ChainDesk — agentic threat model
ChainDesk presents a moderate-to-high risk profile due to its integration with custom business data sources and external APIs, which could be exploited via prompt injection to exfiltrate sensitive data or trigger unauthorized API actions.
OWASP AIVSS score rationale
| Autonomy of Action | 0.60 | |
| Goal-Driven Planning | 0.40 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.60 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.20 | |
| 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.
Leverages GPT-4 and other generative models. Primary threats include prompt injection, jailbreaking, and misaligned outputs that could lead to brand damage or misinformation during customer interactions.
Integrates with various business data sources for RAG and automated retraining. This introduces risks of knowledge-base poisoning if source documents are manipulated, as well as potential data exfiltration of sensitive internal data.
Uses a no-code orchestration framework supporting custom API endpoints and ChatGPT plugins. Insecure tool integration and lack of input sanitization before API execution could allow attackers to trigger unauthorized backend actions.
Not certain from the listing — hosted platform details are not provided. General commentary: Standard cloud hosting risks apply; robust tenant isolation and secure secrets management are critical to prevent cross-tenant data access or credential theft.
Not certain from the listing — mentions automated retraining but lacks details on guardrails or monitoring. General commentary: Automated retraining without strict evaluation guardrails risks introducing drift, bias, or poisoned data into the active model.
Not certain from the listing — no explicit compliance certifications (like SOC2, GDPR) or fine-grained RBAC are mentioned. General commentary: Crucial to ensure robust authentication for custom API endpoints and data source connectors to prevent unauthorized access.
Integrates with ChatGPT plugins and multi-channel platforms. This exposes the agent to ecosystem risks, where a compromise in a third-party plugin or channel could lead to cascading security failures.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).