Ollie AI — agentic threat model
Ollie AI presents a moderate risk profile as a consumer-facing personal assistant; while its current capabilities are primarily advisory (meal planning and list generation), its continuous learning, image parsing, and planned automated grocery ordering introduce risks of data privacy leaks, prompt-injection-based allergen bypasses, and unauthorized financial transactions.
OWASP AIVSS score rationale
| Autonomy of Action | 0.30 | |
| Goal-Driven Planning | 0.50 | |
| Self-Modification | 0.20 | |
| Dynamic Tool Use | 0.40 | |
| Persistent Memory | 0.70 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.60 | |
| Opacity & Reflexivity | 0.50 |
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 relies on commercial vision-language models to parse screenshots and generate recipes. Threats include prompt injection (e.g., bypassing safety filters to generate harmful recipes) and model hallucinations regarding ingredient safety or allergen substitutions.
Not certain from the listing — ingests user-uploaded photos, screenshots, and favorite recipes to build a continuous learning profile. Threats include data exfiltration of personal family photos and data poisoning of the user's preference profile to skew recommendations.
Not certain from the listing — orchestrates recipe adjustments and compiles shoppable grocery lists. Threats include memory poisoning (manipulating the continuous learning state) and insecure tool integration with external grocery platforms.
Not certain from the listing — likely deployed as a cloud-hosted mobile backend. Threats include insecure storage of user-uploaded images (e.g., public S3 buckets) and exposure of API keys used to interface with grocery retail partners.
Not certain from the listing — no mention of guardrails or monitoring systems. Gaps in observability could allow toxic or unsafe recipe recommendations (e.g., misidentifying ingredients in screenshots) to pass through to the user without detection.
Not certain from the listing — no compliance certifications (such as SOC2) or data privacy guarantees are cited. Risks include lack of robust access controls over personal family data and unclear data retention policies for uploaded images.
Not certain from the listing — currently operates as a vertical consumer app, but plans to integrate automated grocery ordering. This future ecosystem expansion introduces risks of unauthorized financial transactions and cascading failures through third-party delivery APIs.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).