analyzing-mft-for-deleted-file-recovery — Claude Code skill for $MFT
Forensic skill for NTFS analysis: parses $MFT, $LogFile, $UsnJrnl and slack space to recover metadata and content of deleted files.
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-mft-for-deleted-file-recovery -a claude-codeWhat analyzing-mft-for-deleted-file-recovery does
The skill covers Master File Table analysis on NTFS volumes. Every file gets at least one 1024-byte record holding $STANDARD_INFORMATION, $FILE_NAME and $DATA attributes. Deleting a file clears the InUse flag but leaves metadata intact until a new file reallocates the entry. So MFT analysis recovers names, paths, sizes and timestamps of deleted objects.
Four techniques are described. Record parsing with MFTECmd, filtering the CSV by the InUse column. USN Journal analysis by reason codes for deletion and rename events. $LogFile parsing via LogFileParser to find DeallocateFileRecordSegment and DeleteAttribute operations. A Python script pulls readable strings and attribute header remnants out of MFT slack space.
You need a forensic image in E01, raw/dd, VMDK or VHDX, MFTECmd or analyzeMFT, and FTK Imager or Arsenal Image Mounter for mounting. CSV output goes into Timeline Explorer or Excel. Python 3.8+ if you run the custom slack-space script. The skill is a procedure, not a packaged command set, so the agent walks through it step by step.
What it helps with
- recover deleted file metadata from $MFT records
- extract deletion and rename events from the USN Journal
- find DeallocateFileRecordSegment operations in $LogFile
- read remnants of previous records from MFT slack space
- spot timestomping via mismatched $STANDARD_INFORMATION and $FILE_NAME timestamps
Example prompts for the agent
- Parse the $MFT from C:\Evidence and list deleted records
- Look for file deletion events in the USN Journal
- Check MFT slack space for leftovers of previous records
How to install analyzing-mft-for-deleted-file-recovery
1Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-mft-for-deleted-file-recovery -a claude-code2Manually: put the files in place
~/.claude/skills/analyzing-mft-for-deleted-file-recovery/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/analyzing-mft-for-deleted-file-recovery/
1Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-mft-for-deleted-file-recovery -a codex2Manually: put the files in place
.agents/skills/analyzing-mft-for-deleted-file-recovery/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-mft-for-deleted-file-recovery -a cursor2Manually: put the files in place
.cursor/skills/analyzing-mft-for-deleted-file-recovery/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-mft-for-deleted-file-recovery2Manually: put the files in place
.github/skills/analyzing-mft-for-deleted-file-recovery/SKILL.md1Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-mft-for-deleted-file-recovery -a gemini-cli2Platform CLI
gemini skills install https://github.com/mukul975/Anthropic-Cybersecurity-Skills --path skills/analyzing-mft-for-deleted-file-recoveryManually: put the files in place
.devin/skills/analyzing-mft-for-deleted-file-recovery/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-mft-for-deleted-file-recovery -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about analyzing-mft-for-deleted-file-recovery
How do I install analyzing-mft-for-deleted-file-recovery in Claude Code?
Run npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-mft-for-deleted-file-recovery -a claude-code. The skill lands in ~/.claude/skills/analyzing-mft-for-deleted-file-recovery/SKILL.md.
What does analyzing-mft-for-deleted-file-recovery do?
It parses the NTFS Master File Table and related artifacts: $LogFile, $UsnJrnl and MFT slack space. It recovers deleted file metadata, rebuilds filesystem timelines and flags timestomping.
What tools does the skill require?
MFTECmd by Eric Zimmerman or the analyzeMFT Python library, plus LogFileParser for $LogFile. Mounting needs FTK Imager or Arsenal Image Mounter. The disk image must be E01, raw/dd, VMDK or VHDX.
Source text
SKILL.md · Apache-2.0
---
name: analyzing-mft-for-deleted-file-recovery
description: Analyze the NTFS Master File Table ($MFT) with MFTECmd, analyzeMFT,
and X-Ways Forensics to recover metadata and content of deleted files by examining
MFT record entries, $LogFile, $UsnJrnl, and MFT slack space. Use when recovering
evidence of deleted files, reconstructing NTFS file-system timelines, or detecting
anti-forensic timestomping during a Windows forensic examination.
domain: cybersecurity
subdomain: digital-forensics
tags:
- mft
- ntfs
- deleted-files
- file-recovery
- mftecmd
- usn-journal
- logfile
- mft-slack-space
- file-system-forensics
- dfir
version: '1.0'
author: mahipal
license: Apache-2.0
nist_csf:
- RS.AN-03
- DE.AE-02
- RS.MA-01
mitre_attack:
- T1070.004
- T1070.006
- T1005
---
# Analyzing MFT for Deleted File Recovery
## Overview
The NTFS Master File Table ($MFT) is the central metadata repository for every file and directory on an NTFS volume. Each file is represented by at least one 1024-byte MFT record containing attributes such as $STANDARD_INFORMATION (timestamps, permissions), $FILE_NAME (name, parent directory, timestamps), and $DATA (file content or cluster run pointers). When a file is deleted, its MFT record is marked as inactive (InUse flag cleared) but the metadata remains until the entry is reallocated by a new file. This persistence makes MFT analysis a primary technique for recovering deleted file evidence, reconstructing file system timelines, and detecting anti-forensic activity such as timestomping.
