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Your Own AI — agentic threat model

5.7AIVSS 5.7 · Medium

Your Own AI presents a low-to-moderate agentic risk posture, acting primarily as a customizable conversational companion with a strong emphasis on privacy, though lacking high-consequence tool execution capabilities.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 5.3AARS uplift 1.46Factor sum 3.1/10Threat ×1.0Mitigation ×0.85
Autonomy of Action
0.20
Goal-Driven Planning
0.20
Self-Modification
0.30
Dynamic Tool Use
0.10
Persistent Memory
0.50
Contextual Awareness
0.40
Dynamic Identity
0.10
Multi-Agent Interactions
0.20
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✓ mapped

Leverages open-source LLMs to power custom and pre-made characters. Primary threats include prompt injection to bypass character personas, model misalignment, and potential model utility degradation depending on the specific open-source models selected.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — While a 'privacy-first architecture' is claimed, the exact mechanism for storing conversation history, custom character definitions, and user data isolation is unspecified, leaving potential risks of data leakage or cross-tenant data exposure.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — The orchestration framework supporting character customization and the 'grow, learn, and evolve' memory capability is not detailed, presenting potential risks of memory poisoning or insecure state management.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — The service is described as providing an experience close to running locally, but it is offered as a cloud-based API/service. The hosting infrastructure, sandboxing of custom characters, and API security controls are not disclosed.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — There is no mention of real-time monitoring, input/output guardrails, or observability tools to detect drift, toxic outputs, or policy violations within custom-built characters.

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

Not certain from the listing — Despite claiming 'strong data protection' and a 'privacy-first' design, specific compliance certifications (such as GDPR or SOC2) or identity/access management controls are not explicitly detailed.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — The ability to 'collaborate with your own custom-built AIs' suggests a multi-persona environment, but the presence of an active multi-agent ecosystem, marketplace, or inter-agent communication protocols is unverified.

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.