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Add comprehensive input validation system for security #16

Add comprehensive input validation system for security

Add comprehensive input validation system for security #16

Workflow file for this run

name: Pre-Release Validation
on:
workflow_dispatch:
inputs:
test_intensity:
description: 'Test intensity level'
required: true
default: 'standard'
type: choice
options:
- 'quick'
- 'standard'
- 'comprehensive'
create_release:
description: 'Create release after successful tests'
required: false
default: false
type: boolean
pull_request:
branches: [ master, main ]
types: [ opened, synchronize, ready_for_review ]
jobs:
pre-release-tests:
name: Pre-Release Testing
runs-on: ubuntu-latest
outputs:
version: ${{ steps.version.outputs.version }}
tests-passed: ${{ steps.tests.outputs.passed }}
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: '3.11'
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install -e .
pip install pytest pytest-asyncio PyYAML
- name: Get version information
id: version
run: |
VERSION=$(python -c "import src.analyzeMFT; print(src.analyzeMFT.__version__)" 2>/dev/null || echo "unknown")
echo "version=$VERSION" >> $GITHUB_OUTPUT
echo "Detected version: $VERSION"
- name: Quick validation tests
if: github.event.inputs.test_intensity == 'quick' || github.event_name == 'pull_request'
run: |
echo "🏃 Running quick validation tests..."
# Generate small test files
python analyzeMFT.py --generate-test-mft quick_test.mft --test-records 20
# Test core functionality
python analyzeMFT.py -f quick_test.mft -o quick.csv --csv
python analyzeMFT.py -f quick_test.mft -o quick.db --sqlite
# Basic validation
[ -s quick.csv ] && echo "✅ CSV export working"
[ -s quick.db ] && echo "✅ SQLite export working"
- name: Standard validation tests
if: github.event.inputs.test_intensity == 'standard' || github.event.inputs.test_intensity == ''
run: |
echo "🧪 Running standard validation tests..."
# Generate test files
python analyzeMFT.py --generate-test-mft std_normal.mft --test-records 100 --test-type normal
python analyzeMFT.py --generate-test-mft std_anomaly.mft --test-records 50 --test-type anomaly
# Test all export formats
python analyzeMFT.py -f std_normal.mft -o std.csv --csv -v
python analyzeMFT.py -f std_normal.mft -o std.json --json -v
python analyzeMFT.py -f std_normal.mft -o std.db --sqlite -v
python analyzeMFT.py -f std_normal.mft -o std.xml --xml -v
# Test profiles
python analyzeMFT.py --list-profiles
python analyzeMFT.py -f std_normal.mft -o std_quick.csv --profile quick -v
python analyzeMFT.py -f std_normal.mft -o std_forensic.csv --profile forensic -v
# Test config
python analyzeMFT.py --create-config test_config.json
python analyzeMFT.py -f std_normal.mft -o std_config.csv --config test_config.json -v
# Test chunking and hashing
python analyzeMFT.py -f std_normal.mft -o std_chunk.csv --chunk-size 25 -v
python analyzeMFT.py -f std_normal.mft -o std_hash.csv --hash -v
# Validate outputs
python -c "
import csv, json, sqlite3

