Skills
skills/jeremylongshore/claude-code-plugins-plus-skills/implementing-database-audit-logging

implementing-database-audit-logging

Installation
SKILL.md

Database Audit Logger

Overview

Implement database audit logging to track all data modifications (INSERT, UPDATE, DELETE) with full before/after values, user identity, timestamps, and application context. This skill supports trigger-based auditing for PostgreSQL and MySQL, change data capture (CDC) patterns, and application-level audit logging.

Prerequisites

  • Database credentials with CREATE TABLE, CREATE FUNCTION, and CREATE TRIGGER permissions
  • psql or mysql CLI for executing audit setup DDL
  • Understanding of applicable compliance requirements (which tables, which operations, retention period)
  • Estimated storage for audit logs: plan for 10-30% of the audited table's data volume per year
  • Separate tablespace or storage volume for audit data to prevent audit growth from affecting application performance

Instructions

  1. Identify tables requiring audit logging based on compliance and business needs:

    • Tables containing PII (users, contacts, addresses) -- GDPR/HIPAA requirement
    • Tables containing financial data (transactions, payments, invoices) -- SOX/PCI-DSS requirement
    • Tables containing access control data (roles, permissions, API keys) -- security requirement
    • Determine which operations to audit per table: INSERT, UPDATE, DELETE, or all three

  2. Create the audit log table with comprehensive metadata:

    CREATE TABLE audit_log (
  id BIGSERIAL PRIMARY KEY,
  table_name VARCHAR(100) NOT NULL,
  record_id TEXT NOT NULL,
  action VARCHAR(10) NOT NULL CHECK (action IN ('INSERT', 'UPDATE', 'DELETE')),
  old_values JSONB,
  new_values JSONB,
  changed_columns TEXT[],
  changed_by VARCHAR(100),
  changed_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
  client_ip INET,
  application_name VARCHAR(100),
  transaction_id BIGINT
);

  3. Add indexes for common audit queries:

    • CREATE INDEX idx_audit_table_record ON audit_log (table_name, record_id)
    • CREATE INDEX idx_audit_changed_at ON audit_log (changed_at)
    • CREATE INDEX idx_audit_changed_by ON audit_log (changed_by)
    • CREATE INDEX idx_audit_action ON audit_log (table_name, action)

  4. Create the PostgreSQL audit trigger function:

    CREATE OR REPLACE FUNCTION audit_trigger_func() RETURNS TRIGGER AS $$
BEGIN
  IF TG_OP = 'INSERT' THEN
    INSERT INTO audit_log (table_name, record_id, action, new_values, changed_by, client_ip, application_name, transaction_id)
    VALUES (TG_TABLE_NAME, NEW.id::text, 'INSERT', to_jsonb(NEW), current_setting('app.user', true), inet_client_addr(), current_setting('application_name'), txid_current());
  ELSIF TG_OP = 'UPDATE' THEN
    INSERT INTO audit_log (table_name, record_id, action, old_values, new_values, changed_by, client_ip, application_name, transaction_id)
    VALUES (TG_TABLE_NAME, NEW.id::text, 'UPDATE', to_jsonb(OLD), to_jsonb(NEW), current_setting('app.user', true), inet_client_addr(), current_setting('application_name'), txid_current());
  ELSIF TG_OP = 'DELETE' THEN
    INSERT INTO audit_log (table_name, record_id, action, old_values, changed_by, client_ip, application_name, transaction_id)
    VALUES (TG_TABLE_NAME, OLD.id::text, 'DELETE', to_jsonb(OLD), current_setting('app.user', true), inet_client_addr(), current_setting('application_name'), txid_current());
  END IF;
  RETURN COALESCE(NEW, OLD);
END;
$$ LANGUAGE plpgsql;

  5. Attach triggers to each audited table:

    • CREATE TRIGGER audit_users AFTER INSERT OR UPDATE OR DELETE ON users FOR EACH ROW EXECUTE FUNCTION audit_trigger_func()
    • Repeat for each table requiring audit logging

