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Chai — agentic threat model

8.6AIVSS 8.6 · High

Chai is a closed-source, no-code AI agent development platform that introduces moderate-to-high risk due to the rapid deployment of LLM-based automation tools (like email summarizers and support bots) without visible built-in security guardrails, sandboxing, or compliance controls.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 7.5AARS uplift 1.07Factor sum 4.3/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.60
Goal-Driven Planning
0.40
Self-Modification
0.10
Dynamic Tool Use
0.50
Persistent Memory
0.40
Contextual Awareness
0.60
Dynamic Identity
0.20
Multi-Agent Interactions
0.10
Non-Determinism
0.70
Opacity & Reflexivity
0.70

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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — The platform leverages LLMs for prompt-to-agent creation, making it susceptible to prompt injection, adversarial reprogramming, and misaligned outputs, but the specific underlying models are not disclosed.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — While agents handle data for email summarization and customer support, the platform's data ingestion, vector database usage, and RAG capabilities are not detailed.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — Chai orchestrates prompt-to-agent conversion and automation, but the underlying execution framework, memory management, and tool-calling mechanisms are proprietary and unspecified.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — The platform hosts and deploys user-created agents, but details regarding containerization, sandboxing of execution environments, and secrets management are absent.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — No built-in guardrails, evaluation frameworks, or monitoring tools for deployed agents are explicitly mentioned in the directory listing.

L6 · Security & Compliance (cross-cutting)⚠ not certain from listing

Not certain from the listing — The platform is closed-source and freemium, but there is no mention of enterprise security controls, access management, or compliance certifications (e.g., SOC2, GDPR).

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — While it is an agent development platform, there is no explicit mention of a multi-agent marketplace or direct agent-to-agent interaction protocols.

MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).