Securing Agentic AI: A Framework for Enterprise Guardrails
A practical framework for implementing security controls in agentic AI systems, covering prompt injection defense, action authorization, and audit compliance.
As AI agents gain the ability to take actions — sending emails, modifying databases, triggering payments — security becomes existential, not optional. This white paper presents a practical framework for enterprise guardrails.
The Threat Model for Agentic AI
Traditional AI security focuses on model outputs (harmful content, bias). Agentic AI introduces action-oriented threats:
- Prompt injection: Malicious input causes unintended actions
- Privilege escalation: Agent accesses resources beyond its scope
- Data exfiltration: Agent sends sensitive data to unauthorized endpoints
- Action replay: Duplicated or repeated actions cause business harm
The GUARD Framework
We propose five security layers:
G — Gate: Input Validation
Every input to an agent passes through content filtering and injection detection before reaching the model. Known attack patterns are blocked at this layer.
U — Understand: Intent Classification
Before executing, classify the agent's intended actions. Map them to allowed action spaces per workflow configuration.
A — Authorize: Least Privilege
Agents operate with minimum necessary permissions. Database agents get read-only by default. Write access requires explicit workflow-level authorization with time-bounded tokens.
R — Review: Human Checkpoints
High-risk actions (financial transactions, external communications, data deletions) require human approval. Confidence-based escalation ensures humans review only uncertain decisions.
D — Document: Audit Trail
Every agent action is logged with: who triggered it, what context was provided, which model decided, what action was taken, and what the outcome was. This satisfies SOC 2, HIPAA, and GDPR audit requirements.
Implementation at Yanok
Our platform implements the GUARD framework natively. Every workflow inherits these security layers without additional configuration, while advanced users can customize thresholds and escalation rules per workflow step.
