Securing the Future: AI Adoptability Security Review for a Leading SaaS Provider

Client Profile

A global SaaS provider with over 1,000 employees and a rapidly expanding customer base in financial services. The client had begun integrating AI and ML technologies across their platform to enhance automation and decision-making capabilities. However, the lack of secure AI development practices and growing concerns over model integrity, data privacy, and compliance triggered the need for a comprehensive AI security review.

Challenges Faced
Key security concerns included:
  • Exposure to adversarial attacks on deployed ML models
  • Use of unvetted third-party AI components
  • Lack of visibility into AI risk across development and production environments
  • Limited readiness among DevOps and data science teams regarding AI threat mitigation
Solution
COE Security implemented a tailored AI Security Posture Enhancement Program, combining:
  • AI Threat Modeling: Identified vulnerabilities across AI/ML pipelines and model lifecycles
  • Data & Model Risk Assessment: Audited datasets and trained models for integrity and bias
  • Toolchain Hardening: Secured MLOps environments and CI/CD pipelines
  • Capability Building: Conducted workshops to upskill development and security teams
AI Risk Identification & Mitigation
  • Assessed training data integrity and implemented data validation checkpoints
  • Hardened deployed models against ML attacks using adversarial training and anomaly detection
  • Evaluated third-party AI components for hidden risks and backdoors
  • Conducted red teaming exercises to simulate real-world AI attack scenarios
Governance & Readiness Framework
  • Developed AI-specific security policies and operational procedures
  • Established secure model lifecycle management practices
  • Integrated AI risk metrics into the enterprise governance dashboard
  • Defined escalation and response protocols for AI-related incidents
COE Security’s AI Assurance Service Portfolio
  • AI Security Readiness Assessment
  • Secure MLOps Integration
  • Model Threat Simulation (Red Teaming)
  • Bias & Fairness Auditing
  • Third-Party AI Component Vetting
  • Secure Model Deployment Playbooks
  • AI-Specific Incident Response Planning
  • Training for AI Developers & Security Teams
  • AI Risk Monitoring & Dashboarding
  • Regulatory Compliance Alignment (e.g., NIST AI RMF, EU AI Act)
Implementation Details
  • Deployed AI security tools across dev, test, and production environments
  • Integrated monitoring and alerting into existing SIEM platforms
  • Delivered hands-on training for DevOps and data science teams
  • Documented secure AI development policies and incident handling procedures
Results Achieved
  • 30% reduction in exposure to AI-related security risks
  • Integrated risk monitoring across 100% of AI model deployments
  • Achieved compliance alignment with emerging AI governance standards
  • Increased AI security maturity score by 40% within six months
Client Testimonial

“COE Security gave us the clarity and control we needed to scale our AI capabilities securely. Their expert guidance turned what felt like a black box into a manageable and trustworthy system.”