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analyzing-slack-space-and-file-system-artifacts

Examine NTFS slack space, MFT entries, the USN Change Journal, and Alternate Data Streams (ADS) to recover hidden or residual data, reconstruct deleted-file…

Skill by mukul975

IndexedApache-2.0★ 34,941
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Examine NTFS slack space, MFT entries, the USN Change Journal, and Alternate Data Streams (ADS) to recover hidden or residual data, reconstruct deleted-file metadata, and reconstruct available file-system change activity from USN records. Use during deep forensic analysis of an NTFS image when standard file recovery is insufficient, such as hunting for data hidden in ADS.

Use cases: data, marketing, productivity

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What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.

Tools
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Secrets
None asked for
Install scripts
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Runs as
Python package

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/analyzing-slack-space-and-file-system-artifacts

What's inside

Skill name
analyzing-slack-space-and-file-system-artifacts
Description
Examine NTFS slack space, MFT entries, the USN Change Journal, and Alternate Data Streams (ADS) to recover hidden or residual data, reconstruct deleted-file metadata, and reconstruct available file-system change activity from USN records. Use during deep forensic analysis of an NTFS image when standard file recovery is insufficient, such as hunting for data hidden in ADS.
License
Apache-2.0
Instructions
373 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Files (4)

  • LICENSE
  • SKILL.md
  • api-reference.md · references/
  • agent.py · scripts/

SKILL.md (first lines)

# Analyzing Slack Space and File System Artifacts

## When to Use
- When searching for hidden or residual data in file system slack space
- For analyzing NTFS Master File Table (MFT) entries for deleted file metadata
- When reconstructing file operations from the USN Change Journal
- For detecting Alternate Data Streams (ADS) used to hide data or malware
- During deep forensic analysis requiring examination beyond standard file recovery

## Prerequisites
- Forensic disk image with NTFS file system
- The Sleuth Kit (TSK) tools: istat, icat, fls, blkls, blkstat
- MFTECmd (Eric Zimmerman) for MFT parsing
- MFTExplorer for interactive MFT analysis
- Understanding of NTFS structures (MFT, $UsnJrnl, $LogFile, ADS)
- Python with analyzeMFT or mft library for automated parsing

## Workflow

### Step 1: Identify and Extract NTFS File System Artifacts

```bash
# Determine partition layout
mmls /cases/case-2024-001/images/evidence.dd

# Extract key NTFS system files
# $MFT - Master File Table
icat -o 2048 /cases/case-2024-001/images/evidence.dd 0 > /cases/case-2024-001/ntfs/MFT

# $UsnJrnl:$J - USN Change Journal
icat -o 2048 /cases/case-2024-001/images/evidence.dd 62-128 > /cases/case-2024-001/ntfs/UsnJrnl_J

# $LogFile - Transaction log
icat -o 2048 /cases/case-2024-001/images/evidence.dd 2 > /cases/case-2024-001/ntfs/LogFile

# Extract all slack space from the volume
blkls -s -o 2048 /cases/case-2024-001/images/evidence.dd > /cases/case-2024-001/ntfs/slack_space.raw

# Get file system information
fsstat -o 2048 /cases/case-2024-001/images/evidence.dd | tee /cases/case-2024-001/ntfs/fs_info.txt
```

### Step 2: Analyze the Master File Table (MFT)

```bash
# Parse MFT with MFTECmd (Eric Zimmerman)
MFTECmd.exe -f "C:\cases\ntfs\MFT" --csv "C:\cases\analysis\" --csvf mft_analysis.csv

# Parse with analyzeMFT (Python)
pip install analyzeMFT

analyzeMFT.py -f /cases/case-2024-001/ntfs/MFT \
   -o /cases/case-2024-001/analysis/mft_analysis.csv \
   -c

# Custom MFT analysis with Python
python3 << 'PYEOF'
from mft import PyMft
import csv

mft = PyMft(open('/cases/case-2024-001/ntfs/MFT', 'rb').read())

deleted_files = []
suspicious_files = []

for entry in mft.entries():
    if entry is None:
        continue

    filename = entry.get_filename()
    if filename is None:
        continue

    is_deleted = not entry.is_active()
    is_directory = entry.is_directory()
    created = entry.get_created_timestamp()
    modified = entry.get_modified_timestamp()
    mft_modified = entry.get_mft_modified_timestamp()
    size = entry.get_file_size()

    # Flag deleted files for recovery
    if is_deleted and not is_directory and size > 0:
        deleted_files.append({
            'filename': filename,
            'size': size,
            'created': str(created),
            'modified': str(modified),
            'entry_number': entry.entry_number
        })

    # Detect timestomping (MFT modified time != $SI modified time)
    si_modified = entry.get_si_modified_timestamp()
    fn_modified = entry.get_fn_modified_timestamp()
    if si_modified and fn_modified:
        if abs((si_modified - fn_modified).total_seconds()) > 86400:  # >1 day difference
            suspicious_files.append({
                'filename': filename,
                'si_modified': str(si_modified),
                'fn_modified': str(fn_modified),
                'delta': str(si_modified - fn_modified)
            })

print(f"=== DELETED FILES (recoverable metadata) ===")
print(f"Total: {len(deleted_files)}")
for f in deleted_files[:20]:
    print(f"  [{f['modified']}] {f['filename']} ({f['size']} bytes)")

print(f"\n=== POTENTIAL TIMESTOMPING ===")
print(f"Total suspicious: {len(suspicious_files)}")
for f in suspicious_files[:10]:
    print(f"  {f['filename']}: $SI={f['si_modified']}, $FN={f['fn_modified']} (delta: {f['delta']})")
PYEOF
```

### Step 3: Analyze Slack Space for Hidden Data

```bash
# Search slack space for strings
strings -a /cases/case-2024-001/ntfs/slack_space.raw > /cases/case-2024-001/analysis/slack_strings.txt

From mukul975/Anthropic-Cybersecurity-Skills, Apache-2.0.

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Open issues
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Last commit (this folder)
Aug 2, 2026 (2 months ago)
Last release
Jun 22, 2026 (4 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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analyzing-slack-space-and-file-system-artifacts skill. Agent Mart. https://agentmart.dev/skills/mukul975-analyzing-slack-space-and-file-system-artifacts (last updated 2026-10-24)