## When to Use
- When investigating security incidents that require analyzing mft for deleted file recovery
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques
## Prerequisites
- Forensic disk image (E01, raw/dd, VMDK, or VHDX format)
- MFTECmd (Eric Zimmerman) or analyzeMFT (Python-based)
- FTK Imager, Arsenal Image Mounter, or similar for image mounting
- Timeline Explorer or Excel for CSV analysis
- Python 3.8+ for custom analysis scripts
- Understanding of NTFS file system internals
## MFT Structure and Record Layout
### MFT Record Header
Each MFT record begins with the signature "FILE" (0x46494C45) and contains:
| Offset | Size | Field |
|--------|------|-------|
| 0x00 | 4 bytes | Signature ("FILE") |
| 0x04 | 2 bytes | Offset to update sequence |
| 0x06 | 2 bytes | Size of update sequence |
| 0x08 | 8 bytes | $LogFile sequence number |
| 0x10 | 2 bytes | Sequence number |
| 0x12 | 2 bytes | Hard link count |
| 0x14 | 2 bytes | Offset to first attribute |
| 0x16 | 2 bytes | Flags (0x01 = InUse, 0x02 = Directory) |
| 0x18 | 4 bytes | Used size of MFT record |
| 0x1C | 4 bytes | Allocated size of MFT record |
| 0x20 | 8 bytes | Base file record reference |
| 0x28 | 2 bytes | Next attribute ID |
### Key MFT Attributes
| Type ID | Name | Description |
|---------|------|-------------|
| 0x10 | $STANDARD_INFORMATION | Timestamps, flags, owner ID, security ID |
| 0x30 | $FILE_NAME | Filename, parent MFT reference, timestamps |
| 0x40 | $OBJECT_ID | Unique GUID for the file |
| 0x50 | $SECURITY_DESCRIPTOR | ACL permissions |
| 0x60 | $VOLUME_NAME | Volume label (volume metadata files only) |
| 0x80 | $DATA | File content (resident if <700 bytes) or cluster run list |
| 0x90 | $INDEX_ROOT | B-tree index root for directories |
| 0xA0 | $INDEX_ALLOCATION | B-tree index entries for large directories |
| 0xB0 | $BITMAP | Allocation bitmap for index or MFT |
## Deleted File Recovery Techniques
### Technique 1: MFT Record Analysis with MFTECmd
```powershell
# Extract $MFT from forensic image using KAPE or FTK Imager
# Parse the $MFT with MFTECmd
MFTECmd.exe -f "C:\Evidence\$MFT" --csv C:\Output --csvf mft_full.csv
# Filter for deleted files (InUse = FALSE) in Timeline Explorer
# Look for entries where InUse column is False
```
**Identifying Deleted Files in CSV Output:**
- `InUse` = False indicates a deleted or reallocated record
- `ParentPath` shows original file location before deletion
- `FileSize` shows the original size (may still be recoverable)
- Timestamps in `$STANDARD_INFORMATION` and `$FILE_NAME` attributes persist
### Technique 2: USN Journal ($UsnJrnl:$J) Analysis
The USN Journal records all changes to files on an NTFS volume, including creation, deletion, rename, and data modification events.
```powershell
# Parse USN Journal with MFTECmd
MFTECmd.exe -f "C:\Evidence\$J" --csv C:\Output --csvf usn_journal.csv
# Key USN reason codes for deletion evidence:
# USN_REASON_FILE_DELETE = 0x00000200
# USN_REASON_CLOSE = 0x80000000
# USN_REASON_RENAME_OLD_NAME = 0x00001000
# USN_REASON_RENAME_NEW_NAME = 0x00002000
```
### Technique 3: $LogFile Transaction Analysis
The $LogFile stores NTFS transaction records that can reveal file operations even after the USN Journal has been cycled.
```powershell
# Parse $LogFile with LogFileParser
LogFileParser.exe -l "C:\Evidence\$LogFile" -o C:\Output
# Look for REDO and UNDO operations indicating file deletion:
# - DeallocateFileRecordSegment
# - DeleteAttribute
# - UpdateResidentValue (clearing InUse flag)
```
### Technique 4: MFT Slack Space Analysis
MFT slack space exists between the end of the used portion of an MFT record and the end of the allocated 1024 bytes. This area may contain remnants of previous file records.
