I design secure-by-design architectures for cloud-native, AI-driven, and distributed systems.

Focused on:

• Security Architecture
• Threat Modeling
• AI / LLM Security
• Service-to-Service Trust
• Software Supply Chain Security

Secured 60+ cloud-native and distributed systems through architecture reviews, attack path analysis, and threat modeling.

Built an ML-assisted DAST validation system reducing false positives by 80%.

• Trust boundaries and attack paths in distributed systems
• AI inference security (RAG, agents, tool execution)
• Identity-first architecture and workload trust
• Secure service-to-service communication (OAuth, mTLS)
• CI/CD and software supply chain security

Core belief:

Security failures happen at trust boundaries, not components.

🔗 https://github.com/khirawdhi/secure-inference-architecture-blueprint

Practical security architecture blueprint for AI inference systems.

Covers:

• Prompt injection
• Retrieval poisoning
• Tool abuse
• Data leakage
• Trust boundaries across inference pipelines

Core idea:

AI security is not a model problem.
It is an inference architecture problem.

🔗 https://github.com/khirawdhi/zero-to-hero-threat-model

Practical playbook for threat modeling modern distributed systems.

Covers:

• DFD + STRIDE
• Attack path analysis
• AI systems
• OAuth vs mTLS
• CI/CD and supply chain risks

Cloud: AWS, Azure, GCP
Security: Threat Modeling, Security Architecture, Identity & Access Design
DevSecOps: CI/CD Security, Container Security, Supply Chain Security
Language: Python

I write about:

• Threat Modeling as Architecture
• AI / LLM Security
• Distributed System Trust Models
• Secure-by-Design Systems

• LinkedIn: https://www.linkedin.com/in/khirawdhi/
• Website: https://raykhira.com/