Dynamically securing operations in agentic artificial intelligence models
Disclosed embodiments relate to systems and methods for controlling access to a resource by an artificial intelligence orchestration system. Example techniques include receiving, at an authorization component integrated with the orchestration system, a request to perform an operation, the request being initiated by an autonomous component; deriving, from the request and data associated with an environmental state, information representing at least one of a purpose and a context of the operation; dynamically evaluating the information, to identify one or more least-privileged permissions required for the operation; issuing an authorization artifact that embeds an ephemeral permission set scoped to the least-privileged permissions; and enabling the operation to execute using only the ephemeral permission set.
1 . A non-transitory computer readable medium including instructions that, when executed by at least one processor, cause the at least one processor to perform operations for controlling access to a resource by an artificial intelligence orchestration system, the operations comprising:
receiving, at an authorization component integrated with the orchestration system, a request to perform an operation, the request being initiated by an autonomous component;
deriving, from the request and data associated with an environmental state, information representing at least one of a purpose and a context of the operation;
dynamically evaluating the information to identify one or more least-privileged permissions required for the operation;
issuing an authorization artifact that embeds an ephemeral permission set scoped to the least-privileged permissions; and
enabling the operation to execute using the ephemeral permission set.
2 . The non-transitory computer readable medium of claim 1 , wherein deriving the information representing the purpose comprises applying at least one machine-learning model.
3 . The non-transitory computer readable medium of claim 1 , wherein the context of the operation comprises one or more attributes selected from: an input to a machine learning model associated with the request, metadata associated with the autonomous component, an identity of a user associated with the autonomous component, a role of a user associated with the autonomous component, an identifier of a tool associated with the orchestration system, a model chain step, an identifier associated with a target resource, a data classification, a time, a location, a device posture, a historical operation, past operations performed by the autonomous components, past operations performed by an identity associated with a user associated with the autonomous components, and a workload attestation.
4 . The non-transitory computer readable medium of claim 1 , wherein the authorization artifact encodes at least one of a time limit, a usage count, or a signature that binds at least one of a purpose, a scope, an expiry, a session identifier, a prompt digest, or a reasoning plan identifier.
5 . The non-transitory computer readable medium of claim 1 , wherein evaluating the information further comprises initiating a human approval workflow for an action.
6 . The non-transitory computer readable medium of claim 1 , wherein causing the operation to execute comprises constraining at least one of: a prompt scope, a target selection, or an environment configuration.
7 . The non-transitory computer readable medium of claim 1 , wherein causing the operation to execute comprises provisioning a temporary credential that embodies the ephemeral permission set.
8 . The non-transitory computer readable medium of claim 1 , wherein the operations further comprise invalidating the authorization artifact upon completion of the operation or upon satisfaction of a revocation condition.
9 . The non-transitory computer readable medium of claim 8 , wherein invalidating the authorization artifact comprises revoking a temporary credential and clearing secret material from memory.
10 . The non-transitory computer readable medium of claim 1 , wherein the operations further comprise recording one or more audit records associated with the operation.
11 . The non-transitory computer readable medium of claim 10 , wherein recording the audit comprises binding the operation to at least one of a workflow identifier or a step identifier, and wherein the authorization component operates as a proxy or wrapper for an agentic artificial intelligence tool framework.
12 . The non-transitory computer readable medium of claim 1 , wherein the evaluating further includes analyzing one or more rules pre-defined by an entity associated with a customer.
13 . The non-transitory computer readable medium of claim 1 , wherein evaluating the information comprises utilizing a policy engine coupled to the orchestration system.
14 . The non-transitory computer readable medium of claim 1 , wherein evaluating the information comprises applying at least one machine-learning model.
15 . The non-transitory computer readable medium of claim 1 , wherein the information represents a context of the operation and wherein deriving the information comprises obtaining attributes selected from: a user identity, a user role, historical requests of the user, a running environment, an active task associated with the operation, a name and version of a tool associated with the orchestration system, document labels, a time, a geofence, a device posture, past operations performed by the autonomous component, past operations performed by an identity of a user associated with the autonomous components, and a workload attestation.
16 . The non-transitory computer readable medium of claim 1 , wherein the authorization artifact encodes a purpose binding comprising at least one of: a workflow identifier, a step identifier, a data classification, or a requested scope, and wherein the evaluation requires the purpose to match a permitted value.
17 . The non-transitory computer readable medium of claim 1 , wherein the operations further comprise:
identifying an input to a machine learning model associated with the request;
dynamically evaluating the input to determine a first distance metric of the input relative to a mission associated with the autonomous component; and
performing a first validation of the operation based on the first metric.
18 . The non-transitory computer readable medium of claim 1 , wherein the operations further comprise:
identifying an execution plan associated with the operation, the execution plan being generated using a machine learning component;
identifying at least one reference execution plan associated with the operation;
dynamically evaluating the execution plan to determine a second distance metric of the execution plan relative to the at least one reference execution plan; and
performing a second validation of the operation based on the second distance metric.
19 . A computer-implemented method for controlling access to a resource by an artificial intelligence orchestration system, the method comprising:
receiving, at an authorization component integrated with the orchestration system, a request to perform an operation, the request being initiated by an autonomous component;
deriving, from the request and data associated with an environmental state, information representing at least one of a purpose and a context of the operation;
dynamically evaluating the information, to identify one or more least-privileged permissions required for the operation;
issuing an authorization artifact that embeds an ephemeral permission set scoped to the least-privileged permissions; and
causing the operation to execute using the ephemeral permission set.
20 . The method of claim 19 , wherein at least one of deriving the information or dynamically evaluating the information comprises applying at least one machine-learning model.
21 . The method of claim 20 , wherein the model incorporates historical interaction data associated with an initiator of the operation.
22 . The method of claim 19 , wherein the authorization artifact further embeds at least one of an indication of the request to perform an operation or a sequence of actions associated with causing the operation to execute.
23 . A non-transitory computer readable medium including instructions that, when executed by at least one processor, cause the at least one processor to perform operations for controlling access to a resource by an artificial intelligence orchestration system, the operations comprising:
receiving, at an authorization component integrated with the orchestration system, a request to perform an operation, the request being initiated by an autonomous component;
deriving, from the request and data associated with an environmental state, information representing at least one of a purpose and a context of the operation;
dynamically evaluating the information, to identify one or more parameters for adapting the operation;
modifying the request based on the parameters to generate a modified request; and
causing the operation to execute the modified request.