AI-assisted threat modeling for secure-by-design
Raptor Model
Find threats before code — AI-assisted threat modeling that surfaces architectural risk at design stage, when it's still cheap to fix.
The problem
What it addresses
- Traditional threat-modeling workshops are expert-intensive and hard to scale across many teams.
- Security reviews often land late, when architectural weaknesses are expensive to remediate.
- Architecture documentation lives in many formats and rarely turns into actionable analysis.
Capabilities
What it does
- AI/LLM-assisted analysis of architecture diagrams and design information.
- Support for common inputs — Visio, Draw.io, PNG/JPG — and IaC such as Terraform / Pulumi where supported.
- Identification of threats, affected components and trust boundaries, and recommended mitigations.
- A secure-by-design workflow that fits design-stage assurance and engineering review.
- Findings tracked in engineering systems such as Jira, with support for DevSecOps gating.
Differentiators
Why it's different
- Automates a traditionally manual, specialist-heavy activity.
- Reads architecture inputs rather than asking every team to build a model from scratch.
- Connects each threat to a practical mitigation engineers can act on.
- Shifts assurance earlier, reducing reliance on late-stage pen testing as the primary discovery mechanism.
In practice
A team uploads an architecture with internet-facing APIs, cloud services, databases and third-party integrations. Raptor Model flags trust boundaries and likely threat scenarios, proposes mitigations, and lets findings be tracked through development.
Where it fits
Part of one connected lifecycle
ClassifyControlDesignComplyGovern
Risk context created upstream is reused here, instead of being rebuilt independently by GRC, AppSec and engineering.
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