What it does. Perform comprehensive forensic analysis of raw (dd), E01, or AFF disk images with Autopsy and The Sleuth Kit, recovering deleted files, examining metadata and embedded artifacts, keyword searching, and building investigation timelines with visual reports. Use for structured analysis of a forensic disk image or when stakeholders need visual reports from evidence. Part of mukul975/Anthropic-Cybersecurity-Skills (817 security skills) (mukul975/Anthropic-Cybersecurity-Skills).

Install

• npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-disk-image-with-autopsy, or copy the skill folder into ~/.claude/skills/analyzing-disk-image-with-autopsy/.
• Raw file: curl -sL https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/HEAD/skills/analyzing-disk-image-with-autopsy/SKILL.md

SKILL.md (verbatim)

name: analyzing-disk-image-with-autopsy
description: Perform comprehensive forensic analysis of raw (dd), E01, or AFF disk images with Autopsy and The Sleuth Kit, recovering deleted files, examining metadata and embedded artifacts, keyword searching, and building investigation timelines with visual reports. Use for structured analysis of a forensic disk image or when stakeholders need visual reports from evidence.
domain: cybersecurity
subdomain: digital-forensics
tags:
- forensics
- autopsy
- disk-analysis
- sleuth-kit
- file-recovery
- artifact-analysis
version: '1.0'
author: mahipal
license: Apache-2.0
nist_csf:
- RS.AN-03
- DE.AE-02
- RS.MA-01
mitre_attack:
- T1005
- T1074.001
- T1070.004
- T1083

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

# 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)

# 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

# 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

# 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/

# Get detailed file metadata
istat -o 2048 /cases/case-2024-001/images/evidence.dd 14523
# Shows: creation, modification, access, MFT change timestamps, size, data runs

Step 5: Perform Keyword Searches and Tag Evidence

In Autopsy:
1. Keyword Search panel > "Ad Hoc Keyword Search"
2. Search terms: credit card patterns, SSN regex, email addresses
3. Example regex for credit cards: \b(?:4[0-9]{12}(?:[0-9]{3})?|5[1-5][0-9]{14})\b
4. Example regex for SSN: \b\d{3}-\d{2}-\d{4}\b
5. Review results > Right-click items > "Add Tag"
6. Create tags: "Evidence-Critical", "Evidence-Supporting", "Requires-Review"
7. Add comments to tagged items documenting relevance

# Using Sleuth Kit for CLI keyword search
srch_strings -a -o 2048 /cases/case-2024-001/images/evidence.dd | \
   grep -iE '(password|secret|confidential)' > /cases/case-2024-001/keyword_hits.txt

# Search for specific file signatures
sigfind -o 2048 /cases/case-2024-001/images/evidence.dd 25504446
# 25504446 = %PDF header signature

Step 6: Build Timeline and Generate Reports

In Autopsy:
1. Timeline viewer: Tools > Timeline
2. Select date range of interest (incident window)
3. Filter by event type: File Created, Modified, Accessed, Web Activity
4. Zoom into suspicious time periods
5. Export timeline events as CSV for external analysis

Generate Report:
1. Generate Report > HTML Report
2. Select tagged items and data sources to include
3. Configure report sections: file listings, keyword hits, timeline
4. Export to /cases/case-2024-001/reports/

# Using Sleuth Kit mactime for CLI timeline
fls -r -m "/" -o 2048 /cases/case-2024-001/images/evidence.dd > /cases/case-2024-001/bodyfile.txt

# Generate timeline from bodyfile
mactime -b /cases/case-2024-001/bodyfile.txt -d > /cases/case-2024-001/timeline.csv

# Filter timeline to specific date range
mactime -b /cases/case-2024-001/bodyfile.txt \
   -d 2024-01-15..2024-01-20 > /cases/case-2024-001/incident_timeline.csv

Key Concepts

Tools & Systems

Common Scenarios

Scenario 1: Employee Data Theft Investigation Import the employee workstation image, run all ingest modules, search for company-confidential file names and keywords, examine USB connection artifacts in Recent Activity, check for cloud storage client artifacts, review deleted files for evidence of data staging, generate HTML report for legal team.

