Enhancing Data Security with Dynamic Authorization:
A Guide to Mitigating
Vulnerabilities in LLMs
A Guide to Mitigating
Vulnerabilities in LLMs
Policy-Based Access Control: And Its Importance to
Protecting LLM
Policy Management for Agentic AI enables organizations to define granular policies that control what data AI agents can access, how they process it, and which actions they may take—ensuring that every AI-driven workflow abides by corporate and regulatory mandates.
In this whitepaper you will discover:
- Identity-aware control - Enforce access based on human and non-human identity (NHI).
- Dynamic, fine-grained policies - Apply adaptable controls to every AI Agent interaction with data, APIs and services.
- Centralized policy management - Manage and govern all policies in one unified, standardized interface.
- Seamless integration - With popular AI platforms and orchestration frameworks
- Zero Trust Alignment - Ensure AI operations align with enterprise security and compliance frameworks, by design.
- Auditability - Gain full visibility into AI decision chains, access attempts, and policy outcomes.
