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In the era of AI-driven multi-agent systems, one of the most critical challenges is ensuring that each agent acts within the authorization limits of the original user. Without proper controls, a chain of delegations can silently expand the scope of permissions, exposing the organization to security risks. This problem, known as identity and privilege abuse (ASI03 in the OWASP Top 10 for agentic applications), demands robust solutions that combine OAuth 2.0 authentication and a layered authorization policy model. At Q2BSTUDIO, as a company specialized in custom applications, we understand the importance of designing secure architectures from the start.
One proven approach involves implementing three levels of control using Cedar, an open-source authorization policy language. The first layer verifies that the agent has the appropriate trust level (e.g., trust score 3 or higher), belongs to the correct namespace, and is in the production stage. The second layer limits the delegation depth — for example, a maximum of five hops — and checks that the requested tasks are within the registered capabilities of the target agent. The third layer, fundamental for least privilege, evaluates the original user: it requires an admin role, multi-factor authentication (MFA), and that the chain does not exceed a certain depth for high-risk operations, such as record deletion. This way, even if an agent has technical permissions, it cannot execute destructive actions without explicit authorization from the human user.
Integration of this model with AWS and Azure cloud services is natural. For example, in AWS, an MCP (Model Context Protocol) adapter is deployed as a Lambda function that cryptographically signs the user context to prevent tampering, and a Cedar evaluator that verifies the three layers sequentially, stopping at the first denial. All evaluation is logged in OCSF audit events, enabling monitoring with CloudWatch dashboards. For multi-account environments, the policy is centralized in a security account using AWS Verified Permissions and controlled with SCPs.
At Q2BSTUDIO, we combine our experience in artificial intelligence for businesses with advanced cybersecurity to design systems where AI agents operate autonomously but in a controlled manner. Our business intelligence and Power BI services help visualize authorization logs, while our custom software solutions integrate personalized policy layers. If you are building multi-agent architectures, we invite you to explore how we can help you implement least privilege controls without sacrificing operational agility.
