From Whiteboard to
ISO 21434 Model
in Seconds
Proprietary Image-to-Model AI converts photos, diagrams, and legacy docs into structured cyber models with 95% accuracy.
Whiteboard Photo Input
Proprietary Image-to-Model AI converts photos, diagrams, and legacy docs into structured cyber models with 95% accuracy.
Whiteboard Photo Input
Watch how TaraFlow transforms a whiteboard photo into an ISO 21434-compliant threat model in under 30 seconds. Or upload your own architecture diagram to see it yourself.
Three-stage AI pipeline trained on 10,000+ automotive diagrams for industry-leading accuracy
Accepts Whiteboard photos, Visio exports, and PowerPoint slides
AI identifies Components (95% confidence), Protocols (CAN/LIN), and Trust Zones
Generates structured JSON models ready for risk assessment
{
"component": "Brake ECU",
"criticality": "SAFETY_CRITICAL",
"protocol": "CAN",
"trustZone": "Zone_1_Internal",
"interfaces": [
{
"type": "CAN",
"bandwidth": "500kbps",
"authentication": true
}
],
"threats": [
{
"id": "T-001",
"type": "Spoofing",
"severity": "HIGH"
}
]
}Damage Scenarios FIRST, Threats SECOND — The only platform following the ISO 21434 standard correctly
Define impact first: Safety, Financial, Operational, Privacy
AI auto-correlates threats to damage scenarios
Visual tree structure showing all attack paths
Feasibility × Impact = ISO 21434 Risk Score
Define impact first: Safety, Financial, Operational, Privacy
AI auto-correlates threats to damage scenarios
Visual tree structure showing all attack paths
Feasibility × Impact = ISO 21434 Risk Score
Most tools start with threat libraries and force-fit them to your system. TARA Flow follows ISO 21434's correct methodology: understand potential damages first, then identify relevant threats. This results in 40% fewer false positives and complete audit compliance.
Multi-party security boundaries with automatic threat escalation detection
Model complex ecosystems with OEMs, suppliers, and cloud services. TARA Flow automatically detects and flags cross-boundary threats that require special attention.
Cross-zone attacks automatically inherit higher risk scores. No manual recalculation needed.
AI flags potential trust zone violations before they become audit findings.
Track which components belong to which suppliers for SBOM and compliance reporting.
See how AI-powered automation transforms the threat modeling process
Total Time & Cost Savings
Technical specifications for engineering teams and security architects