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RealmWeave — agentic threat model

5.3AIVSS 5.3 · Medium

RealmWeave is a low-risk, entertainment-focused content generator with minimal agentic autonomy, posing primarily standard web application and content moderation risks rather than systemic agentic threats.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 4.3AARS uplift 1.03Factor sum 2.0/10Threat ×0.9Mitigation ×1.0
Autonomy of Action
0.10
Goal-Driven Planning
0.20
Self-Modification
0.00
Dynamic Tool Use
0.10
Persistent Memory
0.20
Contextual Awareness
0.30
Dynamic Identity
0.00
Multi-Agent Interactions
0.00
Non-Determinism
0.70
Opacity & Reflexivity
0.40

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 utilizes commercial foundation models for text (e.g., GPT-4) and image generation (e.g., Stable Diffusion). Primary threats include prompt injection leading to jailbreaks or generation of inappropriate/copyrighted content.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — likely stores user-submitted campaign details and generated assets in standard cloud databases. Threats include unauthorized access to user-created world data and lack of data lineage for generated images.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — orchestration is likely a straightforward pipeline mapping user inputs to text/image generation APIs rather than a complex agentic framework. Threats are limited to insecure input handling and API rate-limiting issues.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — hosted as a closed-source web application. Threats include standard web application vulnerabilities (OWASP Top 10), credential theft, and resource exhaustion from unauthorized API consumption.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — likely relies on basic application logging. Threats include a lack of automated content moderation guardrails to detect and block offensive or abusive generated content.

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

Not certain from the listing — likely uses standard web authentication (OAuth/email). As a freemium gaming tool, it is unlikely to have rigorous enterprise compliance certifications (e.g., SOC2, ISO 27001).

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — operates as a standalone creative tool with no described multi-agent interactions or external marketplace integrations, minimizing ecosystem-level threats.

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.