performing-file-carving-with-foremost
Recovers files from disk images and unallocated space using Foremost's header-footer signature carving, extracting evidence independent of the file system's state. Use during digital forensics investigations to carve deleted or fragmented files, such as documents, images, and archives, from raw disk images or unallocated space.
- License 许可
- Apache-2.0
- 最近更新
- 2026-08-31
- Stars
- ★ 3.6w
- Forks
- 4.4k
01 前言 Front Matter
- name
- performing-file-carving-with-foremost
- tags
- [ "forensics", "file-carving", "foremost", "data-recovery", "evidence-recovery", "unallocated-space" ]
- author
- mahipal
- domain
- cybersecurity
- license
- Apache-2.0
- version
- 1.0
- nist_csf
- [ "RS.AN-03", "DE.AE-02", "RS.MA-01" ]
- subdomain
- digital-forensics
- description
- Recovers files from disk images and unallocated space using Foremost's header-footer signature carving, extracting evidence independent of the file system's state. Use during digital forensics investigations to carve deleted or fragmented files, such as documents, images, and archives, from raw disk images or unallocated space.
- mitre_attack
- [ "T1005", "T1074", "T1119", "T1070", "T1059" ]
02 资源文件 4
- 许可证LICENSE11.0 KB
- 参考文档references/api-reference.md1.5 KB
- 脚本scripts/agent.py6.8 KB
- 其他SKILL.md.tmpl16.1 KB
03 SKILL.md 正文
Performing File Carving with Foremost
When to Use
- When recovering files from unallocated disk space or corrupted file systems
- For extracting evidence from formatted or wiped storage media
- When file system metadata is unavailable but raw data sectors contain evidence
- During investigations requiring recovery of specific file types from raw images
- As a complement to file system-based recovery for maximum evidence extraction
Prerequisites
- Foremost installed on forensic workstation
- Forensic disk image in raw (dd) format
- Sufficient output storage (potentially larger than source)
- Custom foremost.conf for specialized file types (optional)
- Understanding of file signatures (magic bytes) for target file types
- Scalpel as an alternative for performance-critical carving
Workflow
Step 1: Install and Configure Foremost
# Install Foremost
sudo apt-get install foremost
# Verify installation
foremost -V
# Review default configuration
cat /etc/foremost.conf
# The default foremost.conf supports:
# jpg, gif, png, bmp - Image formats
# avi, exe, mpg, wav - Media and executables
# riff, wmv, mov, pdf - Documents and video
# ole (doc/xls/ppt), zip, rar - Office and archives
# htm, cpp, java - Text/code files
# Create custom configuration for additional file types
cp /etc/foremost.conf /cases/case-2024-001/custom_foremost.conf
# Add custom file signatures
cat << 'EOF' >> /cases/case-2024-001/custom_foremost.conf
# Custom additions for investigation
# Format: extension case_sensitive max_size header footer
docx y 10000000 \x50\x4b\x03\x04 \x50\x4b\x05\x06
xlsx y 10000000 \x50\x4b\x03\x04 \x50\x4b\x05\x06
pptx y 10000000 \x50\x4b\x03\x04 \x50\x4b\x05\x06
sqlite y 50000000 \x53\x51\x4c\x69\x74\x65\x20\x66\x6f\x72\x6d\x61\x74
pst y 500000000 \x21\x42\x44\x4e
eml y 1000000 \x46\x72\x6f\x6d\x3a \x0d\x0a\x0d\x0a
evtx y 50000000 \x45\x6c\x66\x46\x69\x6c\x65
EOF
Step 2: Run Foremost Against the Disk Image
# Basic carving of all supported file types
foremost -t all \
-i /cases/case-2024-001/images/evidence.dd \
-o /cases/case-2024-001/carved/foremost_all/
# Carve only specific file types
foremost -t jpg,png,pdf,doc,xls,zip \
-i /cases/case-2024-001/images/evidence.dd \
-o /cases/case-2024-001/carved/foremost_targeted/
# Use custom configuration
foremost -c /cases/case-2024-001/custom_foremost.conf \
