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LoveGenius — agentic threat model

7.0AIVSS 7.0 · High

LoveGenius is a low-autonomy, consumer-focused AI assistant posing primarily privacy and data security risks due to its handling of sensitive personal dating profiles and chat histories without explicit security certifications.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 5.9AARS uplift 1.07Factor sum 2.6/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.20
Goal-Driven Planning
0.20
Self-Modification
0.00
Dynamic Tool Use
0.10
Persistent Memory
0.40
Contextual Awareness
0.50
Dynamic Identity
0.10
Multi-Agent Interactions
0.00
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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — likely relies on third-party commercial LLMs via API to generate profiles and messages. Risks include prompt injection to bypass safety filters, potentially generating inappropriate, harassing, or deceptive content.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — processes highly sensitive personal data, dating preferences, and chat histories. Risks include data exfiltration of private user conversations and lack of transparent data isolation or encryption-at-rest standards.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — likely uses a basic template-based orchestration framework to inject user context into LLM prompts. Risks include insecure prompt construction leading to system prompt leakage or context manipulation.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — deployed as a closed-source web application. Risks include standard web application vulnerabilities (e.g., broken authentication, insecure session management) exposing user accounts.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — no public details on output monitoring or guardrails. Risks include a lack of real-time filters to prevent the generation of abusive, toxic, or scam-like dating messages.

L6 · Security & Compliance (cross-cutting)⚠ not certain from listing

Not certain from the listing — handles sensitive personal information (PII) and relationship preferences but does not advertise compliance with privacy regulations (like GDPR) or security frameworks (like SOC2).

L7 · Agent Ecosystem✓ mapped

The agent operates as a standalone vertical B2C assistant with no described multi-agent coordination or marketplace integrations, minimizing ecosystem-level cascading risks.

MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).