TeamPal — agentic threat model
TeamPal is a highly capable horizontal AI agent platform utilizing advanced LLMs and diverse tools (web browsing, file handling, doc generation) across business functions, presenting a significant attack surface for prompt injection, data exfiltration, and tool abuse due to a lack of visible security controls or sandboxing.
OWASP AIVSS score rationale
| Autonomy of Action | 0.60 | |
| Goal-Driven Planning | 0.50 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.70 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.40 | |
| 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.
Uses advanced foundation models including GPT-4o, Claude 3.5 Sonnet, and Gemini 1.5. Threats include prompt injection, adversarial inputs, and model-specific alignment bypasses that could hijack assistant behavior.
Not certain from the listing — No explicit details on RAG, vector databases, or data storage are provided, but handling files (images, PPTs, videos) and web browsing implies temporary or persistent data ingestion risks like data exfiltration or ingestion of malicious payloads.
Orchestrates 80+ assistants and 30+ pre-built skills (Doc maker, Web browsing, File handling). Threats include insecure tool calling, prompt injection leading to unauthorized tool execution (e.g., SSRF via web browsing), and logic flaws in task execution.
Not certain from the listing — The hosting environment, sandboxing of file execution/generation, and secrets management for third-party integrations are not specified, posing risks of container escape or lateral movement if file handling is unsandboxed.
Not certain from the listing — No monitoring, logging, or guardrail mechanisms are mentioned, which could lead to blind spots in detecting malicious prompt injections or anomalous tool usage.
Not certain from the listing — The platform is closed-source and paid, but there is no mention of enterprise security controls, access management (RBAC), or compliance certifications (like SOC2 or GDPR).
Features 80+ AI assistants and a Task Library. Threats include cascading failures if one assistant is compromised, or unauthorized cross-assistant interaction/trust abuse within the platform.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).