i10X.ai — agentic threat model
i10X.ai acts as a highly connected hub aggregating multiple LLMs and over 500 third-party tools, presenting a significant attack surface where prompt injection could lead to unauthorized tool execution or data exposure across various business domains.
OWASP AIVSS score rationale
| Autonomy of Action | 0.40 | |
| Goal-Driven Planning | 0.30 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.70 | |
| Persistent Memory | 0.30 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.20 | |
| Non-Determinism | 0.80 | |
| 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.
The platform provides unified access to leading foundation models (ChatGPT, Claude, Gemini, Perplexity). This exposes the workspace to model-specific vulnerabilities, including adversarial prompt injection, jailbreaking, and data leakage to third-party model providers.
Not certain from the listing — there is no mention of how user data, session history, or RAG vector stores are managed or isolated across the 500+ tools and multiple LLM providers, raising potential data leakage and lineage concerns.
The platform orchestrates over 500 curated AI tools across business and creative tasks. Insecure tool integration or lack of strict input validation could allow malicious prompts to hijack tool execution (e.g., in legal drafting or marketing automation tools).
Not certain from the listing — although noted as open source, the deployment architecture, hosting environment, secrets management for LLM API keys, and sandboxing of executed tools are not detailed.
Not certain from the listing — there is no mention of built-in guardrails, real-time monitoring, or logging mechanisms to detect anomalous agent behavior or malicious tool usage.
Not certain from the listing — despite handling sensitive business and legal tasks, the listing does not specify identity governance, access controls, or compliance alignments (such as SOC2 or GDPR).
The platform features a constantly updated library of AI agents and curated tools. This introduces supply-chain risks, where a compromised or malicious agent/tool added to the library could exploit the unified workspace to access other models or user data.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).