AI System, Flow, and Trust-Boundary Modeling
Model the AI system, its boundaries, and its flows.
Create a reviewable security model of applications, models, data stores, retrieval systems, agents, tools, identities, trust boundaries, controls, and intended flows. Define candidate abuse scenarios before testing, hardening, or preserving evidence.
Connected system canvas
Model components, external entities, data stores, agents, tools, trust boundaries, and intended data or action flows.
Trust-boundary mapping
Identify where authorization, identity, data handling, ownership, control, logging, or approval requirements change.
AI threat modeling
Apply established threat-modeling methods and AI-specific failure patterns to the actual system design.
Candidate abuse-scenario planning
Describe plausible routes from attacker-controlled input or unsafe system state toward security consequence without presenting untested scenarios as validated attack paths.
Control mapping
Attach mitigations, ownership, test requirements, and evidence expectations directly to the relevant components, flows, boundaries, and scenarios.
Jira & Confluence export
Turn approved risks and controls into engineering work and design-review records.
Core capabilities
What Threat Canvas does.
System and flow canvas
Represent external entities, processes, applications, models, data stores, retrieval systems, agents, tools, identities, trust boundaries, controls, and flows in one structured view.
Trust-boundary mapping
Define trust zones and security boundaries across user-facing surfaces, internal services, model providers, vector stores, identities, tenants, tools, external APIs, and consequential actions.
AI threat modeling
Apply STRIDE and AI-specific threat patterns including prompt injection, retrieval leakage, excessive agency, unsafe output handling, model manipulation, memory poisoning, and supply-chain risk.
Candidate abuse-scenario planning
Enumerate plausible abuse scenarios from the canvas. Each scenario names the actor, entry condition, affected flow, trust boundary, required preconditions, relevant controls, and potential impact.
Control mapping
Attach controls, mitigations, owners, test requirements, and evidence expectations directly to canvas elements and modeled scenarios.
Jira & Confluence export
Create structured Jira-ready remediation work and Confluence-ready design records containing system context, risk, ownership, control state, evidence, and reviewer decisions.
AI SECURITY WORKBENCH
Ready to put Threat Canvas to work?
Start with one bounded application, workflow, tool set, or security decision. Use the relevant Workbench experience to produce connected context, reviewable findings, assigned controls, and explicit next steps.
Continue through the Workbench
Continue through the Workbench
Surface Discovery
Discover applications, providers, prompts, agents, tools, and external boundaries that feed the system model.
Continue through the Workbench
Authority Graph
Trace identities, credentials, permissions, tools, approvals, and consequential actions.
Continue through the Workbench
Adversarial Range
Exercise the modeled failure flows and preserve the observed trace.
Continue through the Workbench
Evidence System
Carry the approved model, findings, controls, decisions, and retest results into reviewed outputs.