16  (anomalous access time)

--- Removable Device Access ---
  E:\ (USB Drive)
    Volume Name:    BACKUP_DRIVE
    First Accessed: 2024-01-15 15:30:00 UTC
    Last Accessed:  2024-01-15 15:45:22 UTC
    Folders Browsed: 3 (E:\, E:\Backup, E:\Backup\Corporate_Data)

--- Deleted/No Longer Existing Paths ---
  C:\ProgramData\Updates\                (folder deleted, shellbag persists)
  C:\ProgramData\svc\                    (folder deleted, shellbag persists)
  C:\Windows\Temp\tools\                 (folder deleted, shellbag persists)

Summary:
  Total unique folders accessed:  1,690
  Network shares accessed:        4 (2 newly accessed during incident)
  Removable media:                1 USB device (data staging suspected)
  Deleted folder evidence:        3 paths (anti-forensics indicator)
  CSV exported to:                /analysis/shellbag_output/

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

abusing-dpapi-for-credential-access

Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys) online or offline using SharpDPAPI, SharpChrome, Mimikatz, or Impacket

abusing-shadow-credentials-for-privesc

Take over Active Directory accounts by writing attacker-controlled public keys to msDS-KeyCredentialLink (Shadow Credentials) with pyWhisker, Whisker, or Certipy, then authenticate via PKINIT to recover the target

achieving-cmmc-level-2-compliance

>-

acquiring-disk-image-with-dd-and-dcfldd

Create forensically sound bit-for-bit disk images with dd or dcfldd on a Linux forensic workstation, preserving evidence integrity through hash verification (MD5/SHA) during acquisition. Use when imaging a suspect drive, USB device, or memory card for investigation, preserving volatile disk evidence during incident response, or producing a verified copy for legal or law-enforcement proceedings before any destructive analysis.

analyzing-active-directory-acl-abuse

Detect dangerous ACL misconfigurations in Active Directory using ldap3

analyzing-android-malware-with-apktool

Perform static analysis of Android APK malware using apktool for resource decompilation, jadx for Java source recovery, and androguard for manifest inspection, dangerous permission-combination detection, and identification of obfuscated code, dynamic code loading, and reflection-based API calls. Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules.

analyzing-api-gateway-access-logs

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect

analyzing-apt-group-with-mitre-navigator

Query ATT&CK data with attackcti, mitreattack-python, and stix2, then build MITRE ATT&CK Navigator layers and multi-layer heatmap overlays mapping one or more APT groups

analyzing-azure-activity-logs-for-threats

Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query

analyzing-bootkit-and-rootkit-samples

Analyzes bootkit and advanced rootkit malware infecting the Master

analyzing-browser-forensics-with-hindsight

Parse Chromium-based browser databases with Hindsight to extract and correlate browsing history, downloads, cookies, cached content, autofill data, saved passwords, and extensions from Chrome, Edge, Brave, Opera, and Vivaldi into a unified timeline (XLSX, JSON, or SQLite output). Use during incident response, insider-threat investigations, or criminal cases when you need to reconstruct a user

analyzing-campaign-attribution-evidence

Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use when an incident investigation needs a defensible attribution confidence level.

analyzing-certificate-transparency-for-phishing

Monitor Certificate Transparency logs using crt.sh and Certstream to

analyzing-cloud-storage-access-patterns

Detect abnormal access in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics for after-hours bulk downloads, new-IP access, and API-call spikes (e.g. GetObject) via statistical baselines and time-series anomaly detection. Use when investigating suspected cloud data exfiltration or building related detection rules.

analyzing-cobalt-strike-beacon-configuration

Extract and analyze Cobalt Strike beacon configuration from PE files

analyzing-cobaltstrike-malleable-c2-profiles

Parse and analyze Cobalt Strike Malleable C2 profiles with dissect.cobaltstrike (profiles and beacon-payload configs) and pyMalleableC2 (AST parsing) to extract HTTP/DNS transforms, URIs, headers, sleep/jitter, and injection behavior, then generate network detection signatures. Use when reverse-engineering a captured malleable profile or building detections against Cobalt Strike Beacon traffic.

analyzing-command-and-control-communication

Analyzes malware C2 communication over HTTP, HTTPS, DNS, and custom

analyzing-cyber-kill-chain

Analyzes intrusion activity against the Lockheed Martin Cyber Kill Chain

analyzing-disk-image-with-autopsy

Perform comprehensive forensic analysis of raw (dd), E01, or AFF disk images with Autopsy and The Sleuth Kit, recovering deleted files, examining metadata and embedded artifacts, keyword searching, and building investigation timelines with visual reports. Use for structured analysis of a forensic disk image or when stakeholders need visual reports from evidence.

analyzing-dns-logs-for-exfiltration

Analyzes DNS query logs to detect data exfiltration via DNS tunneling,

相關技能