Security Projects & Case Studies

THE CHALLENGE:

A healthcare technology platform had outgrown their simple role-based permission system. They needed fine-grained access control where doctors could only see patients they're treating, administrators could manage their facility but not others, and insurance partners could access aggregate data but not PHI. Their existing codebase had permission checks scattered everywhere, making changes risky and slow.

THE SOLUTION:

Migrated from basic RBAC to an attribute-based access control (ABAC) model with centralized policy enforcement.

Key components:

• Designed ABAC model supporting complex healthcare access rules
• Centralized policy engine replacing scattered permission checks
• Database schema migration to support attribute-based queries
• Policy-as-code framework enabling non-engineers to update rules
• Comprehensive audit logging for HIPAA compliance

THE RESULTS:

• Reduced unauthorized access attempts by 42% through better enforcement
• Cut time to implement new permission rules from 2 weeks to 2 days
• Reduced permission-related code by 60% through centralization
• Passed HIPAA audit with zero access control findings
• Enabled new business model (facility-specific pricing) previously impossible

THE CHALLENGE:

Customer's platform detected unusual API activity suggesting unauthorized access to customer data. They weren't sure what was compromised, how the attacker got in, or if the breach was still active. With thousands of customers potentially affected and a legal obligation to report within 72 hours, they needed fast, definitive answers.

THE SOLUTION:

Led complete incident response from detection through remediation and post-mortem.

THE RESULTS:

• Fully contained breach within 18 hours of engagement
• Determined exact scope for accurate customer notification
• Provided documentation meeting legal reporting requirements
• Zero additional customer records compromised after containment
• Company maintained customer trust through transparent, professional response

THE CHALLENGE:

An AI-powered product platform was preparing for launch. Leaders were asking detailed questions about AI security: "How do you prevent prompt injection? What's your model governance? How do you secure training data?" The team had strong ML expertise but limited security experience, and generic security consultants didn't understand AI-specific risks.

THE SOLUTION:

Implemented comprehensive AI security framework adapted for their specific business needs.

Key components:

• Threat model for their specific AI architecture (fine-tuned LLMs for data analysis)
• Input validation and sanitization to prevent prompt injection attacks
• Model output filtering to prevent data leakage
• Secure model training pipeline with data lineage tracking
• Access controls for model artifacts and training data
• Monitoring for adversarial inputs and model behavior anomalies

THE RESULTS:

• Identified and fixed 12 AI-specific security vulnerabilities
• Passed leadership-level security review with zero critical findings
• Reduced AI model deployment security review from 2 weeks to 2 days
• Framework now used for 15+ models in production