Floot — agentic threat model

Not certain from the listing — Floot likely relies on external commercial LLMs (like OpenAI or Anthropic) or open-source models to generate code, exposing it to prompt injection, model reprogramming, or malicious code generation if the underlying model is manipulated.

Not certain from the listing — Floot must manage user prompts, generated codebases, and potentially database schemas. Lack of details on data isolation or vector stores leaves it vulnerable to data leakage or poisoning of code templates.

Floot acts as an orchestration framework translating high-level user intent into multi-step code generation, database schema creation, and deployment. Insecure tool integration or prompt injection could lead to the generation of vulnerable code or unauthorized system modifications.

Since Floot hosts the generated apps (backend, database, auth), the infrastructure layer is highly critical. If the hosting environment lacks strict containerization or sandboxing, a generated malicious app could lead to container escape, lateral movement, or host compromise.

Not certain from the listing — There is no mention of built-in guardrails, code scanning (SAST), or runtime monitoring for the generated applications, creating a blind spot for deployed vulnerabilities.

Floot handles authentication and hosting for production-grade apps. Without explicit compliance certifications (like SOC2) or robust built-in identity/access management policies, users risk deploying non-compliant or insecure applications.

Not certain from the listing — Floot does not explicitly mention multi-agent coordination or marketplace integrations, but if it interacts with external APIs or package registries, it faces supply chain and cascading failure risks.