> For the complete documentation index, see [llms.txt](https://cortex-docs.paloaltonetworks.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://cortex-docs.paloaltonetworks.com/cortex-agentix/learn-about-cortex-agentix/agentic-ai-in-cortex-agentix/agentic-assistant-security.md). # Agentic Assistant security Learn how the Agentic Assistant protects data through RBAC, approvals, regional processing, and action auditing in Cortex AgentiX, The Agentic Assistant is built on responsible AI principles to ensure its use is safe, fair, and trustworthy. We design our AI to be transparent about its actions, accountable for its decisions, and fair in its operations, avoiding biases. The following describes how the Agentic Assistant protects sensitive data and gives you control and understanding over its automated actions. ### Access control and permissions **User roles and RBAC options** Instance and Account admins control user access to the Cortex Agentic Assistant. Cortex AgentiX uses role-based access control (RBAC) to govern chat access and permissions to view, create, edit, delete, enable, and disable agents and actions in the Agentic Assistant Hub. **Action Execution Scope** Agents can only use assigned actions. Execution is limited to the user's existing permissions in your Cortex AgentiX tenant. If a required integration is inactive, its commands and actions that wrap them do not work. To perform actions in Slack, your Slack email must match your Cortex AgentiX user email. This ensures the system follows your assigned RBAC permissions. The system blocks actions when you lack the required permissions. ### Data security and control **How sensitive data is protected** Data is hosted and encrypted by default in a dedicated Google Cloud Platform (GCP) project. Your IAM permissions isolate and protect the data. Google's multi-tenant architecture enforces strict data separation between customers. **User approval for sensitive actions** Sensitive actions require explicit user approval before execution. They never run automatically. This gives you final control over critical or data-modifying steps. **Data user policy** Prompts and outputs are processed only to generate the immediate response. They are not collected for model training or shared with third parties. **Data residency** All prompts and responses stay within the region's compute boundary. ### Transparency **How the Cortex Agentic Assistant maintains transparency** You can review how the agent reaches an answer. Click the down arrow next to **Plan** to view the interpreted input, planned steps, and actions used. You can also view JSON artifacts created when data was retrieved or an object was created. All agent actions are saved in an audit dataset. You can see which agent ran each action and which user invoked it. Chat logs and Slack-initiated actions are stored in the Cortex AgentiX database. They include a Slack prefix or metadata tag. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://cortex-docs.paloaltonetworks.com/cortex-agentix/learn-about-cortex-agentix/agentic-ai-in-cortex-agentix/agentic-assistant-security.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.