27.2.5 Partnership agreements

Unlike a client engagement or a subcontractor relationship, a partnership implies a collaborative effort toward a shared objective. It moves beyond a simple fee-for-service model into territory involving shared risks, mutual benefits, and often, co-creation of intellectual property. A robust partnership agreement is not just a legal formality; it is the operational blueprint for this collaboration, essential for navigating the complex landscape of AI security.

Defining the Partnership Landscape in AI Red Teaming

Partnerships in this field are diverse, each requiring a tailored legal framework. Your agreement’s focus will shift depending on the nature of the collaboration. Common partnership structures include:

• Technology Partnerships: Collaborating with MLOps platforms, cloud providers, or security tool vendors. The goal is often to integrate your red teaming methodologies into their platforms or to co-develop specialized assessment tools.
• Research & Development (R&D) Partnerships: Working with academic institutions or other specialized research firms. These partnerships focus on discovering novel vulnerabilities, developing new attack techniques, and publishing findings.
• Channel or Go-to-Market (GTM) Partnerships: Teaming up with larger consultancies or Managed Security Service Providers (MSSPs) who resell or bundle your AI red teaming services with their own offerings.
• Joint Ventures (JV): A formal business arrangement where you and another entity create a new, separate entity to tackle a specific large-scale project or market opportunity, sharing in the profits, losses, and control.

Critical Clauses for AI Red Teaming Partnerships

While standard contractual clauses (governing law, force majeure, etc.) are necessary, several areas demand specific and meticulous attention in the context of AI security.

1. Scope of Work and Contribution

This is more than a task list. It must clearly delineate responsibilities, resources, and personnel contributed by each partner. Ambiguity here is a primary source of conflict.

• Who provides the target AI system or environment?
• Who is responsible for obtaining client permissions and safe harbor?
• Which partner’s methodology will be used, or will a hybrid be developed?
• Who has final authority on the test plan and rules of engagement?

2. Intellectual Property (IP) Rights

This is arguably the most critical and contentious clause in any AI-related partnership. You must define ownership for three categories of IP:

• Background IP: The proprietary tools, techniques, and data each partner brings into the relationship. This must be clearly identified and protected.
• Foreground IP: New discoveries, tools, or methodologies created jointly during the partnership. Will ownership be joint? Will one partner have an exclusive license?
• Third-Party IP: Use of open-source models, datasets, or tools. The agreement must specify compliance with their respective licenses.

// Pseudocode for a Foreground IP clause
FUNCTION determine_ip_ownership(discovery):
    IF discovery.origin IN PartnerA.background_ip:
        RETURN { owner: 'PartnerA', license_to_partnerB: 'project_specific' }
    ELSE IF discovery.origin IN PartnerB.background_ip:
        RETURN { owner: 'PartnerB', license_to_partnerA: 'project_specific' }
    ELSE IF discovery.is_jointly_developed:
        // Define the terms of joint ownership clearly
        RETURN { owner: 'Joint', usage_rights: 'unrestricted_both_parties' }
    ELSE:
        // Default case, e.g., belongs to the discovering party
        RETURN { owner: discovery.discoverer }
END FUNCTION
            

3. Data Governance and Confidentiality

Partners will likely be exposed to highly sensitive information, including client data, proprietary model weights, and internal security postures. This section must go beyond a standard NDA.

• Data Handling Protocols: Specify encryption standards, access controls, and secure transfer methods for all shared data.
• Data Segregation: How will one client’s data be kept separate from another’s, especially within a shared research environment?
• Data Sovereignty: Address cross-border data transfer restrictions (e.g., GDPR, CCPA) if partners are in different jurisdictions.
• Breach Notification: Define a clear, time-bound process for notifying the other partner in the event of a security incident affecting shared data.

4. Liability and Indemnification

Red teaming activities carry inherent risks. The agreement must specify who is financially responsible if something goes wrong.

• Limitations of Liability: Cap the financial liability of each partner, often tied to the value of the contract or insurance coverage.
• Indemnification: One partner agrees to cover the losses of the other for specific events. For example, Partner A indemnifies Partner B against any claims arising from a breach of Partner A’s background IP warranty.
• Insurance: Require both parties to maintain adequate professional liability (Errors & Omissions) and cyber insurance, naming the other partner as an additional insured where appropriate.

Partnership Type vs. Key Contractual Focus

The emphasis of your agreement should adapt to the partnership’s nature. A misaligned contract creates friction and risk.