القائمة
Perform comprehensive forensic analysis of disk images using Autopsy to recover files, examine artifacts, and build investigation timelines.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
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| 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. |
| 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-01","RS.AN-03","DE.AE-02","RS.MA-01"] |
| mitre_attack | ["T1005","T1074.001","T1070.004","T1083"] |
# 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
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
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)
# 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
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
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
| 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 |
| 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 |
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.
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