-i /cases/case-2024-001/images/evidence.dd \
-o /cases/case-2024-001/carved/foremost_custom/
# Carve from a specific partition offset
# First, find partitions
mmls /cases/case-2024-001/images/evidence.dd
# Then carve from unallocated space only
# Extract unallocated space with blkls
blkls -o 2048 /cases/case-2024-001/images/evidence.dd \
> /cases/case-2024-001/unallocated.dd
foremost -t all \
-i /cases/case-2024-001/unallocated.dd \
-o /cases/case-2024-001/carved/foremost_unalloc/
# Verbose mode for detailed progress
foremost -v -t all \
-i /cases/case-2024-001/images/evidence.dd \
-o /cases/case-2024-001/carved/foremost_verbose/ 2>&1 | \
tee /cases/case-2024-001/carved/foremost_log.txt
# Indirect mode (process standard input)
dd if=/cases/case-2024-001/images/evidence.dd bs=512 skip=2048 | \
foremost -t jpg,pdf -o /cases/case-2024-001/carved/foremost_pipe/
Step 3: Use Scalpel for High-Performance Carving
# Install Scalpel (faster alternative based on Foremost)
sudo apt-get install scalpel
# Edit Scalpel configuration (uncomment desired file types)
cp /etc/scalpel/scalpel.conf /cases/case-2024-001/scalpel.conf
# Uncomment lines for target file types in the config
# Run Scalpel
scalpel -c /cases/case-2024-001/scalpel.conf \
-o /cases/case-2024-001/carved/scalpel/ \
/cases/case-2024-001/images/evidence.dd
# Scalpel with file size limits
# Edit scalpel.conf to set appropriate max sizes:
# jpg y 5000000 \xff\xd8\xff \xff\xd9
# pdf y 20000000 %PDF %%EOF
Step 4: Process and Validate Carved Files
# Review Foremost audit report
cat /cases/case-2024-001/carved/foremost_all/audit.txt
# The audit.txt contains:
# - Number of files found per type
# - Start and end offsets
# - File sizes
# Validate carved files
python3 << 'PYEOF'
import os
import subprocess
from collections import defaultdict
carved_dir = '/cases/case-2024-001/carved/foremost_all/'
stats = defaultdict(lambda: {'total': 0, 'valid': 0, 'invalid': 0, 'size': 0})
for subdir in os.listdir(carved_dir):
subdir_path = os.path.join(carved_dir, subdir)
if not os.path.isdir(subdir_path) or subdir == 'audit.txt':
continue
for filename in os.listdir(subdir_path):
filepath = os.path.join(subdir_path, filename)
if not os.path.isfile(filepath):
continue
ext = subdir
filesize = os.path.getsize(filepath)
stats[ext]['total'] += 1
stats[ext]['size'] += filesize
# Validate file using 'file' command
result = subprocess.run(['file', '--brief', filepath], capture_output=True, text=True)
file_type = result.stdout.strip()
if 'data' in file_type.lower() or 'empty' in file_type.lower():
stats[ext]['invalid'] += 1
else:
stats[ext]['valid'] += 1
print("=== CARVED FILE VALIDATION ===\n")
print(f"{'Type':<10} {'Total':<8} {'Valid':<8} {'Invalid':<10} {'Total Size':<15}")
print("-" * 55)
for ext in sorted(stats.keys()):
s = stats[ext]
size_mb = s['size'] / (1024*1024)
print(f"{ext:<10} {s['total']:<8} {s['valid']:<8} {s['invalid']:<10} {size_mb:>10.1f} MB")
# Remove zero-byte files
for subdir in os.listdir(carved_dir):
subdir_path = os.path.join(carved_dir, subdir)
if os.path.isdir(subdir_path):
for filename in os.listdir(subdir_path):
filepath = os.path.join(subdir_path, filename)
if os.path.isfile(filepath) and os.path.getsize(filepath) == 0:
os.remove(filepath)
PYEOF
# Hash all valid carved files
find /cases/case-2024-001/carved/foremost_all/ -type f ! -name "audit.txt" \
-exec sha256sum {} \; > /cases/case-2024-001/carved/carved_file_hashes.txt
# Check against known-bad hash database
# Check against NSRL known-good database to filter
Step 5: Examine and Catalog Evidence Files
# Extract metadata from carved images (EXIF data including GPS)
exiftool -r -csv /cases/case-2024-001/carved/foremost_all/jpg/ \
