Write Glow — agentic threat model
Write Glow is a low-risk, utility-focused writing assistant with minimal agentic autonomy, primarily posing data privacy and prompt injection risks through its content generation and API endpoints.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.00 | |
| Contextual Awareness | 0.20 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.50 | |
| 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 relies on third-party foundation models for text generation and humanization, making it susceptible to prompt injection, model alignment bypasses, and potential training data reconstruction if fine-tuned.
Not certain from the listing — processes user-provided text inputs for optimization and detection. Risks include data leakage of sensitive user-submitted drafts and lack of clear data retention or sanitization policies.
Not certain from the listing — orchestration appears to be a straightforward pipeline (input processing, model inference, output formatting) rather than a complex agentic framework, reducing risks of tool misuse or planning failures.
Not certain from the listing — deployed as a web application and API. Standard web application vulnerabilities, API key exposure, and lack of rate limiting on the generation endpoints are the primary infrastructure threats.
Not certain from the listing — no evidence of real-time output monitoring, input guardrails, or evaluation metrics to prevent the generation of toxic, biased, or malicious content.
Not certain from the listing — lacks explicit details regarding compliance certifications (e.g., SOC2, GDPR) or robust access control mechanisms for its API and freemium tiers.
Not certain from the listing — operates as a standalone horizontal utility tool with no described multi-agent coordination, marketplace integrations, or ecosystem dependencies.
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.