Agentic AI Claims processing Threat Modelling

@iimtpradeepdash

Hi! The mix of Azure EDM, TIBCO, and GCP-powered GenAI summarisation is a real-world tangle—especially with data moving between clouds and into/out of AI pipelines. Your focus on clear trust boundaries and GenAI threat libraries makes sense given the risks. I’ve led threat modelling sessions for SaaS with cloud+AI flows before, including hands-on IriusRisk and STRIDE with GenAI libraries. Mapping data movement and publishing back to EDM is a sticking point I’ve seen catch teams out before. First, I’d draft a list of artefacts and stakeholder questions for the discovery, then plan the workshop to surface where the model is thin or assumptions are untested. Outcomes feed straight into IriusRisk and a risk register, with NIST controls suggested for each mapped risk. Quick question: do you already have a formal data flow or architecture diagram, or do we need to build that from scratch at the workshop? Happy to send a sample outline of discovery questions and artefacts I’d use. For other high-security SaaS work, you’ll find examples at work.techindika.com. — Pradeep

@dushyant317

I have experience in security architecture reviews, threat modeling, and cloud-native risk assessments across Azure, GCP, and AI/LLM-based platforms. I can lead the discovery workshops, create DFDs with trust boundaries, build the complete IriusRisk threat model, perform STRIDE and GenAI-specific analysis, map risks to NIST/CIS/CSA controls, and deliver a prioritized risk register with residual risk assessment and executive-ready documentation.

@hugog17

Hi, I can help you run a complete IriusRisk threat modelling engagement for your Agentic AI claims summarisation platform across Azure EDM, TIBCO, and GCP (Gemini/Vertex AI). I will first focus on a structured discovery phase to map end-to-end data flow, trust boundaries, and AI invocation points to identify gaps before formal modelling. Example: I would trace a claim document from Azure ingestion → TIBCO orchestration → GCP AI summarisation → return to EDM, highlighting risks like data leakage, insecure API chaining, and prompt injection across each boundary. Deliverables: • Discovery workshop agenda + notes • Architecture review and improved diagrams • Data Flow Diagram with trust boundaries • STRIDE + GenAI threat modelling • IriusRisk project file • Prioritised risk register with controls • Residual risk summary To start, I need: • Current architecture diagrams • Data classification details • API flows between Azure/TIBCO/GCP • Auth model and security controls • AI prompt/usage flow I can begin with the workshop structure immediately.

@akashdev5567

Hello, My background is primarily in AI systems, cloud architectures, enterprise integrations, and secure application development, which makes this project particularly interesting to me. I have worked on AI-powered platforms involving RAG pipelines, embeddings, OpenAI/Gemini integrations, workflow automation, Azure/GCP deployments, API security, and multi-service enterprise architectures where sensitive data moves across several systems. For your engagement, I would begin by mapping the complete flow from EDM → TIBCO → Gemini/Vertex AI → EDM, identifying missing architectural artifacts, trust boundaries, authentication flows, data classifications, and AI-specific attack surfaces before moving into detailed threat modeling. My experience includes: • AI/LLM and GenAI integrations • Azure & GCP cloud architectures • API security and authentication • OWASP security reviews • SonarQube and OWASP ZAP assessments • Enterprise workflow and integration platforms Given the GenAI component, I understand the importance of assessing risks such as prompt injection, data leakage, unauthorized access, output manipulation, model misuse, and cross-system trust boundary violations. I'd be happy to discuss the current architecture and help identify the key artifacts and questions needed to kick off the discovery phase. Best Regards, Kshitij

@damanohri17

Hello, I am a Backend Developer and Team Lead with 4+ years of experience in API development, system architecture, cloud integrations, and technical documentation. I can assist in reviewing application architecture, mapping end-to-end data flows, documenting integration points, creating technical diagrams, and identifying potential security considerations across Azure, GCP, and API-based systems. My experience includes designing scalable backend solutions, leading development teams, and working closely with stakeholders to understand business and technical requirements. I would be happy to discuss your architecture and requirements further. Regards, Daman Ohri