AI Security Engineering Readiness Assessment

A rigorous, standards-aligned, learning-first assessment covering LLM application security, prompt injection, RAG security, agent security, model supply chain, MLOps, AI SDLC, privacy, governance, red teaming, incident response, vendor risk, and secure architecture. This is a readiness benchmark and educational resource, not an accredited certification.

200 q · 180m

Question 1 of 2001%

ai sdlc product security

Select the six artifacts that should be in a release packet for a high-risk AI feature.

The feature is a customer-facing assistant that retrieves tenant documents and can draft workflow changes for human approval.

A. Provider data-processing review covering training.B. Architecture and data-flow diagram covering prompts.C. Threat model or abuse-case review with risk owners and mitigation decisions.D. Residual-risk and exception record, if any, with owner, scope, expiration, and remediation.E. A model benchmark leaderboard screenshot.F. Operational readiness notes for logging, monitoring, rollback, kill switch, and incident contacts.G. A marketing screenshot showing the assistant looks polished.H. Security eval results for cross-tenant leakage.

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AI Security Engineering Readiness Assessment

200 q · 180m

Question 1 of 2001%

ai sdlc product security

Select the six artifacts that should be in a release packet for a high-risk AI feature.

The feature is a customer-facing assistant that retrieves tenant documents and can draft workflow changes for human approval.