FlowGent AI — agentic threat model

Not certain from the listing — FlowGent is an orchestration platform, meaning the underlying foundation models are integrated by the user, leaving model-level threats like adversarial examples or data poisoning dependent on the chosen external LLM provider.

Not certain from the listing — The platform supports automation flows and AI agents, which implies data ingestion, but specific vector databases, RAG pipelines, or data lineage controls are not detailed.

FlowGent acts as an agent framework combining AI agents and traditional automation flows. This hybrid nature introduces risks of insecure tool integration, where malicious prompt injection in an AI agent could trigger unintended actions in a connected deterministic automation flow.

As an open-source and paid platform hosting client-accessible portals, infrastructure security is critical. Risks include container escape, privilege escalation, and exposed API endpoints if the self-hosted or managed environments are not properly sandboxed.

Not certain from the listing — There is no mention of built-in evaluation frameworks, guardrails, or observability tools to monitor agent drift, prompt injections, or anomalous automation executions.

The presence of a 'whitelabel portal you can give your client access to' highlights critical multi-tenancy, authentication, and authorization risks. Weak access controls could lead to cross-client data leakage or unauthorized modification of automation flows.

Because FlowGent allows building multiple AI agents and automation flows, there is a risk of cascading failures where one compromised agent or broken automation flow triggers a chain reaction across the client ecosystem.