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performing-cloud-storage-forensic-acquisition Perform forensic acquisition and analysis of cloud storage services including Google Drive, OneDrive, Dropbox, and Box by collecting both API-based remote data and local sync client artifacts from endpoint devices. Use when performing forensic acquisition and analysis of cloud storage services including.
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name performing-cloud-storage-forensic-acquisition description Perform forensic acquisition and analysis of cloud storage services including Google Drive, OneDrive, Dropbox, and Box by collecting both API-based remote data and local sync client artifacts from endpoint devices. Use when performing forensic acquisition and analysis of cloud storage services including. domain cybersecurity subdomain digital-forensics tags ["cloud-forensics","google-drive","onedrive","dropbox","box","cloud-acquisition","api-forensics","sync-client","endpoint-artifacts","magnet-axiom"] version 1.0 author oyi77 license Apache-2.0 nist_ai_rmf ["MEASURE-2.7","MAP-5.1","MANAGE-2.4"] atlas_techniques ["AML.T0070","AML.T0066","AML.T0082"] nist_csf ["RS.AN-01","RS.AN-03","DE.AE-02","RS.MA-01"]
Performing Cloud Storage Forensic Acquisition
Overview
Cloud storage forensic acquisition involves collecting digital evidence from services like Google Drive, OneDrive, Dropbox, and Box through both API-based remote acquisition and local endpoint artifact analysis. Modern investigations must address the challenge that cloud-synced files may exist in multiple states: locally synchronized, cloud-only (on-demand), cached, and deleted. Endpoint devices that have synchronized with cloud storage contain a wealth of metadata about locally synced files, files present only in the cloud, and even deleted items recoverable from cache folders. API-based acquisition using service-specific APIs provides direct access to remote data with valid credentials and proper legal authorization.
When to Use
Trigger phrases:
"performing cloud storage forensic acquisition"
"Perform forensic acquisition and analysis of cloud storage services including Go"
When conducting security assessments that involve performing cloud storage forensic acquisition
When following incident response procedures for related security events
When performing scheduled security testing or auditing activities
When validating security controls through hands-on testing
Prerequisites
Legal authorization (warrant, consent, or corporate policy) for cloud data access
Valid user credentials or administrative access tokens
Magnet AXIOM Cloud, Cellebrite Cloud Analyzer, or equivalent tool
KAPE with cloud storage target files
Python 3.8+ with google-api-python-client, msal, dropbox SDK
Network connectivity for API-based acquisition
Acquisition Methods
This section covers acquisition methods for performing cloud storage forensic acquisition.
Ensure all prerequisites are met before proceeding
Follow the documented workflow steps in sequence
Record results and any anomalies encountered during this phase
Method 1: API-Based Remote Acquisition
Google Drive API Acquisition
from google.oauth2.credentials import Credentials
from googleapiclient.discovery import build
from googleapiclient.http import MediaIoBaseDownload
import io
import
import
from
import
class
GoogleDriveForensicAcquisition
"""Forensically acquire files and metadata from Google Drive via API."""
def
__init__
self, credentials_path: str , output_dir: str
self
self
"drive"
"v3"
self
self
True
self
def
list_all_files
self, include_trashed: bool = True
list
"""List all files including trashed items."""
None
""
if
else
"trashed = false"
while
True
self
list
1000
"nextPageToken, files(id, name, mimeType, size, "
"createdTime, modifiedTime, trashed, trashedTime, "
"owners, sharingUser, permissions, md5Checksum, "
"parents, webViewLink, driveId)"
"files"
"nextPageToken"
if
not
break
return
def
download_file
self, file_id: str , file_name: str , mime_type: str
str
"""Download a file from Google Drive preserving forensic integrity."""
self
if
"application/vnd.google-apps"
"application/vnd.google-apps.document"
"application/pdf"
"application/vnd.google-apps.spreadsheet"
"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
"application/vnd.google-apps.presentation"
"application/pdf"
"application/pdf"
self
else
self
with
"wb"
as
False
while
not
self
"timestamp"
"file_id"
"file_name"
"output_path"
"action"
"downloaded"
return
def
get_activity_log
self, file_id: str
list
"""Retrieve activity/revision history for a specific file."""
self
list
"revisions(id, modifiedTime, lastModifyingUser, size, md5Checksum)"
return
"revisions"
def
export_acquisition_report
self
str
"""Export acquisition log for chain of custody documentation."""
