AutoSec TARA Suite vs AWS Threat Composer

AutoSec TARA Suite is a pilot automotive threat-modelling and risk-management platform for analyst-led workflows aligned with ISO/SAE 21434 and UN R155 activities. Its analysis moves through item definition, asset and boundary identification, threat scenarios, attack analysis, impact assessment, and risk determination. Candidate threat scenarios are generated for analyst review and mapped to STRIDE categories. Risk assessment considers safety, financial, operational, and privacy impacts, then calculates attack potential to determine risk. Listed outputs include traceability matrices, PDF and Excel compliance bundles, and VSOC detection rule exports. Deployment options include analyst-led engagements, managed evaluation instances, and self-hosted customer instances. Controlled self-hosted evaluations and technical demonstrations are available on request. The suite is designed to support ISO/SAE 21434, UNECE R155, and ISO 26262 activities, but it does not certify products or organisations. Pricing is available on request.

AWS Threat Composer is a threat-modeling project for identifying security issues and developing ways to address them. Its structured threat grammar offers adaptive suggestions for composing threat statements. Models can include architecture and data-flow diagrams, tracked assumptions, links between threats and mitigations, and an insights dashboard with quality metrics and improvement suggestions. Users can manage multiple models and export them as JSON, Markdown, DOCX, or PDF. The web application stores data in the browser, supports import and export, and is available as a hosted demo or as a static site deployed in an AWS account. The VS Code extension in AWS Toolkit edits .tc.json files, works offline, and stores data locally. A browser extension displays threat model files on GitHub, GitLab, Bitbucket, and Amazon CodeCatalyst; it is read-only and requires internet access for web-hosted files. The AI-assisted CLI and MCP server can analyze source code to create starter models, but the tools are experimental. They use AWS Bedrock, and inference costs apply.