Singularitycrew — agentic threat model
Singularitycrew is a no-code AI agent creation platform that introduces significant risk due to the democratization of agent deployment without visible built-in security guardrails, potentially leading to insecure tool integration and unauthorized business automation.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.60 | |
| Self-Modification | 0.20 | |
| Dynamic Tool Use | 0.70 | |
| Persistent Memory | 0.50 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.40 | |
| Multi-Agent Interactions | 0.50 | |
| 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 — The platform allows users to define roles and functions, but the specific underlying foundation models (e.g., proprietary or open-source LLMs) and their alignment/reprogramming protections are not disclosed.
Not certain from the listing — No details are provided regarding data storage, vector databases, RAG pipelines, or data ingestion mechanisms used by the created agents.
The platform acts as a no-code agent orchestration framework allowing users to define roles, functions, and behaviors. Threats include insecure tool integration, tool misuse, and framework-level vulnerabilities during agent execution.
Not certain from the listing — The hosting environment, sandboxing of user-defined agent functions, and secrets management are not specified in the public directory listing.
Not certain from the listing — There is no mention of built-in evaluation, monitoring, logging, or guardrail mechanisms for the created agents.
Not certain from the listing — No compliance certifications (e.g., SOC2, ISO) or specific identity/access management controls are detailed in the listing.
The platform is designed for creating multiple customizable AI agents for business automation, implying potential multi-agent interactions or cascading failures if compromised agents interact within an enterprise ecosystem.
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.