How should I scope OAuth tokens and authorization for AI agent tool calls?

To scope OAuth tokens and authorization for AI agent tool calls, implement intent-aware authorization, which binds a structured intent scope to a session token and continuously enforces it against every tool call for the duration of the session. This approach extends existing IAM infrastructure with an "intent plane" to address the authorization gap in agentic systems.

Here are concrete controls for scoping OAuth tokens and authorization:

• Discover and Inventory Agents: Before defining policies, identify all AI agents, including shadow AI agents, by scanning networks, capturing browser activity, and integrating with platforms like LangChain or cloud AI services. This addresses the NIST AI RMF function of Govern, specifically the "Map" category, by understanding the AI system's context and capabilities.
• Use Session-Scoped and Short-Lived Tokens: Store OAuth tokens in a secure vault at session creation time and use a dedicated proxy for external service calls. The proxy should hold only a session-scoped token and fetch the real credential from the vault when a tool is called, ensuring the agent loop and sandbox never directly handle the real credential. When calls cross trust boundaries, issue short-lived, cryptographically signed transaction tokens that carry the user's verified identity, agent chain, and original declared intent. This helps mitigate OWASP LLM Top 10 risk LLM07: Insecure Plugin Design and LLM08: Excessive Agency.
• Implement Intent-Aware Authorization: Parse natural language requests into structured intent objects, map these to fine-grained authorization tuples, and enforce them at every tool invocation. This means an agent's actions are continuously validated against the purpose defined at the start of the session, preventing privilege drift. This aligns with the NIST AI RMF function of Govern, specifically the "Measure" category, by continuously monitoring and evaluating the AI system's performance and risks.
• Enforce Policies at the Tool-Call Gateway: Intercept every tool call and MCP server invocation at a tool gateway and verify it against the authorization engine in real time. This enforcement point should use an "IBAC Judge" to extract original intent, compare the current hop's reason against that intent, and emit a drift score, coupled with a deterministic policy floor for hard constraints. This directly addresses OWASP LLM Top 10 risk LLM08: Excessive Agency by controlling what actions an agent can take.
• Baseline and Monitor Agent Behavior: Establish baselines for normal tool call patterns, data access scopes, and outbound traffic volumes for each agent. Continuously monitor agent behavior and alert on statistically significant deviations, especially for agents that combine access to private data, exposure to untrusted content, and external communication capabilities. This aligns with the NIST AI RMF function of Monitor, specifically the "Respond" category, by detecting and responding to anomalies.
• Secure Non-Human Identities: Maintain a complete inventory of all non-human identities (e.g., service accounts, API keys, OAuth tokens) across the agentic ecosystem and continuously monitor their behavior against established baselines, flagging deviations that indicate compromise, abuse, or misconfiguration. This addresses the NIST AI RMF function of Govern, specifically the "Map" category, by understanding the AI system's context and capabilities.