Nik Kale, a specialist in enterprise AI platforms and security, argues that many organizations start with the agent runtime gateway as the primary control point, even though these gateways depend on identity and attribution layers that may not exist or may not be sufficiently mature. As a result, the gateway may verify the validity of a token and an API request, but it does not always know which agent executed the request, who authorized it, what task it was performing, or whether the request was part of a tool chain initiated by an untrusted component.
This issue is gaining practical importance as agent deployment expands. In June, the U.S. Cybersecurity and Infrastructure Security Agency (CISA) added a vulnerability in LiteLLM to its Known Exploited Vulnerabilities Catalog after observing its actual abuse. The vulnerability enabled command execution on the host through the gateway itself, and, when combined with a second vulnerability, it could be exploited without credentials. The source states that seven Common Vulnerabilities and Exposures (CVEs) were disclosed in the gateway within a single month.
Security Is a Chain of Trust, Not a Single Control Point
Kale proposes what he calls “trust-governed deployment,” meaning that no later layer should be considered operationally complete before the required tests for the preceding layers have been passed. Controls can be developed in parallel, but their activation in production should follow a clear sequence:
- Agent inventory and accountable ownership: Every production agent should have a known owner, a defined purpose, approved tools, and a lifecycle status.
- Independent identity and authorization context: The system should know the agent, its owner, and the user or entity on whose behalf the agent is performing the work.
- Short-lived, task-specific credentials: A compromised agent should not be able to access resources unrelated to its assigned task.
- Attributable measurement: The task should be reconstructible from the moment it begins through its final impact on other systems.
- Runtime enforcement: Policy decisions should be based on the agent’s identity, the authorizing entity, the task, and the action—not solely on token validity.
- Behavioral baseline and cross-system shutdown path: Security teams should be able to revoke the agent’s effective authority everywhere it has access.
Start with What Can Be Defined and Attributed
The first step, according to the proposed framework, is to catalog existing production agents across open-source frameworks, cloud services, software-as-a-service products, and developer tools. The record should include the agent’s owner, its responsibility, its lifecycle stage, permitted tools, data scopes, and credential sources. The absence of this inventory is not merely a documentation problem; it may consume part of the incident-response window in trying to identify an asset the organization should already know about.
The author emphasizes that an agent’s identity should not be buried inside developer code, a shared service account, or a user session. Knowing that the caller is an “agent” is not enough. The system must also record who authorized the work, the specific task, and the resources the agent needs to use. Identity identifies the actor, while authorization explains the entity under whose authority the agent is operating and the reason that authority was granted.
Reduce Permissions Before Analyzing Behavior
After identifying the agent, its capabilities should be restricted by time and according to the task, tools, and resources required for it. The source points to the possibility of using existing functions in identity and access management (IAM) systems, such as workload identity, token exchange, conditional access, and time-limited entitlements.
Kale cites Teleport’s 2026 study of 205 security leaders: organizations using overprivileged AI reported an incident rate of 76%, compared with 17% among organizations applying the principle of least privilege. According to his analysis, this indicates that access scope may be an earlier factor in the trust chain than context-aware runtime policy enforcement.
The principle the author presents is “monotonic delegation”: every transfer of responsibility must preserve or reduce authority and must not increase it. In the example of a financial-reconciliation agent, this means granting it permission to view a specific ledger rather than inheriting every system accessible to the employee who submitted the request.
When Does the Gateway Become Truly Useful?
A runtime gateway does not achieve its full value until there is a registered identity for the agent, explicit authorization context, scoped credentials, and attributable logs. At that point, it can assess whether the agent is authorized to perform a particular action, on behalf of a specific entity, within a defined task, and on a particular resource. The user’s token may be valid for granting the reconciliation agent write access, but the full context may show that the action falls outside the task’s scope.
The strictest controls should be directed at boundaries whose effects are difficult to reverse, such as payments, access-policy changes, deletion, production-environment modifications, and data exports. Behavioral baselines come later, once the agent’s activities can be distinguished and attributed; at that point, unusual tool use, unexpected access across data domains, or deviation from the task can be detected.
The shutdown path is not limited to disabling a single object in the identity directory. Full shutdown, as the source describes it, requires disabling the agent’s identity, revoking active and derived credentials, preventing tool execution, terminating running tasks, and isolating the workload containing the agent.
A 30-Day Testing Plan
The author does not propose replacing the existing identity-management program. If the identity provider does not treat agents as native entity types, organizations can begin with a trusted inventory linked to existing workload identities, then add agent and task identifiers as trusted execution contexts, use short-lived credentials, and include these identifiers in tool-invocation logs.
Practically, he proposes starting with ten production agents and documenting each one’s owner, purpose, tools, and credentials. Organizations should then test whether identity-management and logging systems distinguish the agent from the human or service that authorized the task, and reconstruct a completed task from beginning to end, including its downstream effects. The point where the chain breaks reveals the gap that should be addressed before adding a new runtime enforcement mechanism.
Editorial reading: The value of this framework lies not in proposing a new gateway, but in reordering the starting point. The facts cited about LiteLLM, together with the Teleport and Okta figures, support the importance of reducing permissions and attribution, but they do not by themselves prove that the proposed layer order is the only solution or that it is appropriate for every enterprise architecture. The material is also the author’s analysis rather than an official standard; therefore, applying it requires reviewing the details of the identity, logging, and shutdown systems already in place at each organization.