Flyback.ai — agentic threat model
Flyback.ai acts primarily as a real-time analytical and valuation platform rather than an autonomous transactional agent, meaning its primary security risks center on data poisoning of marketplace inputs and model manipulation rather than unauthorized execution of actions.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.30 | |
| 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 — It is unclear if Flyback.ai utilizes large language models or traditional machine learning regression models for valuation. If LLMs are used for parsing unstructured listing data, they are vulnerable to prompt injection via malicious marketplace listings.
Aggregates data from 20+ external marketplaces and historical sold transactions. This creates a significant threat surface for data poisoning, where malicious actors could flood marketplaces with fake listings or artificial transaction histories to manipulate the fair value forecasts and deal scores.
Not certain from the listing — The platform appears to function as a structured data pipeline rather than a complex agentic framework. The primary threat here is insecure parsing of scraped marketplace data leading to remote code execution or injection vulnerabilities.
Not certain from the listing — Standard web hosting and database infrastructure are assumed. Key threats include the exposure of scraping infrastructure, API keys for marketplace access, and potential IP blocks from target platforms.
Not certain from the listing — The platform requires continuous monitoring for valuation drift as the luxury watch market fluctuates. A lack of drift detection could lead to stale or highly inaccurate deal scores without developer awareness.
Not certain from the listing — As a free, closed-source tool, there are no public details regarding data privacy, access controls, or compliance with scraping regulations and terms of service of the 20+ target marketplaces.
Not certain from the listing — The platform operates as a standalone vertical tool with no indicated multi-agent or external agent-to-agent marketplace integrations.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology. Are you the vendor? Factual corrections are free.