Engaging with AI systems, particularly those trained on or processing user data, places your red team activities directly within the purview of data protection regulations like the GDPR. This appendix provides a practical reference for the core compliance documents you will encounter and may need to create. Understanding these documents is not just a legal formality; it is a prerequisite for scoping engagements, handling data responsibly, and identifying compliance-related vulnerabilities.
Disclaimer: This material is for educational purposes only and does not constitute legal advice. Always consult with qualified legal counsel for guidance on GDPR compliance and specific contractual obligations.
Key GDPR Documents in an AI Red Teaming Context
While the GDPR framework is extensive, three documents are central to most AI security engagements involving personal data. Your interaction with them will range from being a contributor, a signatory, or a critical reviewer.
1. Data Processing Agreement (DPA)
A DPA is a legally binding contract that governs the processing of personal data by one party (the processor) on behalf of another (the controller). In a typical AI red teaming engagement, your client is the data controller, and your organization is the data processor.
Why it matters to you: The DPA defines the rules of engagement for data handling. It sets the legal boundaries for what you can and cannot do with the client’s data. Violating the DPA is a breach of contract and a violation of the GDPR, carrying significant legal and financial risks. It is your primary shield and your rulebook.
A robust DPA for an AI red team engagement should explicitly address the following points:
| Clause | Description & Red Team Consideration |
|---|---|
| Subject Matter, Nature, and Purpose | Clearly defines the processing as “security testing of an AI model,” “vulnerability assessment,” or similar. This scope prevents data from being used for any other purpose. |
| Duration | Specifies the start and end dates of the processing, aligning with the engagement timeline. It must include post-engagement data deletion/return deadlines. |
| Types of Personal Data | Lists the specific categories of personal data you will access (e.g., user-generated text, images, IP addresses). Avoid vague terms; be as specific as possible. |
| Categories of Data Subjects | Identifies whose data is being processed (e.g., “end-users of the chatbot,” “customers in the training dataset”). |
| Technical and Organisational Measures (TOMs) | Details the security controls you (the processor) must implement. This includes encryption, access controls, and secure environments for handling test data. |
| Data Deletion and Return | Outlines the mandatory process for securely deleting or returning all personal data upon completion of the engagement. This is a critical exit criterion. |
| Sub-processors | Requires prior written consent from the controller before you can engage another party (a sub-processor) to process the data. |
2. Data Protection Impact Assessment (DPIA)
A DPIA is a risk assessment process required under GDPR for processing that is “likely to result in a high risk” to individuals’ rights and freedoms. Many AI systems, due to their potential for large-scale profiling, automated decision-making, or processing of sensitive data, necessitate a DPIA.
Why it matters to you: You will interact with a DPIA in two ways:
- As a reviewer: Requesting and analyzing the client’s DPIA for the target AI system is a goldmine of information. It reveals the system’s intended data flows, identified privacy risks, and the mitigation strategies the organization believes are effective. These mitigations are prime targets for testing.
- As a potential subject: The red teaming engagement itself, if it involves novel techniques or large-scale processing of sensitive production data, might trigger the need for a DPIA focused on the testing activities.
3. Record of Processing Activities (ROPA)
Required by Article 30 of GDPR, the ROPA is a detailed, internal log of an organization’s data processing activities. It’s essentially a data map, documenting what data is processed, why, for how long, and with whom it is shared.
Why it matters to you: The ROPA is a foundational document for understanding the target environment. Reviewing the ROPA entry for the AI system under test provides a structured overview of its data lifecycle. Discrepancies between the ROPA’s description and the system’s actual behavior are significant findings, indicating a potential GDPR compliance gap and a control failure.
For example, if the ROPA states that user inputs are deleted after 30 days, but your testing reveals they are retained indefinitely in a logging database, you have uncovered a critical compliance and security issue.
Pre-Engagement Compliance Checklist
Before beginning any hands-on testing that involves personal data, ensure you can answer the following questions. Your engagement lead should work with the client’s legal and data protection teams to clarify these points.
- Is a DPA fully executed between our organization and the client, specifically covering this red team engagement?
- Have we reviewed the DPA to understand the precise scope, data types, and security measures we are contractually obligated to follow?
- Have we requested and reviewed the DPIA for the target AI system to understand its known risks and mitigations?
- Does the information in the system’s ROPA align with the architecture and data flows we’ve observed during initial reconnaissance?
- Is there a clearly defined and agreed-upon process for the secure handling, transfer, and ultimate deletion of all personal data used during the test?
- Who is our designated point of contact at the client for data protection queries or in the event of a potential data breach during testing?
Treating these documents as integral parts of your red teaming methodology, rather than mere administrative hurdles, will elevate the quality of your findings and protect both your team and your client from significant regulatory risk.