self
"acquisition_log.json"
with
open
"w"
as
"acquisition_start"
self
0
"timestamp"
if
self
else
None
"acquisition_end"
"total_files"
len
self
"entries"
self
2
return
OneDrive / Microsoft 365 API Acquisition import msal
import requests
import os
import json
from datetime import datetime
class OneDriveForensicAcquisition :
"""Forensically acquire files and metadata from OneDrive via Microsoft Graph API."""
def __init__ (self, client_id: str , tenant_id: str , client_secret: str , output_dir: str ):
self .output_dir = output_dir
os.makedirs(output_dir, exist_ok=True )
authority = f"https://login.microsoftonline.com/{tenant_id} "
self .app = msal.ConfidentialClientApplication(
client_id, authority=authority, client_credential=client_secret
)
token_result = self .app.acquire_token_for_client(
scopes=["https://graph.microsoft.com/.default" ]
)
self .access_token = token_result.get("access_token" )
self .headers = {"Authorization" : f"Bearer {self.access_token} " }
self .base_url = "https://graph.microsoft.com/v1.0"
def list_user_files (self, user_id: str ) -> list :
"""List all files in user's OneDrive."""
url = f"{self.base_url} /users/{user_id} /drive/root/children"
files = []
while url:
response = requests.get(url, headers=self .headers)
data = response.json()
files.extend(data.get("value" , []))
url = data.get("@odata.nextLink" )
return files
def download_file (self, user_id: str , item_id: str , filename: str ) -> str :
"""Download a file from OneDrive."""
url = f"{self.base_url} /users/{user_id} /drive/items/{item_id} /content"
response = requests.get(url, headers=self .headers, stream=True )
output_path = os.path.join(self .output_dir, filename)
with open (output_path, "wb" ) as f:
for chunk in response.iter_content(chunk_size=8192 ):
f.write(chunk)
return output_path
def get_deleted_items (self, user_id: str ) -> list :
"""Retrieve items from OneDrive recycle bin."""
url = f"{self.base_url} /users/{user_id} /drive/special/recyclebin/children"
response = requests.get(url, headers=self .headers)
return response.json().get("value" , [])
Method 2: Local Endpoint Artifact Collection
KAPE Targets for Cloud Storage # Collect all cloud storage artifacts using KAPE
kape.exe --tsource C: --tdest C:\Output\CloudArtifacts --target GoogleDrive,OneDrive,Dropbox,Box
# OneDrive artifacts
# %USERPROFILE%\AppData\Local\Microsoft\OneDrive\logs\
# %USERPROFILE%\AppData\Local\Microsoft\OneDrive\settings\
# %USERPROFILE%\OneDrive\
# Google Drive artifacts
# %USERPROFILE%\AppData\Local\Google\DriveFS\
# Contains metadata SQLite databases and cached files
# Dropbox artifacts
# %USERPROFILE%\AppData\Local\Dropbox\
# %USERPROFILE%\Dropbox\.dropbox.cache\
# Contains filecache.dbx (encrypted SQLite), host.dbx, config.dbx
OneDrive Local Database Analysis import sqlite3
import os
def analyze_onedrive_sync_engine (db_path: str ) -> list :
"""Analyze OneDrive SyncEngineDatabase for file metadata."""