> /cases/case-2024-001/analysis/carved_image_metadata.csv
# Search carved documents for keywords
find /cases/case-2024-001/carved/foremost_all/pdf/ -name "*.pdf" -exec pdftotext {} - \; 2>/dev/null | \
grep -iE '(confidential|secret|password|account|ssn|credit.card)' \
> /cases/case-2024-001/analysis/keyword_hits_pdf.txt
# Generate thumbnails for image review
mkdir -p /cases/case-2024-001/carved/thumbnails/
find /cases/case-2024-001/carved/foremost_all/jpg/ -name "*.jpg" -exec \
convert {} -thumbnail 200x200 /cases/case-2024-001/carved/thumbnails/{} \; 2>/dev/null
# Create evidence catalog
python3 << 'PYEOF'
import os, hashlib, csv, subprocess
catalog = []
carved_dir = '/cases/case-2024-001/carved/foremost_all/'
for subdir in sorted(os.listdir(carved_dir)):
subdir_path = os.path.join(carved_dir, subdir)
if not os.path.isdir(subdir_path):
continue
for filename in sorted(os.listdir(subdir_path)):
filepath = os.path.join(subdir_path, filename)
if not os.path.isfile(filepath):
continue
size = os.path.getsize(filepath)
sha256 = hashlib.sha256(open(filepath, 'rb').read()).hexdigest()
file_type = subprocess.run(['file', '--brief', filepath], capture_output=True, text=True).stdout.strip()
catalog.append({
'filename': filename,
'type': subdir,
'size': size,
'sha256': sha256,
'file_description': file_type[:100]
})
with open('/cases/case-2024-001/analysis/carved_file_catalog.csv', 'w', newline='') as f:
writer = csv.DictWriter(f, fieldnames=['filename', 'type', 'size', 'sha256', 'file_description'])
writer.writeheader()
writer.writerows(catalog)
print(f"Catalog created with {len(catalog)} files")
PYEOF
Key Concepts
| Concept | Description |
|---|---|
| File carving | Recovering files by searching for known header/footer byte sequences in raw data |
| File signature | Unique byte pattern at the start (header) or end (footer) identifying a file type |
| Unallocated space | Disk sectors not assigned to any file; primary target for carving |
| Fragmentation | When file data is stored in non-contiguous sectors, complicating carving |
| Header-footer carving | Extracting data between known file start and end signatures |
| False positives | Carved data matching file signatures but containing corrupt or unrelated content |
| Slack space | Unused bytes at the end of a file's last allocated cluster |
| Sector alignment | Files typically start at sector boundaries, improving carving accuracy |
Tools & Systems
| Tool | Purpose |
|---|---|
| Foremost | Original header-footer file carving tool developed for US Air Force OSI |
| Scalpel | High-performance file carver with configurable signatures |
| PhotoRec | Signature-based file recovery supporting 300+ formats |
| bulk_extractor | Extracts features (emails, URLs, credit cards) from raw data |
| blkls | Sleuth Kit tool extracting unallocated space from disk images |
| mmls | Partition table display for identifying carving targets |
| ExifTool | Metadata extraction from carved image and document files |
| hashdeep | Recursive hash computation for carved file cataloging |
Common Scenarios
Scenario 1: Recovering Deleted Evidence Documents Run Foremost targeting doc, pdf, xlsx formats against the unallocated space extracted with blkls, validate carved documents, search content for case-relevant keywords, catalog and hash all recoverable documents, present as evidence.
Scenario 2: Image Recovery from Formatted Media Carve JPEG, PNG, GIF, BMP from a formatted USB drive image, extract EXIF metadata including GPS coordinates and camera information, generate thumbnails for rapid visual review, identify evidence-relevant images, document recovery chain.
