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.
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.
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 Autopsysudo 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 Autopsysudo 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
fls -o 2048 /cases/case-2024-001/images/evidence.dd
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
Concept
Description
Ingest Modules
Automated analysis plugins that process data sources upon import
MFT (Master File Table)
NTFS metadata structure recording all file entries and attributes
File carving
Recovering files from unallocated space using file signatures
Hash filtering
Using NSRL or custom hash sets to exclude known-good or flag known-bad files
Timeline analysis
Chronological reconstruction of file system and user activity events
Deleted file recovery
Restoring files whose directory entries are removed but data remains
Keyword indexing
Full-text search index built from all file content including slack space
Artifact extraction
Automated parsing of browser, email, registry, and OS-specific artifacts
Tools & Systems
Tool
Purpose
Autopsy
Open-source GUI forensic platform for disk image analysis
The Sleuth Kit (TSK)
Command-line forensic toolkit underlying Autopsy
fls
List files and directories in a disk image including deleted entries
icat
Extract file content by inode number from a disk image
mactime
Generate timeline from TSK bodyfile format
mmls
Display partition layout of a disk image
NSRL
NIST hash database for identifying known software files
sigfind
Search 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.
