Full Report
Forensic artifacts, which can be found during forensic examination of a Windows endpoint.
Analysis Summary
# Research: Forensic Analysis of Nextcloud Artifacts on Windows Endpoints
## Metadata
- **Authors:** Oleg Skulkin
- **Institution:** Group-IB
- **Publication:** Group-IB Blog / Digital Forensics Research
- **Date:** (Implicitly recent, citing tools from 2019 onwards)
## Abstract
This research identifies and analyzes the forensic artifacts generated by the Nextcloud desktop synchronization client on Windows operating systems. As cloud storage becomes a primary vector for data exfiltration and evidence storage, understanding local synchronization databases and logs is critical for investigators. The study highlights how Nextcloud stores metadata, file activity, and synchronization history in accessible SQLite databases and log files.
## Research Objective
The research aims to answer:
1. What local artifacts does the Nextcloud Windows client create?
2. How can an investigator reconstruct file activity (creation, modification, deletion) using these artifacts?
3. How can these artifacts be extracted and parsed efficiently during an incident response or digital forensic engagement?
## Methodology
### Approach
The researcher performed a behavioral analysis of the Nextcloud Windows client, monitoring file system changes and identifying the specific database schemas and log structures used by the application to track synchronization.
### Dataset/Environment
- **Operating System:** Microsoft Windows.
- **Application:** Nextcloud Desktop Client.
### Tools & Technologies
- **SQLite3:** For querying and inspecting `.db` files.
- **KAPE (Kroll Artifact Parser and Extractor):** Used to automate the collection and parsing of identified artifacts.
- **Unix Epoch Converters:** To interpret timestamps stored in the databases.
## Key Findings
### Primary Results
1. **Metadata Database:** Nextcloud stores critical file information in a synchronization database (typically found in the root of the sync folder). The `metadata` table within this database is the primary source of evidence.
2. **Tracking Mechanism:** The client tracks files using MFT (Master File Table) entry numbers (inodes), file paths, sizes, and timestamps.
3. **Synchronization Logs:** The `Nextcloud_sync.log` file provides a chronological record of synchronization events, including file deletions and transfers.
4. **Configuration Artifacts:** The `sync-exclude.lst` file reveals which file types or directories were intentionally excluded from cloud backup, which may point to hidden or sensitive data.
### Supporting Evidence
- **Database Schema:** The `metadata` table includes columns: `path` (file path), `inode` (MFT reference), `modtime` (Unix Epoch timestamp), and `contentChecksum` (SHA1 hash).
- **Log Data:** Log entries include `mtime` (modification time), `etag` (unique change identifier), and `size` (bytes).
### Novel Contributions
- Provided a custom **KAPE Target and Module** specifically for Nextcloud, allowing forensicators to automate the extraction of these artifacts across multiple endpoints.
- Established a direct link between Nextcloud's `inode` column and the NTFS MFT Entry Number, facilitating cross-referencing with filesystem forensics.
## Technical Details
The research provides a specific SQL query to extract actionable intelligence from the Nextcloud sync database:
sql
SELECT path as "File Path",
inode as "MFT Entry Number",
datetime(modtime,'unixepoch') as "Modified (UTC)",
filesize as "Size (bytes)",
contentChecksum as "SHA1"
FROM metadata
This query bridges the gap between application-level synchronization data and low-level filesystem metadata.
## Practical Implications
### For Security Practitioners
- Nextcloud artifacts can be used to prove data exfiltration by showing when specific sensitive files were synced to an external cloud instance.
- Even if files are deleted from the disk, the `Nextcloud_sync.log` may retain a history of their existence.
### For Defenders
- Monitor for the creation and modification of `.db` files in user directories as an indicator of unauthorized cloud storage usage.
- Use the provided KAPE modules to include Nextcloud in standard triage collections.
### For Researchers
- The `etag` value, while not a standard hash according to Nextcloud, warrants further study to see if it can be reverse-engineered for file identification.
## Limitations
- The research focuses specifically on the Windows client; artifacts on macOS or Linux may differ in pathing and structure.
- The `etag` is noted as "not a hash" by Nextcloud, meaning it cannot reliably be used for multi-source file integrity verification like a MD5 or SHA256.
## Comparison to Prior Work
While cloud forensics often focuses on browser history or API logs, this work builds on "Local Artifact" research by treating cloud sync clients similarly to traditional backup software, focusing on the local SQLite databases rather than the cloud provider's server-side logs.
## Real-world Applications
- **Insider Threat Investigations:** Determining if an employee synced proprietary data to a personal Nextcloud server.
- **Malware Analysis:** Identifying if ransomware or a stealer used Nextcloud for C2 or exfiltration.
- **Implementation:** Investigators can drop the provided `.tkape` and `.mkape` files into their KAPE instance for immediate deployment.
## Future Work
- Analysis of Nextcloud’s "Virtual Files" feature and how it impacts local metadata availability.
- Investigation into encrypted synchronization folders and the availability of local keys.
## References
- Group-IB Digital Forensics: `https://www.group-ib.com/services/digital-forensics/`
- KAPE Tool: `https://www.kroll.com/en/services/cyber-risk/incident-response-litigation-support/kroll-artifact-parser-extractor-kape`