Ainisa — agentic threat model
Ainisa is a high-exposure Chrome extension agent with extensive browser-level capabilities (web reading, screenshots, document generation) that present significant indirect prompt injection and data exfiltration risks if malicious web content is processed.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.30 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.60 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.10 | |
| 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.
Utilizes multiple external foundation models (ChatGPT 4, Claude, Deepseek). This introduces risks of model-specific prompt injections, adversarial inputs, and potential data leakage to third-party model providers.
Processes active webpage content, links, and YouTube transcripts. This creates a high risk of indirect prompt injection where malicious web content manipulates the agent's behavior or exfiltrates sensitive user data.
Orchestrates diverse tools including a screenshot taker, web search, document/invoice generator, and code generator. Insecure tool integration could allow an attacker to trigger unauthorized screenshots or generate malicious code via prompt injection.
Deployed as a Chrome extension. This architecture inherits browser-extension risks, such as potential access to sensitive browser storage, cookies, and active DOMs, requiring strict origin isolation and permission scoping.
Not certain from the listing — No explicit mention of real-time monitoring, guardrails, or logging mechanisms to detect prompt injection, anomalous tool usage, or data leakage.
Not certain from the listing — No details are provided regarding user authentication, data encryption standards, or compliance certifications (such as SOC2 or GDPR) for handling generated invoices and documents.
Not certain from the listing — While it allows switching between multiple LLMs, there is no evidence of multi-agent collaboration, delegation, or ecosystem-level marketplace interactions.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).