Detecting Hidden Data with Marx NTFS Alternate Data Streams Viewer

Marx NTFS ADS Viewer: Features, Tips, and Best PracticesMarx NTFS ADS Viewer is a specialized utility designed to discover, inspect, and manage Alternate Data Streams (ADS) on NTFS-formatted volumes. ADS are a lesser-known feature of the NTFS filesystem that allow multiple streams of data to be associated with a single file name. While ADS can be useful for legitimate purposes (storing metadata, compatibility layers, or application-specific information), they are also used by attackers and malware to hide files and payloads. This article covers Marx NTFS ADS Viewer’s features, practical tips for using it effectively, and best practices for handling ADS in both incident response and regular system maintenance.

What Are NTFS Alternate Data Streams (ADS)?

Alternate Data Streams are additional named streams attached to an existing file or directory in NTFS. Each stream behaves like a separate file, but it is not visible through standard directory listings and can be used to hide information. ADS syntax uses the colon character — for example: filename.txt:secretstream.

Key points:

• ADS can store arbitrary data separate from the primary file content.
• ADS are not shown by typical file managers and can be missed by casual users.
• ADS were introduced for compatibility with the Macintosh HFS filesystem and to support extended metadata.

Core Features of Marx NTFS ADS Viewer

Marx NTFS ADS Viewer focuses on accessibility and thoroughness when working with ADS. Its main capabilities include:

• Stream enumeration: scans files and directories to list attached ADS, showing stream names and sizes.
• Content preview: displays the content of discovered streams in hex and text modes for quick inspection.
• Extraction and export: saves ADS contents to separate files for further analysis.
• Bulk scanning: performs recursive scans across drives or folders, producing consolidated reports.
• Filtering and search: filter results by stream name, size, time stamps, or content patterns (e.g., ASCII, UTF-16, known file headers).
• Integration with forensic workflows: exports in common formats (CSV, JSON) and supports command-line automation.
• Safe read-only mode: ensures ADS are not modified during inspection unless explicitly allowed.
• Hashing and identification: computes hashes (MD5/SHA1/SHA256) of stream contents to support triage and malware detection.

Interface and Usability

Marx typically offers both GUI and CLI interfaces:

• GUI: presents a tree view of scanned folders with attached streams displayed under each file. Hex/text preview panes and context menus allow extraction, copying, or quick hashing.
• CLI: supports scripted scans and outputs machine-readable logs—useful for automated monitoring or integrating with SIEM/EDR tools.

Practical Tips for Using Marx NTFS ADS Viewer

1. Start with a read-only scan

   • Run the initial scan in safe read-only mode to avoid altering timestamps or contents.

2. Use targeted filters

   • Filter by stream size (e.g., >1 KB) and known magic bytes (MZ, PK) to surface likely executable or archive payloads.

3. Export suspicious streams

   • Export streams to a quarantine folder and compute hashes for further static and dynamic analysis.

4. Combine with other indicators

   • Cross-reference ADS findings with process lists, scheduled tasks, registry autoruns, and network artifacts.

5. Automate regular scans

   • Schedule periodic CLI scans for critical servers and store JSON/CSV reports for trend analysis.

6. Preserve forensic evidence

   • When investigating incidents, image disks and operate on copies. Use Marx’s export and hashing to document chain-of-custody-friendly artifacts.

Best Practices for Handling ADS in Security Operations

• Awareness and policy

  • Train admins and SOC analysts to include ADS in triage playbooks. Update incident response policies to mention ADS as a potential hiding place for artifacts.

• Monitoring and alerting

  • Integrate Marx CLI output into monitoring pipelines. Alert on creation of ADS with executable signatures or unexpected sizes on sensitive hosts.

• Regular housekeeping

  • Periodically scan backup sets and file shares to detect legacy ADS that may persist unnoticed.

• Least privilege and integrity checks

  • Limit who can write to file shares and verify integrity of critical files by hashing main streams and known good configurations.

• Malware analysis workflow

  • Quarantine and analyze ADS payloads in isolated sandboxes. Use static scanners first, then dynamic analysis for behavior.

Common Use Cases

• Incident response: locating hidden payloads placed in ADS by attackers.
• Forensics: recovering evidence stored in alternate streams.
• IT hygiene: identifying leftover ADS in legacy systems or migrated shares.
• Threat hunting: searching for patterns of ADS use across endpoints.

Limitations and Caveats

• ADS are NTFS-specific; Marx’s ADS features won’t find similar hidden data on FAT, exFAT, HFS+, APFS, or other filesystems.
• Some cloud-sync clients and backup tools strip or ignore ADS; absence in those stores doesn’t mean absence on local disks.
• Large-scale scans can be I/O intensive; plan scans for off-peak hours on production systems.

Example Workflow (CLI)

1. Run a recursive, read-only scan on C: and output JSON:

   
   marx-ads --scan C: --recursive --read-only --output report.json 

2. Filter report for streams with MZ header and export:

   
   marx-ads --report report.json --filter "header:MZ" --export suspicious_exports 

3. Hash exported files:

   
   sha256sum suspicious_exports* > exported_hashes.txt 

Conclusion

Marx NTFS ADS Viewer is a useful tool for defenders and forensic practitioners who need to reveal and manage hidden data on NTFS volumes. By combining careful scanning, automated monitoring, and solid incident-handling practices, teams can reduce the risk posed by malicious or unintended use of Alternate Data Streams.

If you’d like, I can translate this article into Russian, expand any section (e.g., give more CLI examples), or create a shorter blog post version.