UndercoverGPT — agentic threat model
UndercoverGPT presents a high risk of shadow AI and data exfiltration by actively bypassing organizational network blocks to facilitate covert LLM usage. Its closed-source proxy nature introduces significant man-in-the-middle risks for sensitive workplace or school data.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.20 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.50 | |
| 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.
Utilizes ChatGPT (OpenAI) as its foundation model. Primary threats include model alignment bypasses and prompt injection, which are exacerbated by the tool's goal of evading detection.
Not certain from the listing — there is no mention of custom RAG pipelines, vector databases, or training data operations; it appears to act primarily as a pass-through proxy.
Not certain from the listing — the tool functions as a stealth wrapper rather than a complex agentic framework with planning, memory, or tool-calling capabilities.
The deployment architecture must employ domain fronting, proxying, or obfuscation to bypass firewalls. This introduces significant risks of traffic interception, insecure hosting, and data leakage through unverified intermediary servers.
Not certain from the listing — likely lacks enterprise-grade logging, auditing, or guardrails, as its core value proposition is to evade administrative monitoring and detection.
Directly violates organizational security policies and compliance frameworks (e.g., NIST, ISO) by design. It facilitates shadow AI, lacks access controls, and provides no compliance guarantees.
Not certain from the listing — there is no indication of multi-agent orchestration or integration with external agent marketplaces.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).