Conviction AI — agentic threat model
Conviction AI presents a high-risk profile due to its ability to turn arbitrary web tasks and browsing into executable API endpoints, creating significant vectors for prompt injection, unauthorized web actions, and downstream data integrity issues.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.20 | |
| Dynamic Tool Use | 0.80 | |
| Persistent Memory | 0.30 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.40 | |
| Multi-Agent Interactions | 0.30 | |
| 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 — the underlying LLMs used to translate natural language into web automations are unspecified. Risks include prompt injection altering the generated automation logic or model reprogramming.
Not certain from the listing — the data operations, vector stores, or caching mechanisms for extracted website information are not detailed. Risks include data exfiltration of sensitive scraped data.
The agent orchestrates web browsing, information extraction, and action execution based on natural language. Risks include tool misuse (e.g., executing unintended actions on target websites) and insecure tool integration via the generated API endpoints.
Not certain from the listing — the sandboxing of the browser agent and hosting infrastructure for the generated API endpoints are not detailed. Risks include SSRF, IP blacklisting, or container escape during web browsing.
Not certain from the listing — no monitoring, logging, or guardrails for the generated APIs are mentioned. Risks include undetected drift in website structures causing automation failures or silent data corruption.
Not certain from the listing — authentication and authorization mechanisms for securing the generated API endpoints and SDK integrations are not specified. Risks include unauthorized API execution and lack of audit trails.
The tool generates API endpoints designed to be integrated into codebases or used by other agents. Risks include cascading failures if a target website changes, and downstream trust abuse where other agents blindly trust the extracted data.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).