UEM-12Cloud & AI Related

Remote Locate

Specification

Enable remote geo-location capabilities for all managed mobile endpoints, according to all applicable laws and regulations.

Threat coverage

Model manipulation

Data poisoning

Sensitive data disclosure

Model theft

Model/Service Failure

Insecure supply chain

Insecure apps/plugins

Denial of Service

Loss of governance

Architectural relevance

Physical infrastructure

Network

Compute

Storage

Application

Data

Lifecycle

Preparation

Data collection

Development

Design, Training, Guardrails, Supply Chain

Evaluation

Evaluation, Validation/Red Teaming, Re-evaluation

Deployment

AI applications

Delivery

Continuous monitoring

Retirement

Not applicable

Ownership / SSRM

Shared Cloud Service Provider-Model Provider (Shared CSP-MP)

The CSP and MP are jointly responsible and accountable for the design, development, implementation, and enforcement of the control to mitigate security, privacy, or compliance risks associated with Large Language Model (LLM)/GenAI technologies in the context of the services or products they develop and offer.

Model

Owned by the Model Provider (MP)

The model provider (MP) designs, develops, and implements the control as part of their services or products to mitigate security, privacy, or compliance risks associated with the Large Language Model (LLM). Model Providers are entities that develop, train, and distribute foundational and fine-tuned AI models for various applications. They create the underlying AI capabilities that other actors build upon. Model Providers are responsible for model architecture, training methodologies, performance characteristics, and documentation of capabilities and limitations. They operate at the foundation layer of the AI stack and may provide direct API access to their models. Examples: OpenAI (GPT, DALL-E, Whisper), Anthropic(Claude), Google(Gemini), Meta(Llama), as well as any customized model.

Orchestrated

Shared Model Provider-Orchestrated Service Provider (Shared MP-OSP)

The MP and OSP are jointly responsible and accountable for the design, development, implementation, and enforcement of the control to mitigate security, privacy, or compliance risks associated with Large Language Model (LLM)/GenAI technologies in the context of the services or products they develop and offer.

Application

Shared Orchestrated Service Provider-Application Provider (Shared OSP-AP)

The OSP and AP are jointly responsible and accountable for the design, development, implementation, and enforcement of the control to mitigate security, privacy, or compliance risks associated with Large Language Model (LLM)/GenAI technologies in the context of the services or products they develop and offer.

Implementation guidelines

[Applicable to all actors except CSP]  
1. Enable geo-location tracking via UEM for all mobile endpoints (laptops, tablets, smartphones) used by MP, OSP, AP, and AIC in the AI supply chain, ensuring that each organization’s device can report its last known location if lost or stolen.

2. Develop a shared procedure for utilizing remote locate during security incidents, for example, clearly define who within each stakeholder’s team is authorized to trigger a “find device” command and under what circumstances, and agree on how location information will be shared or handed off if a device from one party is lost in another’s facility or jurisdiction.

3. Protect location data by restricting access to authorized security personnel across the organizations; all stakeholders should mutually ensure that any collected device location info is used solely for recovery/security purposes and handled in compliance with privacy expectations.

4. Periodically test the remote locate function on a sample of endpoints from each stakeholder (e.g., as part of an annual drill) to confirm that devices report accurate location data and that all teams know how to initiate and respond to a device location query in practice.

Auditing guidelines

1. Verify that the CSP has a documented process for remote tracking of endpoint devices, including BYOD and corporate devices, under all service delivery models.

2. Confirm that the policy mandates inventory of all endpoints, use of GPS or network-based tracking, and immediate alerts for devices going offline or untraceable.

3. Review whether remote tracking processes are integrated with incident response workflows and include well-defined escalation paths for lost or stolen devices.

4. Inspect implementation evidence such as tracking logs, inventory records, alert configurations, and periodic testing documentation of remote wipe functionality.

5. Verify that the CSP routinely tests the effectiveness of remote locate and wipe procedures across different endpoint types and maintains records of these tests.

From CCM:
1. Examine the organization's remote geo-location for managed mobile endpoints policy.
2. Determine if such controls are in place.

Standards mappings

ISO 42001Partial Gap

No Mapping for ISO 42001
ISO 27001 A.8.12

Addendum

No ISO 42001 controls support UEM-12 topic of geolocation, especially not configured on endpoint devices

EU AI ActFull Gap

No Mapping

Addendum

Include a technical annex specifying that remote geo-location must be implemented for endpoints handling high-risk AI data.

NIST AI 600-1Full Gap

No Mapping

Addendum

No NIST AI 600-1 control supports the UEM-12 topic of geolocation on endpoint devices. Cover mobile devices, Remote wipe/location capabilities, Endpoint management or tracking.

BSI AIC4No Gap

C4 SR-06
C5 AM-05

Addendum

N/A

AI-CAIQ questions (1)

UEM-12.1

Are remote geolocation capabilities enabled for all managed mobile endpoints, according to all applicable laws and regulations?