RAG Isolation Findings
Findings on tenant, role, document, source, and metadata boundaries before retrieved content reaches model context.
RAG Security Assessment
Validate tenant isolation, retrieval boundaries, and prompt-injection resilience before enterprise review.
A focused assessment for retrieval-augmented systems that need defensible isolation, authorization, and response-boundary controls.
Best fit
Security, data platform, AI product, and enterprise SaaS teams shipping RAG features over sensitive or multi-tenant data.
Use this before enterprise security review, customer launch, multi-tenant rollout, or expansion into higher-sensitivity document sets.
Review focus
TKOResearch reviews retrieval paths, authorization checks, chunking behavior, prompt handling, and response controls so teams can reduce leakage risk before scrutiny.
What you get
Decision support for connected AI systems.
Within 10 business days, you receive: threat model, agent/tool attack-path map, RAG isolation findings, MCP/API permission matrix, sanitized transcripts where applicable, prioritized mitigations, and an executive Go/No-Go memo.
Sample assessment package
Every engagement produces a decision-ready assessment package: an executive Go/No-Go memo, technical findings register, architecture/trust-boundary review, abuse-case matrix, and prioritized remediation roadmap.
Retrieval Boundary Review
Assess how user identity, tenant membership, metadata filters, and query rewriting affect what material can be retrieved.
Source Authorization Matrix
Matrix showing which sources require authorization, attribution, trust labeling, filtering, or exclusion from generation.
Prompt-Injection Resilience Notes
Review how instructions embedded in documents, emails, webpages, and tool output can influence retrieval and response behavior.
Enterprise Review Remediation Plan
Prepare a concise technical summary of isolation controls, known limits, and remediation priorities for customer security teams.
Risk addressed
Tool, data, and trust-boundary risk in one review.
- Designed for RAG systems that combine sensitive content, search, and generated responses
- Covers tenant boundaries, authorization checks, retrieval filters, and response behavior together
- Keeps findings tied to practical engineering changes rather than abstract model risk
When to use it
Principal-led, architecture-level review for high-stakes agent deployments.
Use this when a specific system boundary needs senior technical judgment before production access, customer review, or executive approval.
Written scope