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Disk Forensics

Community
briiirussell
disk-forensics

Analyze disk images, file systems, and memory captures for digital evidence recovery in forensic investigations and CTF challenges. Use when the user mentions 'disk forensics,' 'forensic analysis,' 'disk image,' 'file carving,' 'deleted files,' 'evidence recovery,' 'timeline analysis,' 'memory forensics,' 'volatility,' 'autopsy,' 'sleuthkit,' 'plaso,' 'log2timeline,' 'artifact analysis,' 'chain of custody,' or needs to examine a forensic image.

Overview

Publisherbriiirussell
Repositorycybersecurity-skills
Skill namedisk-forensics
Stars
429
Forks
60
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by briiirussell on GitHub. Read the source before you install it.

Installation

Install the Disk Forensics AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/briiirussell/cybersecurity-skills/tree/main/skills/disk-forensics
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/briiirussell/cybersecurity-skills.git /tmp/cybersecurity-skills
mkdir -p .claude/skills
cp -r /tmp/cybersecurity-skills/skills/disk-forensics .claude/skills/disk-forensics
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Disk Forensics in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Disk Forensics on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Disk Forensics is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Disk Forensics — Digital Evidence Analysis

Analyze disk images and file systems to recover evidence, reconstruct timelines, and identify artifacts.

Cross-references: incident-triage for the upstream containment phase that captures the image this skill analyzes — that skill makes the bit-for-bit copy; this skill analyzes it. breach-patterns for translating the forensic findings into preemptive controls so the same root cause doesn't recur.

Authorization Check

Before analyzing any image, confirm:

  1. Lawful basis — the user has authorization for this analysis (internal investigation with documented scope, court-ordered work, signed IR engagement, your own system, CTF / lab environment)
  2. Chain of custody is preserved — the image and its hashes were captured in a way that survives evidentiary scrutiny, OR the scope is explicitly non-evidentiary (CTF, internal triage where chain-of-custody is not the goal)
  3. Privacy scope — the analysis stays within what was authorized; personal data outside the scope is not pulled, analyzed, or reported

If lawful basis is unclear, ask before proceeding. Never analyze an image you cannot confirm the user is authorized to possess.

Evidence Handling Principles

  • Always work on copies, never originals
  • Verify image integrity with hash comparison before analysis
  • Mount everything read-only
  • Document every command and finding
  • Preserve timestamps — never modify source evidence

Methodology

Step 1: Image Identification and Integrity

Identify the image format and verify integrity:

bash
file <image>                    # Identify format (E01, dd/raw, VMDK, VHD)
sha256sum <image>               # Compare to provided hash

For E01 images, use ewfinfo to extract metadata.

Step 2: Partition Layout

Examine the partition structure:

bash
fdisk -l <image>                # Partition table
mmls <image>                    # Sleuth Kit partition layout

Calculate mount offsets: sector_start × sector_size

Step 3: Mount and Explore

Mount read-only and survey the file system:

bash
mount -o ro,loop,offset=<bytes> <image> /mnt/evidence
ls -laR /mnt/evidence

For encrypted volumes, identify the encryption type and request the key/passphrase.

Step 4: File System Analysis (Sleuth Kit)

bash
fsstat -o <offset> <image>              # File system details
fls -r -o <offset> <image>             # Full file listing (deleted files marked with *)
icat -o <offset> <image> <inode>       # Extract specific file by inode

Step 5: Artifact Recovery

Deleted files: Use fls to find (marked with *), icat to extract by inode.

File carving: Run foremost or scalpel on unallocated space to recover files by header signatures.

Hidden data:

  • NTFS alternate data streams
  • HFS+ resource forks
  • Check image files for steganography: exiftool, binwalk, steghide

System artifacts:

  • Browser history: ~/.mozilla, ~/Library/Safari, AppData\Local\Google
  • System logs: /var/log/*, Windows Event Logs
  • Registry hives (Windows): SAM, SYSTEM, SOFTWARE, NTUSER.DAT
  • Recently accessed files, USB device history, prefetch files

Step 6: Metadata and Timestamps

bash
exiftool <file>                 # EXIF, XMP, IPTC metadata
stat <file>                     # MAC times (Modified, Accessed, Changed)

For NTFS: examine $MFT timestamps and $UsnJrnl for change journal entries.

Use mactime (Sleuth Kit) to generate a unified timeline from body files.

Step 7: Keyword Search

bash
strings <image> | grep -i <keyword>    # Raw string search across image

Use bulk_extractor for automated extraction of emails, URLs, credit card numbers, and other structured data.

Step 8: Timeline Construction

Collect all timestamps into a unified timeline. Cross-reference file events with log entries. Flag anomalies:

  • Timestamps before the OS install date
  • Future-dated files
  • Gaps in otherwise continuous log sequences
  • Timestamps inconsistent with timezone settings

Output Format

markdown
# Forensic Analysis Report
## Case: [identifier]
## Image: [filename] — SHA256: [hash]
## Date of Analysis: [date]

### Image Integrity
- Hash verified: [yes/no]
- Algorithm: [SHA256]

### Partition Layout
| # | Type | Start | Size | File System |
|---|------|-------|------|-------------|

### Key Findings
#### Finding 1: [Title]
- **Evidence:** [file path or artifact]
- **Content:** [description]
- **Timestamp:** [UTC]
- **Significance:** [why this matters]

### Recovered Files
| File | Source | Recovery Method | SHA256 | Significance |
|------|--------|-----------------|--------|-------------|

### Timeline
| Timestamp (UTC) | Event | Source | Notes |
|-----------------|-------|--------|-------|

### Conclusions
[Summary of findings and their implications]

Boundaries

  • Work only on provided images and files
  • Maintain read-only access at all times
  • Document chain of custody for real investigations
  • For CTF challenges, focus on finding flags and solving the challenge
  • Never modify evidence or suggest evidence tampering
  • Refuse requests involving unauthorized device access

References

  • NIST SP 800-86: Guide to Integrating Forensic Techniques
  • The Sleuth Kit documentation
  • SANS Digital Forensics cheat sheets

Frequently asked questions

What does the Disk Forensics AI skill do?

Analyze disk images, file systems, and memory captures for digital evidence recovery in forensic investigations and CTF challenges. Use when the user mentions 'disk forensics,' 'forensic analysis,' 'disk image,' 'file carving,' 'deleted files,' 'evidence recovery,' 'timeline analysis,' 'memory forensics,' 'volatility,' 'autopsy,' 'sleuthkit,' 'plaso,' 'log2timeline,' 'artifact analysis,' 'chain of custody,' or needs to examine a forensic image.

Why use Disk Forensics on TypingMind?

Because you install it once and use it with any model. Disk Forensics is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Disk Forensics in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/briiirussell/cybersecurity-skills/tree/main/skills/disk-forensics. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Disk Forensics?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Disk Forensics?

As many as you like. As long as a model supports skills, you can use Disk Forensics with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Disk Forensics AI skill free?

Yes. It is published on GitHub by briiirussell under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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