Scenario 2: Malware Infection Forensics Add the compromised system image, enable Extension Mismatch and Encryption Detection modules, examine the prefetch directory for execution evidence, search for known malware hashes, build timeline around the infection window, extract suspicious executables for further analysis in a sandbox.

Scenario 3: Child Exploitation Material (CSAM) Investigation Import image with PhotoDNA and Project VIC hash sets enabled, run Picture Analyzer module, hash all image files against known-bad databases, tag and categorize matches by severity, generate law enforcement report with chain of custody documentation.

Scenario 4: Intellectual Property Dispute Import multiple employee disk images as separate data sources in one case, perform keyword searches for proprietary terms and project names, compare file hashes between sources, build timeline showing file access and transfer patterns, export evidence for legal review.

Output Format

Autopsy Case Analysis Summary:
  Case:           CASE-2024-001-Workstation
  Image:          evidence.dd (500GB NTFS)
  Partitions:     2 (System Reserved + Primary)
  Total Files:    245,832
  Deleted Files:  12,456 (recoverable: 8,234)

  Ingest Results:
    Hash Matches (Known Bad):  3 files
    Extension Mismatches:      17 files
    Keyword Hits:              234 across 45 files
    Encrypted Files:           5 containers detected
    EXIF Data Extracted:       1,245 images with metadata

  Tagged Evidence:
    Critical:     12 items
    Supporting:   34 items
    Review:       67 items

  Timeline Events:  1,234,567 entries (filtered to incident window: 892)
  Report:          /cases/case-2024-001/reports/autopsy_report.html

Other files in this skill

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

references/api-reference.md (verbatim)

API Reference: Autopsy and The Sleuth Kit (TSK)

mmls - Partition Layout

Syntax

mmls <image_file>
mmls -t dos <image_file>    # Force DOS partition table
mmls -t gpt <image_file>    # Force GPT partition table

Output Format

DOS Partition Table
Offset Sector: 0
     Slot    Start        End          Length       Description
     00:  00:00   0000002048   0001026047   0001024000   NTFS (0x07)

fls - File Listing

Syntax

fls -o <offset> <image>              # List root directory
fls -r -o <offset> <image>           # Recursive listing
fls -rd -o <offset> <image>          # Deleted files only, recursive
fls -m "/" -r -o <offset> <image>    # Bodyfile format for mactime

Flags

icat - File Extraction by Inode

Syntax

icat -o <offset> <image> <inode> > recovered_file
icat -r -o <offset> <image> <inode> > file   # Recover slack space

istat - File Metadata

Syntax

istat -o <offset> <image> <inode>

Output Includes

• MFT entry number and sequence
• File creation, modification, access, MFT change timestamps
• File size and data run locations
• Attribute list (NTFS: $STANDARD_INFORMATION, $FILE_NAME, $DATA)

mactime - Timeline Generation

Syntax

mactime -b <bodyfile> -d > timeline.csv
mactime -b <bodyfile> -d 2024-01-15..2024-01-20 > filtered.csv
mactime -b <bodyfile> -z UTC -d > timeline_utc.csv

Output Columns

Date,Size,Type,Mode,UID,GID,Meta,File Name

img_stat - Image Information

Syntax

img_stat <image_file>

sigfind - File Signature Search

Syntax

sigfind -o <offset> <image> <hex_signature>
sigfind -o 2048 evidence.dd 25504446    # Find %PDF headers
sigfind -o 2048 evidence.dd 504B0304    # Find ZIP/DOCX headers

Common Signatures

srch_strings - Keyword Search

Syntax

srch_strings -a -o <offset> <image> | grep -i "keyword"
srch_strings -t d <image>    # Print offset in decimal

Autopsy GUI Ingest Modules

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