  6. Pass application-level user context to the database session so audit logs capture the actual application user (not just the database role):

    • At the start of each request: SET LOCAL app.user = 'user@example.com'
    • For connection pools, set in the connection checkout hook
    • This value is captured by current_setting('app.user', true) in the trigger

  7. Partition the audit_log table by month for efficient querying and archival:

    • CREATE TABLE audit_log (...) PARTITION BY RANGE (changed_at)
    • Create monthly partitions: CREATE TABLE audit_log_2024_01 PARTITION OF audit_log FOR VALUES FROM ('2024-01-01') TO ('2024-02-01')
    • Automate partition creation for future months

  8. Protect audit log integrity:

    • Revoke UPDATE and DELETE permissions on audit_log from all application users
    • Grant only INSERT permission to the trigger execution context
    • Consider using pg_audit extension for additional tamper protection
    • Ship audit logs to an external system (SIEM, S3) for independent retention

  9. Create compliance report queries:

    • Change history for a record: SELECT * FROM audit_log WHERE table_name = 'users' AND record_id = '12345' ORDER BY changed_at
    • All changes by a user: SELECT * FROM audit_log WHERE changed_by = 'user@example.com' ORDER BY changed_at DESC
    • Bulk operations detection: SELECT changed_by, table_name, action, COUNT(*) FROM audit_log WHERE changed_at > NOW() - INTERVAL '1 hour' GROUP BY 1,2,3 HAVING COUNT(*) > 100
    • Off-hours activity: SELECT * FROM audit_log WHERE EXTRACT(HOUR FROM changed_at) NOT BETWEEN 8 AND 18

  10. Set up audit log archival: move audit records older than the retention period to cold storage (S3, Azure Blob). Maintain the archive manifest for retrieval. Typical retention: 1-3 years in database, 7+ years in cold storage for financial data.

Output

  • Audit table DDL with proper columns, indexes, and partitioning
  • Audit trigger function capturing full before/after values with user context
  • Trigger attachment scripts for each audited table
  • Compliance report queries for common audit scenarios
  • Archival configuration for audit log lifecycle management

Error Handling

Error Cause Solution
Audit trigger slows INSERT/UPDATE operations Trigger overhead on high-write tables Audit only critical columns instead of full rows; use asynchronous audit with pg_notify and a listener process; batch audit writes
Audit table consuming excessive disk space High write volume tables generating millions of audit records Partition by month; archive old partitions to cold storage; audit only specific columns with WHEN clause on trigger
current_setting('app.user') returns NULL Application not setting session variable before database operations Set default in trigger: COALESCE(current_setting('app.user', true), current_user); add connection pool checkout hook
Audit log INSERT fails, blocking application operation Audit table full, permission error, or constraint violation Use BEGIN ... EXCEPTION WHEN OTHERS THEN NULL; END in trigger to prevent audit failures from blocking operations; alert on audit failures
Cannot determine which columns changed in UPDATE Full row stored as JSON, no column-level diff Add changed_columns computation in trigger: compare OLD and NEW field by field; store only changed fields in new_values

Examples

HIPAA-compliant audit logging for a healthcare database: Audit triggers on patient_records, prescriptions, and lab_results tables capture all modifications with practitioner identity. Audit logs are immutable (no UPDATE/DELETE grants), partitioned monthly, and archived to encrypted S3 after 1 year. Quarterly compliance reports show access patterns per practitioner and flag unusual access (patient records accessed without an appointment).

Detecting unauthorized data modifications: Audit log query reveals 500 DELETE operations on the billing table by a service account at 3 AM, outside normal business hours. Alert triggers for bulk operations exceeding 100 rows. Investigation traces the operations to a misconfigured cleanup job. Audit log provides the complete list of deleted records for restoration.

GDPR data access request fulfillment: When a user requests their data access log under GDPR Article 15, the audit system provides a complete history of who accessed or modified their personal data: SELECT changed_by, action, changed_at, changed_columns FROM audit_log WHERE table_name = 'users' AND record_id = '12345' ORDER BY changed_at. The report is generated within the 30-day compliance window.

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