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analyzing-disk-image-with-autopsy

Perform comprehensive forensic analysis of disk images using Autopsy to recover files, examine artifacts, and build investigation timelines.

Skill by xtofuub

IndexedApache-2.0
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Perform comprehensive forensic analysis of disk images using Autopsy to recover files, examine artifacts, and build investigation timelines.

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
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Install scripts
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Runs as
Python package

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/analyzing-disk-image-with-autopsy

What's inside

Skill name
analyzing-disk-image-with-autopsy
Description
Perform comprehensive forensic analysis of disk images using Autopsy to recover files, examine artifacts, and build investigation timelines.
License
Apache-2.0
Instructions
243 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts
  • Instructions call the network

Agent Skills spec issues

  • body: contains an absolute path from the author's machine

Files (4)

  • LICENSE
  • SKILL.md
  • api-reference.md · references/
  • agent.py · scripts/

SKILL.md (first lines)

# Analyzing Disk Image with Autopsy

## When to Use
- When you have a forensic disk image and need structured analysis of its contents
- During investigations requiring file recovery, keyword searching, and timeline analysis
- When non-technical stakeholders need visual reports from forensic evidence
- For examining file system metadata, deleted files, and embedded artifacts
- When building a comprehensive case from multiple disk images

## Prerequisites
- Autopsy 4.x installed (Windows) or Autopsy 4.x with The Sleuth Kit (Linux)
- Forensic disk image in raw (dd), E01 (EnCase), or AFF format
- Minimum 8GB RAM (16GB recommended for large images)
- Java Runtime Environment (JRE) 8+ for Autopsy
- Sufficient disk space for the Autopsy case database (2-3x image size)
- Hash databases (NSRL, known-bad hashes) for file identification

## Workflow

### Step 1: Install Autopsy and Configure Environment

```bash
# On Linux, install Sleuth Kit and Autopsy
sudo apt-get install autopsy sleuthkit

# Download Autopsy 4.x (GUI version) from official source
wget https://github.com/sleuthkit/autopsy/releases/download/autopsy-4.21.0/autopsy-4.21.0.zip
unzip autopsy-4.21.0.zip -d /opt/autopsy

# On Windows, run the MSI installer from sleuthkit.org
# Launch Autopsy
/opt/autopsy/bin/autopsy --nosplash

# For Sleuth Kit command-line analysis alongside Autopsy
sudo apt-get install sleuthkit
```

### Step 2: Create a New Case and Add the Disk Image

```
1. Launch Autopsy > "New Case"
2. Enter Case Name: "CASE-2024-001-Workstation"
3. Set Base Directory: /cases/case-2024-001/autopsy/
4. Enter Case Number, Examiner Name
5. Click "Add Data Source"
6. Select "Disk Image or VM File"
7. Browse to: /cases/case-2024-001/images/evidence.dd
8. Select Time Zone of the original system
9. Configure Ingest Modules (see Step 3)
```

```bash
# Alternatively, use Sleuth Kit CLI to verify the image first
img_stat /cases/case-2024-001/images/evidence.dd

# List partitions in the image
mmls /cases/case-2024-001/images/evidence.dd

# Output example:
# DOS Partition Table
# Offset Sector: 0
# Units are in 512-byte sectors
#      Slot    Start        End          Length       Description
#      00:  -----   0000000000   0000002047   0000002048   Primary Table (#0)
#      01:  00:00   0000002048   0001026047   0001024000   NTFS (0x07)
#      02:  00:01   0001026048   0976771071   0975745024   NTFS (0x07)

# List files in a partition (offset 2048 sectors)
fls -o 2048 /cases/case-2024-001/images/evidence.dd
```

### Step 3: Configure and Run Ingest Modules

```
Enable the following Autopsy Ingest Modules:
- Recent Activity: Extracts browser history, downloads, cookies, bookmarks
- Hash Lookup: Compares files against NSRL and known-bad hash sets
- File Type Identification: Identifies files by signature, not extension
- Keyword Search: Indexes content for full-text searching
- Email Parser: Extracts emails from PST, MBOX, EML files
- Extension Mismatch Detector: Finds files with wrong extensions
- Exif Parser: Extracts metadata from images (GPS, camera, timestamps)
- Encryption Detection: Identifies encrypted files and containers
- Interesting Files Identifier: Flags files matching custom rule sets
- Embedded File Extractor: Extracts files from ZIP, Office docs, PDFs
- Picture Analyzer: Categorizes images using PhotoDNA or hash matching
- Data Source Integrity: Verifies image hash during ingest
```

```bash
# Configure NSRL hash set for known-good filtering
# Download NSRL from https://www.nist.gov/itl/ssd/software-quality-group/national-software-reference-library-nsrl
wget https://s3.amazonaws.com/rds.nsrl.nist.gov/RDS/current/rds_modernm.zip
unzip rds_modernm.zip -d /opt/autopsy/hashsets/

# Import into Autopsy:
# Tools > Options > Hash Sets > Import > Select NSRLFile.txt
# Mark as "Known" (to filter out known-good files)
```

### Step 4: Analyze File System and Recover Deleted Files

```bash
# In Autopsy GUI: Navigate tree structure
# - Data Sources > evidence.dd > vol2 (NTFS)
# - Examine directory tree, note deleted files (marked with X)

# Using Sleuth Kit CLI for targeted recovery
# List deleted files
fls -rd -o 2048 /cases/case-2024-001/images/evidence.dd

# Recover a specific deleted file by inode
icat -o 2048 /cases/case-2024-001/images/evidence.dd 14523 > /cases/case-2024-001/recovered/deleted_document.docx

# Extract all files from a directory
tsk_recover -o 2048 -d /Users/suspect/Documents \
   /cases/case-2024-001/images/evidence.dd \
   /cases/case-2024-001/recovered/documents/

From xtofuub/openrecon-ios, Apache-2.0.

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Last commit (this folder)
May 15, 2026 (5 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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analyzing-disk-image-with-autopsy skill. Agent Mart. https://agentmart.dev/skills/xtofuub-analyzing-disk-image-with-autopsy (last updated 2026-10-24)