Bit Flows — agentic threat model

Integrates with external LLMs (OpenAI, Claude, Gemini). The primary threat is prompt injection via incoming workflow data (e.g., CRM updates, emails) which could manipulate the AI steps to execute unintended actions or leak sensitive system prompt instructions.

Not certain from the listing — no explicit mention of vector databases or RAG pipelines, but the plugin processes extensive transactional, CRM, and e-commerce data flowing through WordPress, making data exfiltration and lineage tracking key concerns.

The orchestration framework handles multi-step workflows, conditional logic, and delays. Vulnerabilities here include insecure tool integration where malicious inputs bypass conditional checks to trigger unauthorized API actions across the 180+ integrations.

Deployed directly as a WordPress plugin. This inherits the entire attack surface of the host WordPress site. A compromise of the plugin database exposes API keys for all connected platforms, and lack of execution sandboxing could lead to remote code execution on the host.

Features a 'Powerful Log System' to track flow executions. However, there is a risk of log injection if untrusted input from triggers is written directly to logs, or blind spots regarding the specific reasoning steps taken by the integrated AI models.

Not certain from the listing — no explicit security compliance, encryption standards, or access control mechanisms are detailed beyond standard WordPress user roles, leaving potential gaps in credential storage security and auditability.

Operates in a dense ecosystem connecting 180+ platforms. A compromised workflow or malicious trigger can cause cascading failures across multiple connected enterprise APIs, leading to widespread data corruption or unauthorized actions in external systems.