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Get Started Free →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.
.claude/skills/performing-cloud-storage-forensic-acquisition/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-15 | ✗→✓ | ▲ Improved | — | — |
| case-03 | ✗→✓ | ▲ Improved | — | — |
| case-19 | ✗→✓ | ▲ Improved | — | — |
| case-02 | ✗→✓ | ▲ Improved | — | — |
| case-10 | ✗→✓ | ▲ Improved | — | — |
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.
pythonfrom google.oauth2.credentials import Credentials from googleapiclient.discovery import build from googleapiclient.http import MediaIoBaseDownload import io import os import json from datetime import datetime class GoogleDriveForensicAcquisition: """Forensically acquire files and metadata from Google Drive via API.""" def __init__(self, credentials_path: str, output_dir: str): self.creds = Credentials.from_authorized_user_file(credentials_path) self.service = build("drive", "v3", credentials=self.creds) self.output_dir = output_dir os.makedirs(output_dir, exist_ok=True) self.acquisition_log = [] def list_all_files(self, include_trashed: bool = True) -> list: """List all files including trashed items.""" files = [] page_token = None query = "" if include_trashed else "trashed = false" while True: results = self.service.files().list( q=query, pageSize=1000, fields="nextPageToken, files(id, name, mimeType, size, " "createdTime, modifiedTime, trashed, trashedTime, " "owners, sharingUser, permissions, md5Checksum, " "parents, webViewLink, driveId)", pageToken=page_token ).execute() files.extend(results.get("files", [])) page_token = results.get("nextPageToken") if not page_token: break return files def download_file(self, file_id: str, file_name: str, mime_type: str) -> str: """Download a file from Google Drive preserving forensic integrity.""" output_path = os.path.join(self.output_dir, file_name) if mime_type.startswith("application/vnd.google-apps"): export_formats = { "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", } export_mime = export_formats.get(mime_type, "application/pdf") request = self.service.files().export_media(fileId=file_id, mimeType=export_mime) else: request = self.service.files().get_media(fileId=file_id) with io.FileIO(output_path, "wb") as fh: downloader = MediaIoBaseDownload(fh, request) done = False while not done: _, done = downloader.next_chunk() self.acquisition_log.append({ "timestamp": datetime.utcnow().isoformat(), "file_id": file_id, "file_name": file_name, "output_path": output_path, "action": "downloaded" }) return output_path def get_activity_log(self, file_id: str) -> list: """Retrieve activity/revision history for a specific file.""" revisions = self.service.revisions().list( fileId=file_id, fields="revisions(id, modifiedTime, lastModifyingUser, size, md5Checksum)" ).execute() return revisions.get("revisions", []) def export_acquisition_report(self) -> str: """Export acquisition log for chain of custody documentation.""" report_path = os.path.join(self.output_dir, "acquisition_log.json") with open(report_path, "w") as f: json.dump({ "acquisition_start": self.acquisition_log[0]["timestamp"] if self.acquisition_log else None, "acquisition_end": datetime.utcnow().isoformat(), "total_files": len(self.acquisition_log), "entries": self.acquisition_log }, f, indent=2) return report_path
pythonimport 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", [])
powershell# 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
pythonimport 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() # Query for all tracked files including cloud-only items 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
| 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\ |
text$ 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
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-20 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-15 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-18 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-09 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-03 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-14 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-11 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-04 | pass→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-21 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-22 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-12 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-06 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-01 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-19 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-02 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-16 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-08 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-13 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-07 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-05 | fail→fail | — | — | — | — | — | — | — | — | — | — | — | — |
case-10 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
case-17 | fail→pass | — | — | — | — | — | — | — | — | — | — | — | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +27 percentage points is the difference between those two pass rates over the 22 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
The per-case answers from this run were removed by the retention sweep, so the case table below shows the verdicts without the text either arm produced. The counts above were recorded at the time and are unaffected. Answers are now kept for 180 days.
Other measured skills in the registry, with their headline benchmark lift.