Selected Engineering Work
x402Shield
Verified selected engineering work for Rust-based AI-agent, MCP-tool, and API-payment security.
View caseAI System & Model Security Review
From VND 197,500,000~US$7,640Reference date: Oct 9, 2026 · Local price is authoritative; this is not a payment or settlement rate.
Buyer outcome
A scoped security review of an AI system, model-connected workflow, chatbot, or internal assistant used by your Vietnamese business — focused on prompt injection, data exposure, unsafe outputs, permission boundaries, and written remediation priorities before wider rollout.
Why AI security review matters
AI systems are connected directly to user inputs, internal data, APIs, and business tools. Without a planned security review, common failure modes go undetected: prompt injection through Zalo or Messenger chat inputs, data exposure through retrieval systems, unsafe outputs reaching users or downstream systems, and actions taken without human approval.
This review focuses on prompt injection through Zalo and Messenger chat inputs — including Vietnamese-language adversarial prompts designed to manipulate AI responses or extract internal data; data exposure where AI retrieves customer PII or internal pricing and operational data beyond its intended scope; insecure output handling where AI responses include raw internal information without appropriate filtering or review; retrieval risk from knowledge bases containing outdated, conflicting, or sensitive operational documents; and unsafe API or tool access where AI agents have write permissions to CRM, order management, or helpdesk systems without sufficient approval controls.
BilgeQor's AI services are built around written scope, approved data sources, permission boundaries, human approval points, and review before wider rollout.
Scope drivers
Number of AI workflows or assistants reviewed
Internal-only vs customer-facing exposure — Zalo, Messenger, web chat, or internal tools
Model, tool, and integration architecture
Knowledge source and retrieval design
Permission boundaries and action capability
Sensitive data exposure risk
Prompt injection and abuse scenario depth relevant to Vietnamese-language inputs
Required remediation and retest depth
Ideal for
- Vietnamese businesses preparing to launch or expand an AI system connected to customer channels
- E-commerce, logistics, clinic, and school teams with Zalo or Messenger chatbots, internal assistants, or RAG-style knowledge systems
- Teams that need a written risk view before connecting AI to sensitive workflows, customer data, or internal systems
- Leaders who want practical remediation priorities without overstating compliance or certification claims
- Businesses whose AI system or chatbot has grown without a formal security review
What is included
- AI system and workflow scope review
- Prompt injection and abuse scenario testing
- Data exposure and sensitive information review
- Tool, permission, and action boundary review
- Knowledge source and retrieval risk observations
- Unsafe output and handoff review
- Prioritised findings and remediation notes
- Written review summary
What is not included
- Full penetration test of unrelated systems
- Formal compliance certification
- Legal advice
- Model training, fine-tuning, or model replacement
- 24/7 monitoring or managed detection
- Production fixes unless separately scoped
- Payment or checkout before written scope is confirmed
Delivery process
1
Scope and architecture intake
Review the AI workflow, user exposure, data context, tools, knowledge sources, intended actions, and API or channel connections.
2
AI risk testing
Test agreed scenarios around prompt injection, data exposure, unsafe output, permission boundaries, and handoff behavior — including Vietnamese-language adversarial inputs relevant to Zalo and Messenger.
3
Findings and prioritisation
Document risk observations, severity, business impact, and practical remediation notes.
4
Review and next steps
Walk through findings, limitations, remediation priorities, and any recommended retest scope.
Representative deliverable
Prompt Injection, Data Exposure and AI Permission Boundary Findings Report
All AI services are request-first. Scope is confirmed in writing before any payment, deposit, or implementation commitment.
Frequently asked questions
Related evidence
Relevant Engineering work
Selected public case records related directly to this service scope. Each record keeps its attribution and disclosure boundary visible.
Request a scope review
Tell us about your team, workflows, inquiry channels, and data context. We will respond with a written scope and confirmed deliverables before any commitment.