SecureForge AISERVICES
Security-engineering disciplines for sustained hardening
Six practice areas delivered as scoped consultancy — authorized, documented and aligned to Canadian privacy obligations. Every engagement begins with a written scope and ends with engineer-verified deliverables your team can act on.
OVERVIEW
What we deliver
SecureForge AI helps engineering and security teams harden systems before incidents force the conversation. Our work sits between advisory and hands-on assessment: we review architecture, configuration and AI workloads, produce prioritized remediation plans and support implementation — without replacing your internal ownership of production environments.
We integrate with your existing tooling — cloud control planes, identity providers, CI/CD platforms and observability stacks. Our value is in engineering judgment, structured assessment and sustained posture management, not licence resale.
Assessment bay — structured review before findings reach your backlog.
Authorized assessment lab — all testing within written client scope.
AUTHORIZED ASSESSMENT
Controlled validation within scope
Where architecture review requires controlled validation — penetration-style testing of specific surfaces, configuration verification or red-team exercises — we operate strictly within a signed rules-of-engagement document. Targets, methods, timing and data-handling constraints are agreed in advance. We do not perform unauthorized access or testing outside defined boundaries.
Findings from authorized assessment feed directly into hardening plans. Your team receives reproducible evidence, severity ratings and remediation guidance — not a generic report that sits on a shelf.
AI / LLM HARDENING
Governance for inference workloads
Models that process customer data need the same architectural discipline as any production service — plus additional controls around prompt injection surfaces, training-data provenance and output handling. We review model endpoints, RAG pipelines, vector stores and orchestration layers for access gaps, data-residency issues and logging blind spots.
AI-assisted analysis helps correlate configuration across large estates; engineer verification ensures findings reflect your actual risk context, not generic checklist output.
LLM hardening review — prompt boundaries, access controls and data handling.