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
This commit is contained in:
2025-11-13 23:59:23 -06:00
parent e29c839d80
commit 986c0d3d17
22 changed files with 3138 additions and 42 deletions

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migrations/env.py Normal file
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"""Alembic migration environment for SneakyScanner."""
from logging.config import fileConfig
from sqlalchemy import engine_from_config
from sqlalchemy import pool
from alembic import context
# Import all models to ensure they're registered with Base
from web.models import Base
# this is the Alembic Config object, which provides
# access to the values within the .ini file in use.
config = context.config
# Interpret the config file for Python logging.
# This line sets up loggers basically.
if config.config_file_name is not None:
fileConfig(config.config_file_name)
# add your model's MetaData object here
# for 'autogenerate' support
# from myapp import mymodel
# target_metadata = mymodel.Base.metadata
target_metadata = Base.metadata
# other values from the config, defined by the needs of env.py,
# can be acquired:
# my_important_option = config.get_main_option("my_important_option")
# ... etc.
def run_migrations_offline() -> None:
"""Run migrations in 'offline' mode.
This configures the context with just a URL
and not an Engine, though an Engine is acceptable
here as well. By skipping the Engine creation
we don't even need a DBAPI to be available.
Calls to context.execute() here emit the given string to the
script output.
"""
url = config.get_main_option("sqlalchemy.url")
context.configure(
url=url,
target_metadata=target_metadata,
literal_binds=True,
dialect_opts={"paramstyle": "named"},
)
with context.begin_transaction():
context.run_migrations()
def run_migrations_online() -> None:
"""Run migrations in 'online' mode.
In this scenario we need to create an Engine
and associate a connection with the context.
"""
connectable = engine_from_config(
config.get_section(config.config_ini_section, {}),
prefix="sqlalchemy.",
poolclass=pool.NullPool,
)
with connectable.connect() as connection:
context.configure(
connection=connection, target_metadata=target_metadata
)
with context.begin_transaction():
context.run_migrations()
if context.is_offline_mode():
run_migrations_offline()
else:
run_migrations_online()