QuickPick.AI — agentic threat model
QuickPick.AI is a low-risk, informational shopping assistant focused on product discovery and comparison. Because it lacks transactional capabilities (such as direct purchasing or payment handling), its primary security risks are limited to prompt injection, recommendation manipulation, and potential redirection to malicious external links.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.30 | |
| 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 a third-party foundation model to drive the 'Smart Question Flow' and generate recommendations. It is susceptible to prompt injection attacks that could alter recommendation logic or output malicious URLs.
Not certain from the listing — aggregates product data from various online stores. This ingestion pipeline is vulnerable to data poisoning if external retailer listings contain malicious payloads, leading to corrupted recommendations or indirect prompt injection.
Not certain from the listing — orchestrates user input through a question flow to query external retail APIs. Insecure tool integration could allow attackers to manipulate search queries, potentially leading to SSRF or API abuse depending on how the multi-retailer search is implemented.
Not certain from the listing — hosted as a web-based application with no installation needed. Standard web application security risks apply, but specific hosting, sandboxing, or containerization details are not disclosed.
Not certain from the listing — there is no mention of real-time monitoring, guardrails, or evaluation frameworks to detect drift, biased recommendations, or adversarial inputs.
Not certain from the listing — as a free, closed-source tool, there are no public details regarding compliance alignments (e.g., GDPR, SOC2) or user data access controls.
Not certain from the listing — operates as a standalone horizontal agent. There is no evidence of multi-agent collaboration or integration into a broader agent marketplace.
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.