Five Steps to Defend Against AI-Driven Attacks and Secure Enterprise AI Use
Summary
ReliaQuest outlines five ways to address AI-related security risks, including automating response, governing enterprise AI use, limiting agent permissions, continuously testing defenses, and keeping governance aligned with adoption.
Key points
- AI expands the attack surface through faster, more accessible attacks and increased enterprise use that can expose sensitive data or give agents excessive access.
- The article recommends automating containment and remediation to help defenders respond at machine speed.
- Provide approved AI tools with guardrails and visibility into data employees share with them.
- Limit each agent to the permissions and tools it needs; use layered protections against prompt injection and scope expansion, with continuous testing.
- Continuously map attack paths and validate defenses, feeding results into detections, threat hunts, playbooks, and remediation.
- Make AI adoption visible through governance and procurement processes that support safe use without blocking it outright.
Article Details
- Defense Focus
- Defend against AI-accelerated attacks while securing organizational AI adoption, data access, and agent permissions.
- Detection Methods
- Use compliance APIs for real-time visibility into data employees provide to AI models and to identify prohibited sharing.
- Map attack paths through identities, permissions, exposures, and controls as the environment changes.
- Execute techniques against the live environment to validate whether controls hold, then turn findings into detections and hunts.
- Continuously test AI agents for prompt injection, scope expansion, and performance drift.
- Data Sources
- AI compliance API data
- File-sharing and access permissions
- Agent permissions and available tool calls
- Identity, exposure, and security-control data
- Security alerts and validation findings
- AI procurement and adoption records
- Defensive Actions
- Automate containment and remediation, aiming to prevent threats from remaining in the environment longer than 30 minutes.
- Start by automating the five highest-priority alerts.
- Give agents only the access of the person directing them and scope each permitted tool call.
- Apply guardrails to AI use and block data sharing that violates policy.
- Validate agents before, during, and after deployment using quality scoring and golden datasets.
- Feed attack-path validation findings into detections, hunts, playbooks, and remediation.
- Bring security into AI procurement to identify unsanctioned adoption early.