AN OAS WARNING - AI AGENTS CAN BECOME A SERIOUS INSIDER THREAT
AI agents are increasingly integrated into workflows and treating them as trusted entities without proper oversight is a recipe for risk. Here's a breakdown of why AI agents can be insider threats and how to secure them effectively:
Why AI Agents Pose Insider Threat Risks
- Access to Sensitive Data: AI agents often have broad access to internal systems, documents, and communications.
- Autonomous Actions: Some agents can execute tasks, send emails, or modify files—just like human employees.
- Lack of Accountability: Unlike humans, AI agents don’t have personal liability, making it harder to assign blame or responsibility.
- Manipulation or Misuse: If compromised, they can be weaponized to exfiltrate data, spread misinformation, or disrupt operations.
How to Secure AI Agents Like Human Workers
| Security Practice | Human Workers | AI Agents |
| Identity & Access Management | Role-based access, MFA | API keys, scoped permissions, audit logs |
Behaviour Monitoring | Insider threat detection tools | Usage analytics, anomaly detection |
Training & Awareness | Security training, phishing drills | Guardrails, prompt filtering, sandboxing |
| Incident Response | HR + IT coordination | AI-specific playbooks, rollback mechanisms |
| Zero Trust Architecture | Verify every access attempt | Validate every AI action and output |
Pro Tips for AI Governance
- Limit Scope: Don’t give AI agents blanket access—apply the principle of least privilege.
- Audit Everything: Log interactions, decisions, and data access for forensic analysis.
- Human-in-the-Loop: Require human approval for high-risk actions or decisions.
- Model Validation: Regularly test and validate AI behaviours against expected norms.
- Ethical Guardrails: Ensure agents align with company values and legal standards.
AI Security Policy and an accompanying Threat Model.
AI Security Policy Template
1. Purpose Define the goal of the policy:
“To ensure the secure deployment, operation, and oversight of AI agents within the organization, minimizing risks to data, systems, and operations.”
2. Scope Specify what the policy covers:
- All AI agents (internal, third-party, cloud-based)
- All departments and workflows using AI
- All data accessed or processed by AI
3. Roles & Responsibilities
- AI Owners: Teams deploying or managing AI agents
- Security Team: Monitors AI behavior and enforces controls
- Compliance Team: Ensures regulatory alignment
- End Users: Responsible for safe interaction with AI tools
4. Access Control
- Role-based access for AI agents
- API key rotation and encryption
- Least privilege principle enforced
5. Monitoring & Logging
- Continuous monitoring of AI inputs/outputs
- Logging of all AI interactions and decisions
- Alerts for anomalous behaviours
6. Incident Response
- AI-specific playbooks for breaches or misuse
- Isolation procedures for compromised agents
- Post-incident review and retraining
7. Ethical & Legal Compliance
- Prohibit bias, discrimination, or unethical automation
- Ensure GDPR, POPIA, HIPAA, or other compliance
- Regular audits of AI decision-making
8. Training & Awareness
- Staff training on AI risks and safe usage
- Developer training on secure AI design
AI Threat Model Framework
| Threat Category | Example Risk | Mitigation Strategy |
| Data Leakage | AI accesses or shares sensitive info | Data classification, output filtering |
| Model Manipulation | Prompt injection or adversarial input | Input sanitization, validation layers |
| Unauthorized Access | AI agent used to by pass controls | Strong auth, scoped API permissions |
| Autonomous Misuse | AI sends emails or modifies files | Human-in-the-loop, action approval |
| Third-Party Risk | External AI tools with poor security | Vendor assessment, sandboxing |
| Bias & Ethics | AI makes discriminatory decisions | Bias testing, fairness audits |
The bottom line is - securing work, regardless of the WORKER
The positive aspect is that if treating AI agents as any human employee, will enable organisations to integrating them securely into the environment. In other words, creating protective measures for secure workspaces managed by human workers, recognize that these same controls—such as identity management, access control, session monitoring, and anomaly detection—must now also apply to AI workers.
The Core Principle
The key principle remains unchanged: secure the work itself, not merely the worker. Whether the worker is human or AI, whether they’re in the office or working remotely, and regardless of whether they are using a managed device or their own, the work must be safeguarded at the point of execution.
- AI agents will function as first-class workers.
- They will be assigned identities and access controls, and will be monitored and contained, just like their human counterparts.
Ultimately, it’s not particularly beneficial to worry about whether AI agents can be compromised; they can and will be. Instead, focus on ensuring the organisation has the necessary controls in place to detect, contain, and respond effectively when such incidents occur. This strategy is essential to prevent AI agents from evolving into potential insider threats.