GoCharlie — agentic threat model
GoCharlie is a closed-source, multimodal content creation agent presenting moderate risk, primarily centered around prompt injection, brand reputation damage, and potential intellectual property exposure through uploaded creative assets.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.30 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.60 |
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 proprietary or third-party multimodal foundation models. Key threats include adversarial prompt injection to bypass safety filters, generating brand-damaging or copyrighted content, and model reprogramming.
Not certain from the listing — likely ingests user-provided brand guidelines, text, and images. Threats include data exfiltration of proprietary brand assets and potential data poisoning if user feedback is used for continuous learning.
Not certain from the listing — orchestration details for multimodal generation are proprietary. Threats include insecure tool integration if the agent connects directly to external CMS or social media APIs for publishing.
Not certain from the listing — hosted as a closed-source SaaS platform. Standard cloud infrastructure threats apply, including unauthorized access to user accounts, session hijacking, and API exposure.
Not certain from the listing — no details on output guardrails or content moderation systems. Lack of robust observability could allow toxic, biased, or hallucinated content to be generated undetected.
Not certain from the listing — compliance posture regarding copyright laws for AI-generated media and user data privacy is unstated. Lack of clear enterprise access controls poses a risk of unauthorized usage.
Not certain from the listing — no explicit multi-agent or marketplace integrations are described. Risks are limited to downstream publishing integrations if they are configured to trust the agent blindly.
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.