```python
import struct
def parse_mft_slack(mft_path: str, output_path: str):
"""Extract and analyze MFT slack space for deleted file remnants."""
with open(mft_path, "rb") as f:
record_size = 1024
record_num = 0
slack_findings = []
while True:
record = f.read(record_size)
if len(record) < record_size:
break
# Verify FILE signature
if record[:4] != b"FILE":
record_num += 1
continue
# Get used size from offset 0x18
used_size = struct.unpack("<I", record[0x18:0x1C])[0]
if used_size < record_size:
slack = record[used_size:]
# Check if slack contains readable strings or attribute headers
if any(c > 0x20 and c < 0x7F for c in slack[:50]):
slack_findings.append({
"record": record_num,
"used_size": used_size,
"slack_size": record_size - used_size,
"slack_preview": slack[:100].hex()
})
record_num += 1
return slack_findings
```
## Correlation with Supporting Artifacts
### Cross-Reference MFT with $Recycle.Bin
```powershell
# Parse Recycle Bin with RBCmd
RBCmd.exe -d "C:\Evidence\$Recycle.Bin" --csv C:\Output --csvf recycle_bin.csv
# Correlate: $I files contain original path and deletion timestamp
# Match MFT entry numbers from $R files back to original MFT records
```
### Cross-Reference MFT with Volume Shadow Copies
```powershell
# List volume shadow copies
vssadmin list shadows
# Mount shadow copies and extract $MFT from each
# Compare MFT records across shadow copies to track file changes over time
```
## Forensic Value
- **Deleted file metadata recovery**: Original filename, path, size, and timestamps
- **Timeline reconstruction**: File creation, modification, access, and deletion events
- **Timestomping detection**: Comparing $SI vs $FN timestamps
- **Data carving guidance**: MFT cluster runs point to file content on disk
- **Anti-forensic detection**: Identifying wiped or manipulated MFT records
## References
- NTFS MFT Advanced Forensic Analysis: https://www.deaddisk.com/posts/ntfs-mft-advanced-forensic-analysis-guide/
- MFT Slack Space Forensic Value: https://www.sygnia.co/blog/the-forensic-value-of-mft-slack-space/
- MFTECmd Documentation: https://ericzimmerman.github.io/
- SANS FOR500: Windows Forensic Analysis
## Example Output
```text
$ MFTECmd.exe -f "C:\Evidence\$MFT" --csv /analysis/mft_output
MFTECmd v1.2.2 - MFT Parser
==============================
Input: C:\Evidence\$MFT (Size: 384 MB)
Total MFT Entries: 395,264
Parsing MFT entries... Done (12.4 seconds)
--- Deleted File Recovery Summary ---
Total Entries: 395,264
Active Files: 245,832
Deleted Files: 149,432
Recoverable: 87,234 (resident data or clusters not reallocated)
Partially Recoverable: 31,456 (some clusters overwritten)
Unrecoverable: 30,742 (all clusters reallocated)
--- Recently Deleted Files (Incident Window: 2024-01-15 to 2024-01-18) ---
MFT Entry | Filename | Path | Size | Deleted (UTC) | Recoverable
----------|-----------------------------------|------------------------------------|-----------|-----------------------|------------
148923 | exfil_tool.exe | C:\ProgramData\Updates\ | 1,258,496 | 2024-01-17 02:45:12 | YES
148924 | exfil_tool.log | C:\ProgramData\Updates\ | 45,312 | 2024-01-17 02:45:14 | YES
149001 | passwords.txt | C:\Users\jsmith\Desktop\ | 2,048 | 2024-01-17 02:50:33 | YES
149150 | scan_results.csv | C:\Users\jsmith\AppData\Local\Temp | 892,416 | 2024-01-17 03:00:01 | PARTIAL
149200 | mimikatz.exe | C:\Windows\Temp\ | 1,250,816 | 2024-01-18 01:15:22 | YES
149201 | sekurlsa.log | C:\Windows\Temp\ | 32,768 | 2024-01-18 01:15:25 | YES
149302 | .bash_history | C:\Users\jsmith\ | 4,096 | 2024-01-18 03:00:00 | NO
149400 | ClearEventLogs.ps1 | C:\Windows\Temp\ | 1,536 | 2024-01-18 03:01:12 | YES
--- $STANDARD_INFORMATION vs $FILE_NAME Timestamp Analysis (Timestomping Detection) ---
MFT Entry | Filename | $SI Created | $FN Created | Delta | Verdict
----------|---------------------|----------------------|----------------------|-----------|----------
148923 | exfil_tool.exe | 2023-06-15 10:00:00 | 2024-01-15 14:34:02 | -214 days | TIMESTOMPED
149200 | mimikatz.exe | 2022-01-01 00:00:00 | 2024-01-16 02:30:15 | -745 days | TIMESTOMPED
Recovered files exported to: /analysis/mft_output/recovered/
Full CSV report: /analysis/mft_output/mft_analysis.csv (395,264 rows)
Timeline CSV: /analysis/mft_output/mft_timeline.csv
```
© mahipal · Apache-2.0 · mukul975/Anthropic-Cybersecurity-Skills