AI Assistify — agentic threat model
AI Assistify presents a moderate-to-high agentic risk due to its integration of powerful LLMs with workflow automation and external messaging channels (WhatsApp, Telegram), combined with a lack of visible security guardrails or sandboxing in its public listing.
OWASP AIVSS score rationale
| Autonomy of Action | 0.60 | |
| Goal-Driven Planning | 0.50 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.70 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.30 | |
| Multi-Agent Interactions | 0.20 | |
| 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.
Integrates leading foundation models (GPT-4, Claude, Gemini). Risks include prompt injection, model reprogramming, and adversarial inputs that could bypass system prompts to manipulate the agent's behavior.
Allows users to train agents with their own documents (RAG). This introduces risks of document-based prompt injection, knowledge-base poisoning, and unauthorized data exfiltration if document access controls are weak.
Features a no-code platform with workflow automation and a library of tools. Insecure tool integration or lack of strict input validation on tool parameters could lead to tool misuse or arbitrary code execution within the workflow context.
Not certain from the listing — hosting, sandboxing, and secrets management details are not specified, but embedding agents into external channels like WhatsApp and Telegram exposes communication endpoints to potential interception or spoofing.
Not certain from the listing — observability, logging, and guardrail mechanisms are not detailed, posing a risk of blind spots where malicious agent behavior or data leakage could go undetected.
Not certain from the listing — identity, authorization, and compliance policies (such as SOC2 or GDPR) are not described, which is critical for a multi-tenant B2B platform handling proprietary business documents.
Not certain from the listing — while users can deploy multiple custom agents, explicit multi-agent coordination, trust boundaries, or marketplace dynamics are not detailed.
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.