Database Security Best Practices
Universal security principles for databases in AI-generated applications. Learn foundational security practices that apply across PostgreSQL, MySQL, MongoDB, Firestore, and other database systems.
Database Security is Multi-Layered
Secure databases require multiple layers of protection: authentication, authorization, encryption, input validation, and monitoring. No single control provides complete security. These principles apply regardless of database technology.
Access Control
Principle of Least Privilege
Grant minimum necessary permissions. Application database users should not have DROP, ALTER, or GRANT privileges.
Implementation:
Create separate roles for read-only, read-write, and admin operations
Default Deny
Start with no access and explicitly grant permissions. Use allowlists instead of denylists for security rules.
Implementation:
Deny all operations by default, then add specific rules for allowed operations
Defense in Depth
Layer multiple security controls. Even if one fails, others provide protection.
Implementation:
Combine database-level permissions, row-level security, and application-level authorization
Data Protection
Encryption at Rest
Encrypt sensitive data in the database. Use database-native encryption or application-level encryption for PII.
Implementation:
Enable database encryption, use encrypted columns for sensitive fields
Encryption in Transit
Always use TLS/SSL for database connections. Never transmit credentials or data over unencrypted channels.
Implementation:
Enforce SSL-only connections, reject unencrypted database connection attempts
Secure Credential Storage
Never hardcode database credentials. Use environment variables, secret managers, or credential rotation systems.
Implementation:
Store credentials in AWS Secrets Manager, HashiCorp Vault, or equivalent
Input Validation
Parameterized Queries
Always use prepared statements or parameterized queries. Never construct SQL from string concatenation.
Implementation:
Use ORM query builders or database driver parameterization, ban raw SQL
Type Validation
Validate data types at application and database layers. Use database constraints and CHECK constraints.
Implementation:
Define NOT NULL, CHECK, and type constraints in schema definitions
Length Limits
Enforce maximum lengths on text fields to prevent overflow attacks and storage abuse.
Implementation:
Set VARCHAR length limits, validate array sizes, limit JSON document depth
Monitoring & Auditing
Audit Logging
Log all authentication attempts, permission changes, and sensitive data access for compliance and incident response.
Implementation:
Enable database audit logs, log failed queries, track administrative actions
Query Monitoring
Monitor for unusual query patterns, slow queries, and failed permission checks that indicate attacks.
Implementation:
Set up alerts for permission errors, unusual query volume, and long-running queries
Regular Security Reviews
Periodically audit database permissions, security rules, and access patterns to identify drift from security baseline.
Implementation:
Schedule quarterly permission audits, review security rule changes, check for stale accounts
Common Database Vulnerabilities
SQL Injection
CriticalString concatenation in queries allows attackers to inject malicious SQL and read or modify unauthorized data
Exposed Credentials
CriticalDatabase passwords in code repositories, environment files committed to git, or hardcoded connection strings
Missing Access Controls
CriticalNo row-level security or authentication checks, allowing users to access or modify any data in the database
Unencrypted Connections
HighDatabase connections without TLS/SSL, exposing credentials and data to network interception
Related Resources
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