AICM AtlasCSA AI Controls Matrix
DSP · Data Security and Privacy Lifecycle Management
DSP-02Cloud & AI Related

Secure Disposal

Specification

Apply industry accepted methods for the secure disposal of data from storage media such that data is not recoverable by any forensic means.

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 storage

Development

Guardrails

Evaluation

Evaluation

Deployment

AI Services supply chain

Delivery

Operations, Maintenance

Retirement

Data deletion, Model disposal

Ownership / SSRM

PI

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

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.

Orchestrated

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.

Application

Shared Application Provider-AI Customer (Shared AP-AIC)

The AP and AIC both share responsibility and accountability 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 offer and consume.

Implementation guidelines

[All Actors]
1. Dispose of cached inference results and log files the actor retains using approved secure-deletion methods.

2. Purge any user sessions, logs and outputs once the defined retention period expires for data the actor stores or processes.

3. Ensure business- or user-data deletion aligns with compliance obligations for the systems the actor controls.

4. Enable and execute secure-wipe / cryptographic-erasure lifecycle policies.

[Shared among: MP, CSP, OSP]
1. Delete training/validation data and embeddings post-use or repurpose for models the actor trains or fine-tunes.

Auditing guidelines

1. Examine the CSP’s procedures and technical requirements related to the secure disposal of data from storage media. Establish that this process and key controls comply with the CSP’s data privacy and security policy. Establish whether the CSP has documented the roles and responsibilities for this process.

2. Select a sample of disposal requests (if available) and assess whether they have followed the process through to completion. Confirm that all evidence was formally documented and recorded.

3. Examine measure(s) that evaluate(s) this process and determine if the measure(s) address(es) implementation of the process/control requirement(s) as stipulated.

4. Obtain and examine supporting documentation maintained as evidence of these metrics to determine if the office or individual responsible reviews the information and if identified issues were investigated and corrected. Examine related records to determine if the individual or office conducted any follow-ups on the deviations to verify they were corrected as intended.

5. Determine if the CSP has controls to evaluate third parties' secure data disposal methods from storage media.

6. Verify that industry-accepted methods for secure data disposal are defined and implemented, ensuring data is not recoverable by any forensic means.

7. Verify that data disposal techniques include secure deletion, overwriting, and physical destruction of storage media.

8. Verify compliance with relevant data protection laws and organizational policies throughout the data disposal process.

9. Verify the effectiveness of technical measures such as certified data wiping tools and secure destruction methods.

10. Verify that disposal methods align with industry standards (e.g., NIST SP 800-88) and specify appropriate techniques for different media types, such as cryptographic erasure for solid-state drives, degaussing or physical destruction for magnetic media, and secure overwriting where applicable.

3. Review evidence of implementation, including logs, certificates of destruction, or other documentation that confirms proper disposal of decommissioned media.

4. Assess whether disposal procedures address special handling requirements for high-capacity storage systems commonly used in AI workloads.

5. Verify that contracts with any third-party disposal services include appropriate security requirements and that certificates of destruction are obtained.

6. Examine staff training records on secure disposal procedures and confirm that personnel responsible for media handling have appropriate knowledge.

Standards mappings

ISO 42001Partial Gap
42001: A.4.3 Data Resources
42001: A.2.3 Alignment with other organizational policies
27001: A.7.10 - Storage media
27001: A.7.14 - Secure disposal or re-use of equipment
27001: A.8.10 - Information deletion
27002: 7.10 Secure reuse or disposal
27002: 7.14 - Secure disposal or re-use of equipment
27002: 8.10 - Information deletion
Addendum

ISO 42001 should cover 'ensuring data is not recoverable' the provision of the DSP-02 control.

EU AI ActPartial Gap
Article 10
Article 18
Addendum

Industry accepted methods specification for secure disposal. Article 18 covers documentation keeping but lacks specific secure disposal requirements.

NIST AI 600-1Partial Gap
GV-1.7-002
Addendum

NIST AI 600-1 does not mention the DSP-02 topic of "data is not recoverable by any forensic means."

BSI AIC4No Gap
PI-03
Addendum

N/A

AI-CAIQ questions (1)

DSP-02.1

Are industry-accepted methods applied for securely disposing of data from storage media so that it is not recoverable by any forensic means?