Services
AI Product Security Assessment
Assess the real security posture of AI features before they become enterprise risk.
Focused review of LLM-powered product features, RAG systems, copilots, internal AI tools, model integrations, data flows, logging, evaluation, and customer-facing AI surfaces. Outputs include architecture findings, control recommendations, evidence gaps, and a prioritized remediation backlog.
Best for
CISO, Head of Product Security, VP Engineering, AI Product Lead
Engagement model
assessment
Duration
2-4 weeks
Deliverables
4 deliverables
What it covers
AI system inventory and data-flow review
RAG authorization and prompt injection exposure review
Model/vendor, logging, and evidence gap review
Prioritized remediation backlog
Use when
Related people
David Wolf
Builds operating models, controls, detection, and evidence layers for enterprise AI adoption.
Alex Eisen
Leads vulnerability research, incident response, product security, and AI risk management work.
Alex Karoulias
Engineering student at Athens Technical University, Class of 2027
Tim Kerimbekov
Turns cyber risk into practical security decisions.
Related proof
Start here
Scope this review through discovery, then translate the result into engineering work, buyer-ready evidence, or a follow-on engagement.
Canonical route: /services/ai-product-security-assessment