Zendesk Assume Identity
You use zendesk assume identity to act as another user in your support workspace. Admins or apps send requests or view screens from that target user's view. Teams use this tool to test routing rules or send tickets for customers. Still, broad permissions let one admin or token change data across every user account. How the zendesk assume identity workflow works The native workflow works in two main ways across the support platform. First, an admin can switch their view inside the web app to d
Identity and Access Management (IAM): the complete guide
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You use zendesk assume identity to act as another user in your support workspace. Admins or apps send requests or view screens from that target user's view. Teams use this tool to test routing rules or send tickets for customers. Still, broad permissions let one admin or token change data across every user account.
How the zendesk assume identity workflow works
The native workflow works in two main ways across the support platform. First, an admin can switch their view inside the web app to debug issues. This lets the admin see exact ticket queues, macros, and views for one agent. The admin fixes broken workflows fast without asking the agent for their login password.
Second, custom apps can act as specific users when they send API requests. An integration uses a high-level admin credential and sets a target user header. The platform then processes that request as if the target user sent it. This helps when a background job must create tickets or post comments for end users.
Both methods rely on high-level admin roles to grant this wide power. Only top-level admins or tokens tied to admin accounts can switch identities this way. The platform checks the main account role before it allows the identity switch. Once approved, the session or API call runs with the target user's rights.
What native role switching solves and what it misses
Native role switching solves a big problem for support ops and engineering teams. You never need to share passwords or reset agent accounts just to test views. Automated scripts can also assign ticket actions to the right person in the thread. This keeps ticket history clean for customers and agents who read the replies.
Still, this setup leaves a wide gap in how you control live actions. The native permission only checks who logs in at the start of the session. It does not check what individual API calls or commands do in flight. An admin or script with this role can act as any user at any time.
Identity and Access Management (IAM): architecture patterns and best practices
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If an integration token leaks, an attacker can act as any agent in the system. They can pull ticket lists that hold emails, phone numbers, and card numbers. Basic role checks cannot block bulk reads or rewrite sensitive fields in the results. You also lack a clear way to require peer approval for one risky action.
How to tighten control over shared support credentials
Start by trimming the number of people who hold top admin roles in the tool. Give daily support leads narrower roles that only manage tickets and basic user groups. Next, move automated scripts away from full admin keys whenever the task allows it. Create dedicated service accounts with restricted roles for simple ticket creation jobs.
You should also audit your system logs every week to spot strange identity switches. Look for admin accounts that switch views outside of normal support shift hours. Track which API tokens send headers to act as other agents on the team. Finally, put runtime checks in place to inspect every request and mask sensitive data.
Add runtime guardrails and masking beside your databases and APIs
Login rules, role grants, and CI checks govern who connects to your stack. Yet any allowed script, engineer, or AI agent still runs commands with the full scope of its role. For workloads on Postgres, MySQL, SQL Server, MongoDB, ClickHouse, Kubernetes, SSH, or internal HTTP services, hoop.dev sits beside the service as an open-source proxy, a sidecar for your database or API.
Before a query runs, hoop.dev guardrails check the statement against your rules. An AI Analyzer you configure can score intent or hold risky calls for human review. Next, hoop.dev data masking rewrites sensitive fields in responses, and each verdict is logged per listener. Explore the MIT-licensed project on GitHub.
Frequently asked questions
Can regular support agents act as other agents in the workspace?
No, standard support agents cannot switch their identity to view another agent's screen. The platform restricts this feature to accounts that hold high-level admin roles. This stops normal agents from reading private ticket queues outside their own group.
How do API requests act on behalf of another user?
A script authenticates with an admin credential and passes the target user in the request. The platform reads that target value and logs the action under that user's profile. You must protect that admin credential since it can act as any user.
Does acting as a user hide sensitive ticket fields by default?
No, the session shows everything that the target user has permission to read. If that user can view emails, phone numbers, or national IDs, the caller gets them too. You need a separate data masking rule to rewrite matched fields in the results.