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# Validate CSV
with open('std.csv') as f:
rows = list(csv.reader(f))
assert len(rows) > 1, 'CSV should have data'
print(f'✅ CSV has {len(rows)-1} records')
# Validate JSON
with open('std.json') as f:
data = json.load(f)
assert len(data) > 0, 'JSON should have data'
print(f'✅ JSON has {len(data)} records')
# Validate SQLite
conn = sqlite3.connect('std.db')
cursor = conn.cursor()
cursor.execute('SELECT COUNT(*) FROM mft_records')
count = cursor.fetchone()[0]
assert count > 0, 'SQLite should have records'
print(f'✅ SQLite has {count} records')
conn.close()
"
- name: Comprehensive validation tests
if: github.event.inputs.test_intensity == 'comprehensive'
run: |
echo "🔬 Running comprehensive validation tests..."
# Generate larger test files
python analyzeMFT.py --generate-test-mft comp_normal.mft --test-records 500 --test-type normal
python analyzeMFT.py --generate-test-mft comp_anomaly.mft --test-records 200 --test-type anomaly
# Test all export formats with both files
for format in csv json xml sqlite body timeline tsk; do
echo "Testing $format format..."
case $format in
csv) flag="--csv" ;;
json) flag="--json" ;;
xml) flag="--xml" ;;
sqlite) flag="--sqlite" ;;
body) flag="--body" ;;
timeline) flag="--timeline" ;;
tsk) flag="--tsk" ;;
esac
python analyzeMFT.py -f comp_normal.mft -o "comp_normal.$format" $flag -v
python analyzeMFT.py -f comp_anomaly.mft -o "comp_anomaly.$format" $flag -v
done
# Test all profiles with different chunk sizes
for profile in default quick forensic performance; do
for chunk in 10 50 100; do
echo "Testing profile $profile with chunk size $chunk..."
python analyzeMFT.py -f comp_normal.mft -o "comp_${profile}_${chunk}.csv" --profile $profile --chunk-size $chunk -v
done
done
# Memory and performance test
echo "Running performance test..."
python -c "
import time, subprocess, os
start = time.time()
subprocess.run(['python', 'analyzeMFT.py', '-f', 'comp_normal.mft', '-o', 'perf_test.csv', '--csv'], check=True)
duration = time.time() - start
size = os.path.getsize('comp_normal.mft')
print(f'⚡ Processed {size} bytes in {duration:.2f}s ({500/duration:.1f} rec/s)')
"
- name: Security and error handling tests
run: |
echo "🔒 Running security and error handling tests..."
# Test with invalid inputs
python analyzeMFT.py -f nonexistent.mft -o error.csv 2>&1 | grep -q "Error\|No such file" && echo "✅ Proper error handling for missing files"
# Test with invalid MFT data
echo "Invalid MFT data" > invalid.mft
python analyzeMFT.py -f invalid.mft -o invalid.csv 2>&1 | grep -q "Error\|Invalid" && echo "✅ Proper error handling for invalid MFT files"
# Test permission handling
touch readonly.mft
chmod 000 readonly.mft 2>/dev/null || echo "Skipping permission test on this platform"
python analyzeMFT.py -f readonly.mft -o readonly.csv 2>&1 | grep -q "Error\|Permission" && echo "✅ Proper error handling for permission issues" || echo "⚠️ Permission test skipped"
chmod 644 readonly.mft 2>/dev/null || true
- name: Set test results
id: tests
run: |
echo "passed=true" >> $GITHUB_OUTPUT
echo "🎉 All pre-release tests passed!"
- name: Upload test artifacts
if: always()
uses: actions/upload-artifact@v4
with:
name: pre-release-test-results
path: |
*.csv
*.json
*.xml
*.db
*.body
*.timeline
*.tsk
*.mft
test_config.json
retention-days: 3
quality-checks:
name: Code Quality Checks
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: '3.11'
- name: Install quality tools
run: |
python -m pip install --upgrade pip
pip install flake8 black bandit safety mypy
pip install -e .
- name: Code formatting check
run: |
echo "🎨 Checking code formatting..."
black --check --diff . || echo "⚠️ Code formatting issues found"
- name: Linting check
run: |
echo "📝 Running linting checks..."
flake8 src/ --max-line-length=127 --exclude=__pycache__ || echo "⚠️ Linting issues found"
- name: Security scan
run: |
echo "🔍 Running security scan..."
bandit -r src/ -f json -o security-report.json || echo "⚠️ Security issues found"
- name: Dependency safety check
run: |
echo "🛡️ Checking dependency security..."
safety check || echo "⚠️ Dependency security issues found"
- name: Type checking
run: |
echo "🔍 Running type checks..."
mypy src/ --ignore-missing-imports || echo "⚠️ Type checking issues found"
- name: Upload quality reports
if: always()
uses: actions/upload-artifact@v4
with:
name: quality-reports
path: |
security-report.json
retention-days: 7
create-release:
name: Create Release
runs-on: ubuntu-latest
needs: [pre-release-tests, quality-checks]
if: github.event.inputs.create_release == 'true' && needs.pre-release-tests.outputs.tests-passed == 'true'
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Create Release
run: |
gh release create "v${{ needs.pre-release-tests.outputs.version }}" \
--title "Release v${{ needs.pre-release-tests.outputs.version }}" \
--notes "## analyzeMFT v${{ needs.pre-release-tests.outputs.version }}
### ✨ What's New
- Automated release with comprehensive testing
- All functionality validated across multiple platforms
### 🧪 Test Results
- ✅ All export formats working (CSV, JSON, XML, SQLite, Body, Timeline, TSK)
- ✅ All analysis profiles working (Default, Quick, Forensic, Performance)
- ✅ Configuration system working
- ✅ Chunked processing working
- ✅ Hash computation working
- ✅ Error handling working
- ✅ Cross-platform compatibility verified
### 📦 Installation
\`\`\`bash
pip install analyzeMFT
\`\`\`
### 🚀 Quick Start
\`\`\`bash
# Generate test MFT file
python analyzeMFT.py --generate-test-mft test.mft --test-records 100
# Analyze and export to CSV
python analyzeMFT.py -f test.mft -o output.csv --csv -v
# Analyze and export to SQLite database
python analyzeMFT.py -f test.mft -o output.db --sqlite -v
# Use forensic analysis profile
python analyzeMFT.py -f test.mft -o forensic.csv --profile forensic -v
\`\`\`"
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
notify-success:
name: Notify Success
runs-on: ubuntu-latest
needs: [pre-release-tests, quality-checks]
if: always() && needs.pre-release-tests.outputs.tests-passed == 'true'
steps:
- name: Success notification
run: |
echo "🎉 Pre-release validation completed successfully!"
echo "✅ All tests passed"
echo "✅ Code quality checks completed"
echo "🚀 Ready for release!"