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 PHP 445,000~US$7,080Reference date: Oct 9, 2026 · Local price is authoritative; this is not a payment or settlement rate.
Buyer outcome
A scoped security review of a deployed or near-launch AI system for Philippine teams — LLM workflow, chatbot, internal assistant, retrieval system, or API-connected automation. Written findings covering prompt injection, data exposure, permission boundaries, and remediation priorities before wider rollout.
Why security-led AI integration matters
AI systems connect directly to user inputs, internal data, APIs, and business tools. Without a deliberate security review, common failure modes go undetected: prompt injection through Messenger or Viber 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 vulnerabilities in customer-facing AI channels — including Messenger and Viber, data exposure through overly permissive retrieval, insecure output handling where AI-generated content reaches systems without sanitisation, retrieval risk from poorly controlled knowledge bases, unsafe API and tool access without adequate scope constraints, and model behavior drift under adversarial inputs. Many early Philippine AI deployments use off-the-shelf chatbot platforms — this review assesses not just the AI model but the platform configuration and integration points.
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 systems reviewed
Internal vs customer-facing exposure — Messenger, Viber, web chat, helpdesk, CRM, or internal tool
Model, tool, and integration architecture
Knowledge source and retrieval design
Permission boundaries and action capability
Sensitive data exposure and handling risk
Prompt injection and abuse scenario depth
Required remediation and retest depth
Ideal for
- Philippine product, app, e-commerce, and SME teams preparing to launch or expand an AI feature
- Support and operations teams using AI-connected Messenger, Viber, web chat, CRM, or helpdesk workflows
- Businesses with customer-facing chatbots, internal assistants, or retrieval-based knowledge systems
- Technical teams or business owners who have built an AI workflow and need an independent review before wider rollout
- Leaders who want practical risk findings and remediation priorities without overstating certification
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 or audit
- 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 covering prompt injection, data exposure, unsafe output, permission boundaries, and handoff behavior.
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, and data context. We will respond with a written scope and confirmed deliverables before any commitment.