6 Strategic MSSP Capabilities for Securing Enterprise AI
A Guide for Security Leaders: Offensive Security for the AI Attack Surface
As AI adoption accelerates, most security teams are left playing catch-up. AI is creating new attack surfaces that most MSSPs aren’t built to test or defend. As LLMs, ML pipelines, inference APIs, and cloud‑hosted models become central to operations, adversaries are shifting to exploit how these systems behave, not just the underlying infrastructure.
97% of AI-related breaches involve insufficient access controls, and 64% of organizations lack full visibility into their AI risks.*
This guide shows offensive security and red teams how to leverage their MSSP relationships to gain the AI‑specific visibility, adversarial validation, and real‑time response capabilities required to securely operate and continuously pressure‑test AI systems.
Inside, you’ll find:
AI‑specific penetration testing and adversarial ML evaluation (evasion, inversion, extraction, poisoning)
Offensive testing for cloud AI platforms (SageMaker, Azure ML, GCP AI) and model‑hosting infrastructure
Pre‑production offensive validation of AI pipelines, containers, and IaC in CI/CD
Purple‑team simulations for prompt injection, model manipulation, and output tampering
Continuous penetration testing and red‑team integration inside the MSSP operating model for real‑time AI defense
If your AI strategy is accelerating, this guide equips your team to align innovation with assurance—by validating, hardening, and continuously testing the AI systems your business depends on.
