← Startup Readiness Assessment
Startup Readiness Assessment — agentic threat model
The Startup Readiness Assessment is a low-risk, diagnostic agent designed for self-auditing. Its primary security risks are limited to the confidentiality of user-submitted startup data and the potential for prompt injection to manipulate assessment scores.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.00 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.30 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.30 | |
| Opacity & Reflexivity | 0.20 |
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 a standard commercial foundation model to parse user inputs. Primary threats include prompt injection to bypass the structured framework or manipulate the objective readiness scoring.
Not certain from the listing — processes proprietary startup details, operational gaps, and strategic plans. If these inputs are stored or used for model fine-tuning without anonymization, there is a risk of intellectual property leakage.
Not certain from the listing — orchestration is likely a simple linear template matching the six-pillar framework. Risks of tool misuse or insecure integration are minimal due to the lack of active tool execution capabilities.
Not certain from the listing — hosted as a standard web-based freemium tool. Standard web application vulnerabilities and lack of tenant isolation for session data represent the primary infrastructure risks.
Not certain from the listing — no explicit guardrails or observability mechanisms are mentioned to detect hallucinated advice or biased scoring in the diagnostic output.
Not certain from the listing — lacks details on data retention policies, encryption, or compliance with privacy regulations (e.g., GDPR) regarding founder and team information.
The agent operates as an isolated, standalone diagnostic tool. There are no multi-agent interactions, marketplace dependencies, or external ecosystem integrations described.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).