AI Security, Model Protection and Adversarial Risk Management Assessment

Protiviti’s AI Security Program is a strategic professional services offering designed to help organizations secure artificial intelligence (AI) systems, protect critical data assets, and safeguard models against emerging cybersecurity, privacy, and adversarial AI threats. Through expert-led assessments, secure AI architecture design, red-team and adversarial testing, and AI-specific control frameworks, Protiviti helps organizations ensure that AI-enabled platforms and models are resilient, trustworthy, and protected against evolving risk. Our program strengthens enterprise defenses by embedding robust security controls across the entire AI lifecycle—ensuring AI innovation accelerates without compromising confidentiality, integrity, or availability. This offering supports organizations deploying AI in cloud, hybrid, and on‑premises environments, including AI workloads hosted on AWS.

Overview

Protiviti’s AI Security Program equips organizations with the tools, controls, and strategies required to secure AI systems from rapidly evolving cyber and adversarial threats. The program delivers an integrated approach to protecting: • Data ingestion and preprocessing pipelines • AI and machine learning training environments • Model repositories and inference services • AI-enabled applications and APIs

By leveraging AI-specific threat modeling, adversarial testing techniques, secure architecture principles, and continuous monitoring practices, Protiviti helps organizations prevent: • Model manipulation and tampering • Data poisoning and data leakage • Model extraction and inversion attacks • Prompt injection and unauthorized usage • Privilege abuse and access control failures

Our approach integrates seamlessly with existing cybersecurity, cloud security, and data protection frameworks, enabling organizations to adopt and scale AI securely without introducing unmanaged risk. As a result, clients gain confidence that their AI capabilities are hardened against attacks, aligned with enterprise security objectives, and prepared for emerging regulatory and governance expectations.