Complete Phase 1: Foundation - Flask web application infrastructure
Implement complete database schema and Flask application structure for SneakyScan web interface. This establishes the foundation for web-based scan management, scheduling, and visualization. Database & ORM: - Add 11 SQLAlchemy models for comprehensive scan data storage (Scan, ScanSite, ScanIP, ScanPort, ScanService, ScanCertificate, ScanTLSVersion, Schedule, Alert, AlertRule, Setting) - Configure Alembic migrations system with initial schema migration - Add init_db.py script for database initialization and password setup - Support both migration-based and direct table creation Settings System: - Implement SettingsManager with automatic encryption for sensitive values - Add Fernet encryption for SMTP passwords and API tokens - Implement PasswordManager with bcrypt password hashing (work factor 12) - Initialize default settings for SMTP, authentication, and retention Flask Application: - Create Flask app factory pattern with scoped session management - Add 4 API blueprints: scans, schedules, alerts, settings - Implement functional Settings API (GET/PUT/DELETE endpoints) - Add CORS support, error handlers, and request/response logging - Configure development and production logging to file and console Docker & Deployment: - Update Dockerfile to install Flask dependencies - Add docker-compose-web.yml for web application deployment - Configure volume mounts for database, output, and logs persistence - Expose port 5000 for Flask web server Testing & Validation: - Add validate_phase1.py script to verify all deliverables - Validate directory structure, Python syntax, models, and endpoints - All validation checks passing Documentation: - Add PHASE1_COMPLETE.md with comprehensive Phase 1 summary - Update ROADMAP.md with Phase 1 completion status - Update .gitignore to exclude database files and documentation Files changed: 21 files - New: web/ directory with complete Flask app structure - New: migrations/ with Alembic configuration - New: requirements-web.txt with Flask dependencies - Modified: Dockerfile, ROADMAP.md, .gitignore
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migrations/env.py
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83
migrations/env.py
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"""Alembic migration environment for SneakyScanner."""
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from logging.config import fileConfig
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from sqlalchemy import engine_from_config
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from sqlalchemy import pool
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from alembic import context
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# Import all models to ensure they're registered with Base
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from web.models import Base
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# this is the Alembic Config object, which provides
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# access to the values within the .ini file in use.
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config = context.config
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# Interpret the config file for Python logging.
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# This line sets up loggers basically.
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if config.config_file_name is not None:
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fileConfig(config.config_file_name)
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# add your model's MetaData object here
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# for 'autogenerate' support
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# from myapp import mymodel
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# target_metadata = mymodel.Base.metadata
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target_metadata = Base.metadata
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# other values from the config, defined by the needs of env.py,
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# can be acquired:
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# my_important_option = config.get_main_option("my_important_option")
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# ... etc.
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def run_migrations_offline() -> None:
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"""Run migrations in 'offline' mode.
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This configures the context with just a URL
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and not an Engine, though an Engine is acceptable
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here as well. By skipping the Engine creation
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we don't even need a DBAPI to be available.
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Calls to context.execute() here emit the given string to the
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script output.
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"""
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url = config.get_main_option("sqlalchemy.url")
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context.configure(
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url=url,
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target_metadata=target_metadata,
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literal_binds=True,
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dialect_opts={"paramstyle": "named"},
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)
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with context.begin_transaction():
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context.run_migrations()
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def run_migrations_online() -> None:
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"""Run migrations in 'online' mode.
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In this scenario we need to create an Engine
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and associate a connection with the context.
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"""
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connectable = engine_from_config(
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config.get_section(config.config_ini_section, {}),
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prefix="sqlalchemy.",
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poolclass=pool.NullPool,
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)
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with connectable.connect() as connection:
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context.configure(
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connection=connection, target_metadata=target_metadata
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)
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with context.begin_transaction():
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context.run_migrations()
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if context.is_offline_mode():
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run_migrations_offline()
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else:
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run_migrations_online()
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