CarbonCopies AI — agentic threat model
CarbonCopies AI presents a moderate-to-high risk profile due to its autonomous UI execution capabilities (taps, swipes, typing) and integration with external bug-tracking systems, which could be exploited if the agent is exposed to malicious target applications or prompt injection.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.60 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.60 | |
| 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.
Not certain from the listing — likely relies on vision-language models (VLMs) or LLMs to interpret UI screens. A key threat is indirect prompt injection, where malicious text on a tested website or app manipulates the agent's behavior.
Not certain from the listing — processes screen captures, user personas, and flowcharts. Threats include the accidental ingestion and exposure of sensitive user data or PII displayed during test execution.
The agent orchestrates multi-step UI interactions (taps, swipes, typing) and automatically files bug tickets. Threats include tool misuse, where the agent is tricked into executing destructive actions on the target application or spamming external bug trackers.
Not certain from the listing — likely runs emulators or headless browsers in a cloud environment. Threats include container escape from the testing sandbox or lateral movement if the testing environment is not network-isolated.
Not certain from the listing — provides flowcharts and screen documentation which aid observability, but lacks detailed information on real-time guardrails to prevent or log unauthorized agent actions during test runs.
Not certain from the listing — no security certifications (e.g., SOC2, ISO 27001) or enterprise access control mechanisms are specified in the public directory listing.
Not certain from the listing — simulates multiple user personas ('AI twins'), but there is no evidence of a multi-agent marketplace or complex agent-to-agent trust boundaries that could lead to cascading failures.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).