AI and Insider Threats: Securing Your Database at Its Source

The Impact of AI on Insider Threats — and Why Securing Data at Its Source Matters

AI is transforming the way many organisations operate, some of the benefits include offering automation, advanced analytics, and predictive insights. But as AI becomes more deeply ingrained in everyday task, the attack surface expands — not just for external threat actors, but for insiders with legitimate access and illigimiate intentions.

When employees, contractors, or automated processes can interact directly with production data, traditional perimeter-based security controls are no longer enough. The database — the system of record — must become the first line of defence not the final one!

AI and the Evolving Insider Threat

AI introduces both capability and complexity:

AI models often require broad data access to train effectively, sometimes spanning sensitive datasets. Operating at scale, can open up the risk of misconfiguration or compromised credentials exposing vast amounts of data in seconds. Generative AI tools can be used to exfiltrate data, or to assist in privilege escalation by analysing internal patterns and configurations.

The result: insider threats are now faster, more subtle, and harder to detect.

Why This Matters for SMEs

Insider threats are not limited to large enterprises. SMEs often operate with fewer controls, shared credentials, or minimal separation of duties — making them more vulnerable to human error or deliberate misuse.

By securing data at the database layer, SMEs gain a resilient first and last line of defence. Even if perimeter defences or application layers are compromised, sensitive data remains protected, encrypted, and auditable.

AI is reshaping both how we use data and how it can be misused. Protecting against insider threats now means treating the database as the core security boundary — not just a storage layer.

Encryption, auditing, and continuous posture assessment are no longer optional; they are essential safeguards for data integrity and trust.

Securing Data at Its Source
The most effective way to protect against insider threats — AI-assisted or otherwise — is to secure data where it lives: in the database. A modern database security posture should include:

1. Encryption Everywhere - Use database-native TDE to encrypt data at rest (datafiles, temp, and backups). For highly sensitive columns, prefer client-side or application-level encryption (e.g. SQL Server Always Encrypted) so the database never sees plaintext. Require encrypted connections for in-transit data (e.g. TLS 1.2+ for SQL Server/Azure SQL, TCPS or Native Network Encryption for Oracle).

2. Access Control - Implement least-privilege using database roles and object/schema-level permissions. Keep built-in highly privileged accounts (e.g. sa, SYS) disabled for interactive use, credential-vaulted, and fully audited rather than “eliminated.” Integrate with enterprise identity (e.g. Active Directory / IdP) to get centralised authentication and, where available (e.g. Azure SQL), Conditional Access or MFA for admin-level access.

3. Auditing and Anomaly Detection - Turn on native database auditing (SQL Server Audit; Oracle Unified Auditing) to record logins, privileged operations, and access to sensitive objects. Forward audit events to a central SIEM / DAM so you can apply behavioural or ML-based detection to spot abnormal access patterns or possible insider misuse.

4. Data Classification and Masking - Use built-in or external classification to identify PII, financial, health, and other regulated data. Apply dynamic masking or redaction (SQL Server Dynamic Data Masking, Oracle Data Redaction) so lower-trust users see obfuscated values without changing application code. Note: masking/redaction is an access-control feature, not a replacement for encryption at rest.

5. Regular Security Posture Assessments - Include database security checks in your regular health reviews: confirm platform patch/CU/RU levels, review privileged roles and directory-mapped users, verify auditing is enabled and forwarding, and confirm TDE/encryption coverage for all production databases and backups. Managed database services can schedule and enforce these controls to maintain compliance and minimise drift.

At DataWyse, we help organisations across Australia strengthen their database security posture, enabling full encryption, monitoring, and governance to ensure data remains protected — even in the age of AI.

Your AI initiatives will only be as secure as the data they rely on. Make sure that foundation is solid.

Your Data. Our Expertise. Trusted Results.