analyzing-mft-for-deleted-file-recovery

analyzing-mft-for-deleted-file-recovery is a skill for Claude Code, Codex from Youngmaidainon/Agent-Level-Up. It costs 100 tokens per session (2,840 once invoked), scanned A, a copy of analyzing-mft-for-deleted-file-recovery, MIT.

A Windows file-system forensics guide for examining the NTFS Master File Table, the record that stores information about files and folders. It uses that record and related logs to investigate deleted files and activity.

In plain words
What is it for?
It helps recover evidence from deleted files, build timelines of activity on NTFS disks, and investigate attempts to hide or alter file history.
Why use it?
Deleting a file usually removes its normal listing before all its metadata is overwritten. Examining the remaining records can reveal file names, timestamps, locations, and signs of changed timestamps.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps recover evidence from deleted files, build timelines of activity on NTFS disks, and investigate attempts to hide or alter file history.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/youngmaidainon/agent-level-up/analyzing-mft-for-deleted-file-recovery
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Youngmaidainon/Agent-Level-Up --skill analyzing-mft-for-deleted-file-recovery
Clone the repo
git clone --depth 1 https://github.com/Youngmaidainon/Agent-Level-Up

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for analyzing-mft-for-deleted-file-recovery

README.md
[![agentmods](https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/analyzing-mft-for-deleted-file-recovery/github.svg)](https://agentmods.dev/skills/youngmaidainon/agent-level-up/analyzing-mft-for-deleted-file-recovery)
Your own site
<a href="https://agentmods.dev/skills/youngmaidainon/agent-level-up/analyzing-mft-for-deleted-file-recovery"><img src="https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/analyzing-mft-for-deleted-file-recovery/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for analyzing-mft-for-deleted-file-recovery

Your own site · 80×15
<a href="https://agentmods.dev/skills/youngmaidainon/agent-level-up/analyzing-mft-for-deleted-file-recovery"><img src="https://agentmods.dev/badge/skills/youngmaidainon/agent-level-up/analyzing-mft-for-deleted-file-recovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 100 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,840 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00100 $0.02840
Opus 5 $0.00050 $0.01420
Sonnet 5 $0.00020 $0.00568
Haiku 4.5 $0.00010 $0.00284

Measured 11d ago against content hash 37d49a201727, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

analyzing-mft-for-deleted-file-recovery scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/agent.py, scripts/process.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to analyzing-mft-for-deleted-file-recovery — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

cyber-security/ctf/analyzing-mft-for-deleted-file-recovery/SKILL.md · 262 lines

How it starts

The opening of the file, as written. The whole thing — 262 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

Read the full file on GitHub · 262 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 262 lines · 100 tokens per session scan A 37d49a201727

Subscribe to this mod's changes

analyzing-mft-for-deleted-file-recovery is a skill published in the GitHub repository Youngmaidainon/Agent-Level-Up (3 stars, last pushed 17d ago), licensed MIT. It adds 100 tokens to every session and 2,840 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to analyzing-mft-for-deleted-file-recovery, differing in 0 lines, and is treated as a copy.

Related

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analyzing-mft-for-deleted-file-recovery

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…

mukul975/Anthropic-Cybersecurity-Skills · 100 tokens

analyzing-mft-for-deleted-file-recovery

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.

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analyzing-mft-for-deleted-file-recovery

En metod för digital kriminalteknik som analyserar NTFS-filsystemets huvudregister, MFT, för att hitta information om raderade filer.

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analyzing-mft-for-deleted-file-recovery

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.

26zl/cybersec-toolkit · 70 tokens

analyzing-mft-for-deleted-file-recovery

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.

plurigrid/asi · 70 tokens

analyzing-mft-for-deleted-file-recovery

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.

autohandai/community-skills · 70 tokens