analyzing-mft-for-deleted-file-recovery — скилл для Claude Code
Скилл для криминалистического анализа NTFS: разбирает $MFT, $LogFile, $UsnJrnl и slack space, чтобы восстановить метаданные и содержимое удалённых файлов.
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-mft-for-deleted-file-recovery -a claude-codeЧто делает analyzing-mft-for-deleted-file-recovery
Скилл описывает методику разбора Master File Table на NTFS-томах. Каждый файл представлен записью размером 1024 байта с атрибутами $STANDARD_INFORMATION, $FILE_NAME и $DATA. После удаления запись помечается как неактивная, но метаданные остаются на месте, пока её не перезапишет новый файл. Поэтому анализ MFT позволяет восстановить имена, пути, размеры и временные метки удалённых объектов.
Внутри четыре техники. Разбор записей через MFTECmd с фильтром по колонке InUse, анализ журнала USN по кодам причин удаления, разбор $LogFile через LogFileParser для поиска операций DeallocateFileRecordSegment и DeleteAttribute, плюс Python-скрипт для вычитки slack space между концом использованной части записи и границей выделенного блока. Скрипт ищет читаемые строки и остатки заголовков атрибутов в неиспользуемом хвосте записи.
Для работы нужен образ диска в E01, raw/dd, VMDK или VHDX, инструменты MFTECmd или analyzeMFT, а для монтажа образа — FTK Imager или Arsenal Image Mounter. CSV-результаты смотрят в Timeline Explorer или Excel. Python нужен от 3.8, если запускать собственные скрипты. Это не плагин с готовыми командами, а структурированная процедура, которую агент применяет по шагам.
Какие задачи решает
- восстановить метаданные удалённых файлов из записей $MFT
- вытащить из USN Journal события удаления и переименования
- найти в $LogFile операции DeallocateFileRecordSegment и DeleteAttribute
- прочитать остатки старых записей в MFT slack space
- обнаружить timestomping по расхождению временных меток $STANDARD_INFORMATION и $FILE_NAME
Примеры запросов агенту
- Разбери $MFT из образа C:\Evidence и покажи удалённые записи
- Найди в USN Journal события удаления файлов за последний период
- Проверь MFT slack space на остатки предыдущих записей
Как установить analyzing-mft-for-deleted-file-recovery
1Через Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-mft-for-deleted-file-recovery -a claude-code2Вручную: положить файлы
~/.claude/skills/analyzing-mft-for-deleted-file-recovery/SKILL.mdПапка скилла целиком; для одного проекта — .claude/skills/analyzing-mft-for-deleted-file-recovery/
1Через Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-mft-for-deleted-file-recovery -a codex2Вручную: положить файлы
.agents/skills/analyzing-mft-for-deleted-file-recovery/SKILL.mdДля всех проектов — ~/.agents/skills/
1Через Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-mft-for-deleted-file-recovery -a cursor2Вручную: положить файлы
.cursor/skills/analyzing-mft-for-deleted-file-recovery/SKILL.mdCursor читает и .agents/skills/, и .claude/skills/
1GitHub CLI
gh skill install mukul975/Anthropic-Cybersecurity-Skills analyzing-mft-for-deleted-file-recovery2Вручную: положить файлы
.github/skills/analyzing-mft-for-deleted-file-recovery/SKILL.md1Через Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-mft-for-deleted-file-recovery -a gemini-cli2Командой платформы
gemini skills install https://github.com/mukul975/Anthropic-Cybersecurity-Skills --path skills/analyzing-mft-for-deleted-file-recoveryВручную: положить файлы
.devin/skills/analyzing-mft-for-deleted-file-recovery/SKILL.mdСтарый путь .windsurf/skills/ тоже читается
Через Skills CLI (Vercel)
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-mft-for-deleted-file-recovery -a opencodeClaude.ai
Упакуйте папку в zip и загрузите в Settings → Capabilities → Skills
По шагам, с командами для каждой платформы: Как установить скилл в Claude Code: пять способов
Вопросы о analyzing-mft-for-deleted-file-recovery
Как установить analyzing-mft-for-deleted-file-recovery в Claude Code?
Выполни npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-mft-for-deleted-file-recovery -a claude-code. Скилл попадёт в ~/.claude/skills/analyzing-mft-for-deleted-file-recovery/SKILL.md.
Что делает analyzing-mft-for-deleted-file-recovery?
Разбирает NTFS Master File Table и сопутствующие артефакты: $LogFile, $UsnJrnl и MFT slack space. Восстанавливает метаданные и содержимое удалённых файлов, строит таймлайны файловой системы, выявляет timestomping.
Какие инструменты нужны для работы скилла?
MFTECmd от Eric Zimmerman или Python-библиотека analyzeMFT, плюс LogFileParser для $LogFile. Для монтажа образа — FTK Imager или Arsenal Image Mounter. Образ диска должен быть в E01, raw/dd, VMDK или VHDX.
Исходный текст
SKILL.md · Apache-2.0
---
name: analyzing-mft-for-deleted-file-recovery
description: Analyze the NTFS Master File Table ($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