Analyze the NTFS Master File Table ($MFT) to recover metadata and content of deleted files by examining MFT record entries, $LogFile, $UsnJrnl, and MFT slack space using MFTECmd, analyzeMFT, and X-Ways Forensics.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionanalyzing-mft-for-deleted-file-recoveryExecute the skills CLI command in your project's root directory to begin installation:
Fetches analyzing-mft-for-deleted-file-recovery from mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate analyzing-mft-for-deleted-file-recovery. Access via /analyzing-mft-for-deleted-file-recovery in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
0
total installs
0
this week
8.6K
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
8.6K
stars
| name | analyzing-mft-for-deleted-file-recovery |
| description | Analyze the NTFS Master File Table ($MFT) to recover metadata and content of deleted files by examining MFT record entries, $LogFile, $UsnJrnl, and MFT slack space using MFTECmd, analyzeMFT, and X-Ways Forensics. |
| domain | cybersecurity |
| subdomain | digital-forensics |
| tags | - mft - ntfs - deleted-files - file-recovery - mftecmd - usn-journal - logfile - mft-slack-space - file-system-forensics - dfir |
| version | '1.0' |
| author | mahipal |
| license | Apache-2.0 |
| nist_csf | - RS.AN-01 - RS.AN-03 - DE.AE-02 - RS.MA-01 |
The NTFS Master File Table ($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.
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 |
| 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 |
# Extract $MFT from forensic image using KAPE or FTK Imager
# Parse the $MFT with MFTECmd
MFTECmd.exe -f "C:\Evidence\$MFT" --csv C:\Output --csvf mft_full.csv
# Filter for deleted files (InUse = FALSE) in Timeline Explorer
# Look for entries where InUse column is False
Identifying Deleted Files in CSV Output:
InUse = False indicates a deleted or reallocated recordParentPath shows original file location before deletionFileSize shows the original size (may still be recoverable)$STANDARD_INFORMATION and $FILE_NAME attributes persistThe USN Journal records all changes to files on an NTFS volume, including creation, deletion, rename, and data modification events.
# 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
The $LogFile stores NTFS transaction records that can reveal file operations even after the USN Journal has been cycled.
# 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)
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.
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
# 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
# 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
$ 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
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
analyzing-mft-for-deleted-file-recovery has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added analyzing-mft-for-deleted-file-recovery from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
analyzing-mft-for-deleted-file-recovery fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
analyzing-mft-for-deleted-file-recovery reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added analyzing-mft-for-deleted-file-recovery from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
analyzing-mft-for-deleted-file-recovery has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: analyzing-mft-for-deleted-file-recovery is focused, and the summary matches what you get after install.
I recommend analyzing-mft-for-deleted-file-recovery for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: analyzing-mft-for-deleted-file-recovery is the kind of skill you can hand to a new teammate without a long onboarding doc.
analyzing-mft-for-deleted-file-recovery is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
showing 1-10 of 30