conn = sqlite3.connect(db_path)
cursor = conn.cursor()
cursor.execute("""
SELECT fileName, fileSize, lastChange,
resourceID, parentResourceID, eTag
FROM od_ClientFile_Records
ORDER BY lastChange DESC
""" )
files = []
for row in cursor.fetchall():
files.append({
"filename" : row[0 ],
"size" : row[1 ],
"last_change" : row[2 ],
"resource_id" : row[3 ],
"parent_id" : row[4 ],
"etag" : row[5 ]
})
conn.close()
return files
Cloud Storage Artifacts Summary Service Local Database Cache Location Log Files OneDrive SyncEngineDatabase.db %LOCALAPPDATA%\Microsoft\OneDrive\cache\ %LOCALAPPDATA%\Microsoft\OneDrive\logs\ Google Drive metadata_sqlite_db %LOCALAPPDATA%\Google\DriveFS{account}\content_cache\ %LOCALAPPDATA%\Google\DriveFS\Logs\ Dropbox filecache.dbx (encrypted) %APPDATA%\Dropbox.dropbox.cache\ %APPDATA%\Dropbox\logs\ Box sync_db %LOCALAPPDATA%\Box\Box\cache\ %LOCALAPPDATA%\Box\Box\logs\
When NOT to Use
You don't have explicit written authorization to test
Task is about defense/detection, not offense (use detection skills)
You need to implement security controls (use implementing-* skills)
Task requires compliance auditing (use auditing-* skills)
You're investigating an incident (use incident response skills)
Target is out of scope for your engagement
Task is about vulnerability scanning only (use scanning tools)
Red Flags
Performing actions without explicit written authorization from the asset owner
Testing against production systems without a defined scope and rules of engagement
Failing to use write-blockers when acquiring forensic evidence
Not verifying hash integrity before and after imaging
Modifying original evidence during analysis
Verification
All steps executed successfully against a test environment before production use
Output documented with screenshots or logs demonstrating expected behavior
Hash values computed and verified match between source and image
Chain of custody log complete with timestamps and examiner names
Analysis tools and versions documented for reproducibility
References
Example Output $ python3 cloud_forensic_acquire.py --provider google-drive --auth /tokens/gdrive_token.json \
--user jsmith@corporate.com --output /acquisition/gdrive
Cloud Storage Forensic Acquisition Tool v3.2
==============================================
Provider: Google Drive
Account: jsmith@corporate.com
Start Time: 2024-01-19 08:00:15 UTC
Auth Method: Admin SDK (domain-wide delegation)
[+] Enumerating files...
Total files: 2,345
Total folders: 178
Shared with me: 456
Trashed items: 89 (included in acquisition)
Total size: 14.7 GB
[+] Acquiring file contents...
Downloaded: 2,345 / 2,345 [████████████████████████████████] 100%
Errors: 0
Elapsed: 18m 32s
[+] Acquiring metadata...
File metadata: 2,345 entries
Revision history: 8,912 revisions across 1,234 files
Sharing permissions: 3,456 permission entries
Activity log: 12,345 events
[+] Acquiring trashed items...
Recovered: 89 / 89 items (234 MB)
--- Acquisition Log ---
Timestamp (UTC) | Action | File | Size | SHA-256
2024-01-19 08:00:45 | Downloaded | /My Drive/Finance/Q4_Report.xlsm | 245 KB | 7a3b8c9d...
2024-01-19 08:00:46 | Downloaded | /My Drive/Finance/Budget_2024.xlsx | 1.2 MB | 8b4c9d0e...
...
2024-01-19 08:02:12 | Trash-Recovered | /Trash/employee_list_full.csv | 4.5 MB | 9c5d0e1f...
2024-01-19 08:02:13 | Trash-Recovered | /Trash/network_diagram_v3.vsdx | 2.1 MB | 0d6e1f2a...
2024-01-19 08:02:14 | Trash-Recovered | /Trash/credentials_backup.kdbx | 128 KB | 1e7f2a3b...
--- Sharing Analysis ---
Files Shared Externally:
/My Drive/Finance/Q4_Report.xlsm → j.smith.personal8842@protonmail.com (2024-01-16 03:10 UTC)
/My Drive/HR/employee_list_full.csv → j.smith.personal8842@protonmail.com (2024-01-16 03:12 UTC)
/My Drive/IT/network_diagram_v3.vsdx → anonymous (link sharing, 2024-01-16 03:15 UTC)
--- Revision History (Suspicious) ---
File: /My Drive/Finance/Q4_Report.xlsm
Rev 1: 2024-01-10 09:00:00 UTC (245 KB) - Original
Rev 2: 2024-01-15 14:35:00 UTC (248 KB) - Modified (macro added)
Rev 3: 2024-01-16 03:05:00 UTC (245 KB) - Reverted (macro removed - anti-forensics)
Acquisition Summary:
Files acquired: 2,345 (14.7 GB)
Trashed items: 89 (234 MB)
Revisions: 8,912
Chain of custody hash (full archive):
SHA-256: a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4e5f6a1b2
Output directory: /acquisition/gdrive/
Acquisition log: /acquisition/gdrive/acquisition_log.csv
Completion Time: 2024-01-19 08:18:47 UTC
Process
Analyze the task requirements
Apply domain expertise
Verify output quality
Anti-Rationalization Table Rationalization Reality "We are too small to be targeted" Automated attacks target everyone. Size does not matter. "Security slows us down" A breach slows you down 100x more. Build security in from the start. "We will fix it after launch" Vulnerabilities in production are exploited within hours. Fix before deploy.
