The role of intent in securing AI agents

By Itamar Apelblat, co-founder and CEO at Token Security

As AI agents move into production, security teams are confronting a familiar challenge: bringing autonomous systems under identity governance. But unlike scripts or services, AI agents authenticate, make decisions, and act on their own. Treating them as identities is necessary, but just part of the solution.

While identity-first security establishes accountability for AI agents through governance, audit, and guardrails that focuses on who owns the agent and what it has access to, it does not assess whether or not an action should be allowed.

Intent-based permissioning fills this gap.

The limits of identity-only controls

Traditional IAM models assume that once an identity is authenticated and assigned a role, its behavior will remain within predictable boundaries. This generally holds for humans with defined job functions and for services designed to perform narrow, deterministic tasks.

AI agents behave differently. They plan, adapt, chain actions, and respond to changing inputs at runtime. An agent may begin with a defined objective, investigating an outage, analyzing cost anomalies, or responding to a support request, but pivot as they gather new information and start to connect to out-of-scope services. When access decisions are made solely on identity and static roles, permissions granted for one purpose often remain active even as the agent’s behavior evolves.

This leads to familiar but amplified risks: agents inheriting creator or operator privileges for convenience, permissions persisting long after the original task ends, and security teams discovering problematic access only after something goes wrong. Identity-first controls make activity visible, but visibility alone does not prevent misuse or privilege drift.

Intent as the missing cog

Intent-based permissioning introduces a missing element into access management for AI agents by explicitly scoping their defined purpose. Instead of granting access indefinitely based on identity alone, permissions are activated conditionally, when an agent’s declared intent and runtime context align with pre-approved parameters.

Intent captures what an agent is trying to accomplish, under what conditions, and within what scope. This matters because many AI agent tasks share overlapping technical actions while differing fundamentally in business purpose. Two agents may interact with the same cloud APIs, but one may be authorized to observe while another is permitted to change state. Without intent, both can end up with the same broad access.

By anchoring permissions to agent intent, security teams can constrain access even when underlying actions look similar. Access becomes purpose-bound rather than convenience-driven.

How identity and intent work together

An identity-first, intent-aware model combines three signals: identity, intent, and context. Identity establishes what the agent is and how it is governed. Intent defines why it is acting at a given moment. Context determines when access should be allowed, factoring in environment, data sensitivity, system state, and timing.

When an agent’s intent is properly defined, least-privilege policies can be enforced ensuring that the agent only has the access it needs to execute its purpose. If the agent pivots to an unexpected task or operates outside defined constraints, access can be restricted automatically. This prevents the quiet accumulation of privilege that often occurs as agents are reused, repurposed, or modified over time.

Governance Becomes Scalable Again

One of the most practical benefits of intent-based permissioning is how it reshapes governance. Reviewing thousands of low-level permissions for AI agents is neither scalable nor meaningful for security, risk, and compliance teams. Policy reviews quickly devolve into technical exercises disconnected from business objectives.

Intent-based models change the unit of governance. Instead of auditing individual API calls, security, risk, and compliance teams review intent profiles mapped to identities. Attestations answer higher-level questions: Is this agent authorized to perform this class of work? Are constraints appropriate for the risk involved? Are deviations detected and handled? This makes governance traceable, defensible, and aligned with how organizations actually manage risk.

Detecting Privilege Drift Before it’s Too Late

An agent may start a task within bounds, but adapt its behavior based on prompts, context injection, or tool availability. Without continuous validation, permissions granted at the start of execution may no longer be appropriate minutes later. This drift AI introduces unintended  operational risk.

Intent-based permissioning enables runtime checks that compare observed behavior against declared purpose. When discrepancies surface, such as unexpected write operations, cross-domain access, or prolonged privilege use, controls can intervene early to right-size agent privileges. This shifts access control from a static gate to a dynamic safeguard.

Practical Steps Forward

Intent-based security doesn’t require a sweeping IAM reset; meaningful progress starts with a few focused changes to how AI agents are defined, governed, and monitored:

• Treat AI agents as first-class identities, with clear ownership, lifecycle states, and audit requirements equivalent to human and service accounts.
• Require intent profiles for every agent, documenting approved objectives, operational boundaries, and conditions under which access may be activated.
• Bind privilege activation to identity, intent, and context, rather than granting standing roles that persist beyond a specific task.
• Continuously validate runtime access, detecting drift between declared intent and observed actions and triggering access re-evaluation when necessary.

Without intent-based permissioning to define what an agent is actually allowed to do, and why, identity-first controls aren’t enough to scale AI safely or maintain accountability.

About the author

Itamar Apelblat, co-founder and CEO of Token Security, has more than 15 years of technical and leadership experience in cybersecurity. A second-time entrepreneur, he previously co-founded a successful fintech startup and served as an officer and R&D group manager in Israel’s elite Unit 8200, where he led advanced cybersecurity initiatives.

Article Topics

access control  |  AI agents  |  identity access management (IAM)  |  identity security  |  identity verification  |  non-human identities