Agent Pilot — agentic threat model
Agent Pilot is a highly flexible, open-source multi-agent orchestration framework featuring a local code interpreter and tool integration. Its primary security risks stem from the execution of arbitrary code and tools locally without explicit sandboxing, alongside the management of sensitive API keys.
OWASP AIVSS score rationale
| Autonomy of Action | 0.60 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.30 | |
| Dynamic Tool Use | 0.80 | |
| Persistent Memory | 0.50 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.40 | |
| Multi-Agent Interactions | 0.80 | |
| Non-Determinism | 0.70 | |
| Opacity & Reflexivity | 0.50 |
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 framework allows users to bring their own keys and models from different providers. Threats include model alignment issues, API key exposure, and adversarial prompt injection affecting the integrated models.
Not certain from the listing — while the description mentions using 'local data', it does not specify the storage mechanisms, vector databases, or data ingestion pipelines, leaving potential risks of local data poisoning or unauthorized local file access unaddressed.
As an orchestration framework supporting graph workflows, nestable workflows, and a code interpreter, it is highly susceptible to tool misuse, insecure tool integration, and remote code execution if untrusted inputs are processed by the interpreter.
Not certain from the listing — the framework is 'pure python' and 'cross platform' for local execution, but the listing does not detail any sandboxing or containerization controls for the code interpreter, posing a high risk of host compromise.
Not certain from the listing — there is no mention of built-in evaluation, logging, monitoring, or guardrail mechanisms to detect anomalous agent behavior or malicious outputs.
Not certain from the listing — the tool relies on the user's own keys and local environment, with no explicit mention of enterprise security controls, access policies, or compliance auditing features.
Supports complex multi-member workflows and configuring interactions between different models. This introduces risks of cascading failures, multi-agent trust abuse, and complex emergent behaviors within the configured graph.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).