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Analyzing Disk Image With Autopsy

  • 353 installs
  • 27.3k repo stars
  • Updated August 2, 2026
  • mukul975/anthropic-cybersecurity-skills

Walk an agent through digital-forensics steps to analyze disk images with Autopsy for incident response, malware triage, or evidence review.

About

Analyzing Disk Image With Autopsy is a cybersecurity agent skill from the Anthropic-oriented collection that steers coding agents through forensic analysis of disk images using Autopsy—the standard open-source forensics suite for carving artifacts, timelines, and user activity from acquired drives. Solo builders rarely run full SOC teams, but when a laptop backup, server snapshot, or E01 image lands on your desk after a suspected breach, you need repeatable examination steps instead of clicking blindly through wizards. This skill packages procedural knowledge for loading images, navigating Autopsy modules, and interpreting common artifact types while staying in a defensible audit mindset. Use it in Ship when security review demands offline disk validation, or when you must document findings before wider launch or ops handoff. Pair with proper chain-of-custody practices and legal counsel when evidence may be used formally; the skill teaches tooling workflow, not jurisdiction-specific rules.

  • Disk-image forensic workflow centered on the Autopsy platform
  • Structured approach for solo builders handling incident or compromise investigations
  • Fits Anthropic cybersecurity skills collection for agent-guided forensics
  • Apache License 2.0 distribution terms in upstream skill package
  • Agent procedural guidance for evidence-oriented disk analysis rather than live pentesting

Analyzing Disk Image With Autopsy by the numbers

  • 353 all-time installs (skills.sh)
  • +23 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #578 of 2,203 Security skills by installs in the Skillselion catalog
  • Security screen: MEDIUM risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-disk-image-with-autopsy

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Listed on Skillselion
Installs353
repo stars27.3k
Security audit2 / 3 scanners passed
Last updatedAugust 2, 2026
Repositorymukul975/anthropic-cybersecurity-skills

What it does

Walk an agent through digital-forensics steps to analyze disk images with Autopsy for incident response, malware triage, or evidence review.

Files

SKILL.mdMarkdownGitHub ↗

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

ConceptDescription
Ingest ModulesAutomated analysis plugins that process data sources upon import
MFT (Master File Table)NTFS metadata structure recording all file entries and attributes
File carvingRecovering files from unallocated space using file signatures
Hash filteringUsing NSRL or custom hash sets to exclude known-good or flag known-bad files
Timeline analysisChronological reconstruction of file system and user activity events
Deleted file recoveryRestoring files whose directory entries are removed but data remains
Keyword indexingFull-text search index built from all file content including slack space
Artifact extractionAutomated parsing of browser, email, registry, and OS-specific artifacts

Tools & Systems

ToolPurpose
AutopsyOpen-source GUI forensic platform for disk image analysis
The Sleuth Kit (TSK)Command-line forensic toolkit underlying Autopsy
flsList files and directories in a disk image including deleted entries
icatExtract file content by inode number from a disk image
mactimeGenerate timeline from TSK bodyfile format
mmlsDisplay partition layout of a disk image
NSRLNIST hash database for identifying known software files
sigfindSearch for file signatures at the sector level

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

Related skills

FAQ

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