AgentKit — agentic threat model

Not certain from the listing — AgentKit is model-agnostic, supporting single model inference calls and Anthropic MCP. Foundation model threats (adversarial prompt injection, model alignment bypasses) will depend entirely on the specific LLMs integrated by the developer.

Not certain from the listing — The directory listing does not specify built-in vector stores or RAG data operations. Data poisoning and exfiltration risks depend on how developers implement data pipelines within the customizable workflows.

As an orchestration framework, AgentKit directly manages planning, workflows, and tool calling. Vulnerabilities at this layer include insecure tool integration, workflow bypasses via prompt injection, and logic flaws in modular agent orchestration.

Not certain from the listing — Being an open-source framework, deployment and infrastructure security (such as container sandboxing, secrets management for tool APIs, and network isolation) are left entirely to the end-user.

Not certain from the listing — While the framework mentions rate limiting, it does not detail built-in evaluation, logging, or guardrail mechanisms, leaving potential blind spots in monitoring agent behavior and detecting anomalies.

The framework provides basic 'Rate limiting' as a built-in control, but lacks explicit mention of enterprise security controls like role-based access control (RBAC), audit logging, or compliance certifications, which must be implemented externally.

With explicit support for 'Modular agent collaboration' and 'multi-agent systems', the framework is highly exposed to ecosystem threats such as agent-to-agent trust abuse, cascading failures across collaborative workflows, and malicious tool usage via MCP.