Carvia.ai — agentic threat model
Carvia.ai acts as an informational assistant for vehicle transactions, presenting moderate risk primarily centered around the integrity of its vehicle history summaries and market valuation advice, with no direct transactional or autonomous purchasing capabilities.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.30 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.40 | |
| Opacity & Reflexivity | 0.30 |
Scored with the canonical OWASP AIVSS formula (AIVSS calculator reference); agentic risk factors estimated from the agent’s described capabilities.
MAESTRO 7-layer threat model
Per-layer threats for this agent. Layers tagged “not certain from listing” are general, caveated commentary where the public description didn’t pin that layer.
Not certain from the listing — likely utilizes commercial LLMs to summarize vehicle history and generate buyer/seller guidance. Threats include prompt injection that could trick the model into ignoring critical vehicle defects or fabricating clean history reports.
Not certain from the listing — ingests real-time vehicle history, VIN data, and market valuations. Threats include data poisoning of upstream vehicle history APIs or caching mechanisms, leading to inaccurate valuation and risk assessments.
Not certain from the listing — orchestrates tool calls to VIN decoders and marketplace APIs. Threats include insecure tool integration where malformed VIN inputs or API responses could exploit the underlying orchestration framework.
Not certain from the listing — deployed as an API-driven web service. Threats include standard web application vulnerabilities, insecure handling of API keys for third-party vehicle databases, and lack of network isolation.
Not certain from the listing — no monitoring or guardrails are described. Threats include a lack of observability into hallucinated vehicle history details or drift in market pricing algorithms.
Not certain from the listing — compliance and authorization controls are not detailed. Threats include unauthorized access to premium vehicle history reports or user search histories due to weak session management.
Not certain from the listing — integrates with external marketplaces. Threats include trust abuse where compromised marketplace endpoints feed malicious data to the agent, or the agent is used to scrape/spam marketplace listings.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).