Scenario 3: Email Recovery from Damaged PST Use custom foremost.conf with PST and EML signatures, carve email artifacts from damaged Outlook data file, attempt to open carved PST fragments in a viewer, extract individual EML messages, search for relevant communications.
Scenario 4: Database Recovery for Financial Investigation Configure Foremost to carve SQLite databases from unallocated space, recover application databases that were deleted, query recovered databases for financial records, cross-reference with known transaction data, document findings for prosecution.
Output Format
File Carving Summary:
Tool: Foremost 1.5.7
Source: evidence.dd (500 GB)
Target: Unallocated space (234 GB)
Duration: 1h 45m
Files Carved:
jpg: 2,345 files (1.8 GB) - Valid: 2,100 / Invalid: 245
png: 234 files (456 MB) - Valid: 210 / Invalid: 24
pdf: 156 files (890 MB) - Valid: 134 / Invalid: 22
doc: 89 files (234 MB) - Valid: 67 / Invalid: 22
xls: 45 files (123 MB) - Valid: 38 / Invalid: 7
zip: 67 files (567 MB) - Valid: 52 / Invalid: 15
exe: 34 files (234 MB) - Valid: 30 / Invalid: 4
sqlite: 12 files (89 MB) - Valid: 10 / Invalid: 2
Total Files: 2,982 (3.4 GB recovered)
Evidence-Relevant: 45 files flagged for review
Audit Log: /cases/case-2024-001/carved/foremost_all/audit.txt
File Catalog: /cases/case-2024-001/analysis/carved_file_catalog.csv
04 同仓库更多 Skills
verifying-build-provenance-with-slsa-sigstore
Verifies artifact signatures and SLSA provenance using Sigstore's cosign (verify, verify-attestation, verify-blob-attestation) and slsa-verifier (verify-artifact), enforcing keyless OIDC builder identity and source repo against SLSA Build levels. Use in CI/CD before deploying artifacts, when consuming third-party attestations, establishing a SLSA Build L3 pipeline, or confirming provenance during incident response or admission control.
validating-tpm-measured-boot-attestation
Verifies TPM 2.0 measured-boot integrity and remote attestation with tpm2-tools -- reading PCRs (tpm2_pcrread), replaying the boot event log, generating and checking signed quotes (tpm2_quote/tpm2_checkquote), and sealing secrets to a PCR policy. Use to confirm a system booted trusted firmware/kernel for Zero Trust device posture, detect boot-chain tampering via PCR drift, or build a golden-value baseline for fleet attestation.
validating-backup-integrity-for-recovery
Validates backup integrity through cryptographic hash verification, automated restore testing, corruption detection, and recoverability checks to confirm backups are reliable for disaster recovery and ransomware response. Use before relying on backups for recovery, when building post-backup validation pipelines, auditing backup infrastructure for compliance, or checking immutable/air-gapped backups for silent corruption or tampering.
triaging-windows-with-kape
Runs KAPE (Kroll Artifact Parser and Extractor) to collect targeted forensic artifacts (registry hives, $MFT, event logs, prefetch, browser data) via Targets and parse them with Modules wrapping Eric Zimmerman's EZ Tools (PECmd, MFTECmd, RECmd). Use during early incident containment/triage when full disk imaging is impractical but a defensible, parseable Windows artifact set is needed quickly, including at-scale remote collection.
triaging-vulnerabilities-with-ssvc-framework
Triages and prioritizes vulnerabilities with CISA's Stakeholder-Specific Vulnerability Categorization (SSVC) decision tree, weighing exploitation status (via the CISA KEV catalog and FIRST EPSS API), technical impact, automatability, and mission prevalence to output Track/Track*/Attend/Act decisions. Use when prioritizing vulnerability scan results (OpenVAS, Nessus, Qualys) for remediation planning beyond raw CVSS scores.
triaging-security-incident
Performs initial triage of security incidents using the NIST SP 800-61r3 and SANS PICERL frameworks, classifying incident type, assigning priority by business impact, and routing to the appropriate response team. Use when a SIEM/EDR alert needs human classification, concurrent alerts must be prioritized, or a user report or threat-intel IOC match requires initial incident categorization.