Validating AI Security Controls Through Adversary Simulation
Arcova helped a major media brand tackle AI-related risk. With a set of tailored AI Purple Team scenarios, we turned a vague, unsolvable problem into a clear set of discrete tests, outcomes, and remediations. We demystified AI risk and helped the client take meaningful action in real time against active threats.
Project Information
- Services: AI Security, Purple Teaming, Governance, Risk & Compliance
- Areas of Expertise: AI, Adversary Simulation, Framework Alignment
- Sector: Technology, Media & Telecommunications (TMT)
- Pillar: Artificial Intelligence
Challenge
A global stock media brand was performing a security audit focused on AI risk. In the course of this audit, they discovered a serious problem: no one could tell them how to verify their controls. Vendors crowded around every side to reassure them they could provide the silver bullet tool, but no one could offer proof that those tools were working. Unless and until an AI-related incident occurred, it seemed, they were expected to take it all on faith. Being serious about their security, the client wasn’t willing to trust without verification.
Solution
We identified several major opportunities for no-cost improvements to the client’s security infrastructure, along with recommendations around strategic planning. We identified valuable unimplemented controls around API usage, found high-value logs not captured in alerts, helped senior leaders design and push a new DLP implementation, and worked with their engineers to validate an enterprise browser to upgrade and uniformly enforce security. The detailed, prioritized recommendations allowed the client to make strategic, defensible decisions around AI risk and to rapidly upgrade their resilience against it.
Best of all, we tied every single test and recommendation back to major AI frameworks (e.g., MITRE ATLAS, NIST SP 800-171, MAESTRO) to make it all fit smoothly into their audit.
Impact
We identified several major opportunities for no-cost improvements to the client’s security infrastructure, along with recommendations around strategic planning. We identified valuable unimplemented controls around API usage, found high-value logs not captured in alerts, helped senior leaders design and push a new DLP implementation, and worked with their engineers to validate an enterprise browser to upgrade and uniformly enforce security. The detailed, prioritized recommendations allowed the client to make strategic, defensible decisions around AI risk and to rapidly upgrade their resilience against it. Best of all, we tied every single test and recommendation back to major AI frameworks (e.g., MITRE ATLAS, NIST SP 800-171, MAESTRO) to make it all fit smoothly into their audit.
This engagement is part of a broader shift toward AI-enabled purple teaming as a strategic enabler of enterprise resilience. Learn more in our blog post on how AI is transforming purple teaming.
Key Results
API Control Enhancements
Identified and recommended implementation of high-value, unused API controls.
Enterprise Browser Validation
Collaborated with engineers to validate and enforce secure browser usage across the enterprise.
Log Visibility Improvements
Discovered critical logs not captured in existing alerting systems.
Framework Alignment
Mapped all tests and recommendations to MITRE ATLAS, NIST SP 800-171, and MAESTRO.
DLP Implementation Support
Guided senior leaders in designing and deploying a new data loss prevention strategy.
Strategic Planning Guidance
Delivered prioritized, defensible recommendations for long-term AI risk management.