Enhancing Trust in AI: An Overview of AI Certification with the Cloud Security Alliance (CSA)

Overview of CSA STAR

The CSA STAR program serves as a foundation for cloud security evaluations. It provides a public registry where cloud providers can document their security and privacy controls, aiding organizations in decision-making. With more than 3,400 assessments globally, it is based on the Cloud Controls Matrix (CCM), a comprehensive set of controls for cloud services. The program includes Level 1 self-assessments and Level 2 third-party certifications.

Introducing CSA STAR for AI

CSA STAR for AI builds on this foundation as part of the CSA's AI Safety Initiative, focusing on compliance and safety in AI, particularly generative AI (GenAI). It enables AI developers, cloud providers, and enterprises to assess and validate the trustworthiness of their AI offerings, addressing risks such as data leakage and ethical considerations.

The program comprises three main components:

• AI Trustworthy Pledge: A commitment to high-level principles on AI safety and responsibility, granting a digital badge and public recognition.
• AI Controls Matrix (AICM): A vendor-neutral framework with 243 control objectives across 18 domains for secure AI development, deployment, and management. It aligns with standards including ISO 42001 and NIST AI RMF.
• Trusted AI Safety Knowledge Certification Program: Scheduled for launch in 2025, this program will provide professionals with expertise in managing AI risks.

Key Differences from the Original CSA STAR

While the original CSA STAR focuses on cloud security via the CCM, CSA STAR for AI adapts to AI-specific challenges, including societal impacts like system over-reliance, ethical issues, and GenAI threats such as hallucinations.

Notable distinctions include:

• Specialized Controls: The AICM features 37 AI-specific controls, 183 overlapping with cloud controls, and 22 cloud-only, covering the AI value chain beyond traditional cloud scopes.
• Emphasis on Trust Attributes: It prioritizes transparency, accountability, explainability, and safety, incorporating elements like the AI Trustworthy Pledge.
• Audit Enhancements: Introduces risk-based audits, continuous monitoring, and GenAI guidelines, differing from the original's point-in-time assessments.
• Broader Scope: Extends to AI developers and enterprise users, addressing ecosystem-wide issues like shadow AI and regulatory variations.

This evolution maintains the core structure while tailoring it to AI's unique demands.

Requirements for CSA STAR for AI Certification

The certification process is structured to accommodate varying organizational maturities:

1. Commit to the Pledge: Adopt the AI Trustworthy Pledge to qualify for Level 1 and receive recognition.
2. Level 1 Self-Assessment: Evaluate AI systems using the AI Consensus Assessment Initiative Questionnaire (AI-CAIQ) against the AICM, covering domains such as governance and security.
3. Level 2 Third-Party Certification: Engage an independent audit to verify compliance with the 243 AICM controls while integrating the ISO 27001 and/or ISO 42001 standards.
4. Continuous Improvement: Utilize auditing guidelines and the forthcoming certification program for ongoing risk management.

This approach helps mitigate AI-specific risks, including privacy concerns and biases, facilitating secure deployment.

Coalfire Certification

CSA STAR for AI supports organizations in building trust, managing risks, and advancing innovation amid regulations like the EU AI Act. It positions adopters as leaders in responsible AI practices.

As an ANAB accredited certification body, Coalfire Certification will offer CSA STAR for AI assessment services as part of our global assurance and ISO certification practice. If you are ready to move your organization and AI services into the next generation of security and compliance, contact Coalfire today!