ChainClarity — agentic threat model
ChainClarity is a low-risk, read-only research agent focused on summarizing crypto whitepapers. Its primary security risks stem from potential data poisoning of its whitepaper library and LLM hallucinations that could mislead users during financial due diligence.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.30 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.40 | |
| Opacity & Reflexivity | 0.30 |
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 LLM is not specified. Potential threats include model hallucination or adversarial prompt injection designed to bias the analysis of specific crypto projects.
The agent relies on a database of 500+ crypto whitepapers. Key threats include data poisoning (injecting malicious or biased whitepapers into the library) and RAG retrieval manipulation.
Not certain from the listing — the orchestration framework for 'Qai' is undisclosed. Potential threats include insecure prompt templates or prompt injection bypassing the 'no hype' guardrails.
Not certain from the listing — hosting and infrastructure details are not provided. Standard web application threats apply, such as unauthorized access to the underlying vector database or API endpoints.
Not certain from the listing — no mention of evaluation frameworks or real-time monitoring. Gaps here could allow drift in summarization quality or undetected adversarial manipulation of outputs.
Not certain from the listing — no compliance certifications (e.g., SOC2) or specific identity/access management controls are detailed for this closed-source platform.
The agent operates as a standalone research tool with no multi-agent or ecosystem integrations mentioned. Threat of cascading failures or A2A trust abuse is minimal.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).