CVE-2026-34046

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to version 1.5.1, the `_read_flow` helper in `src/backend/base/langflow/api/v1/flows.py` branched on the `AUTO_LOGIN` setting to decide whether to filter by `user_id`. When `AUTO_LOGIN` was `False` (i.e., authentication was enabled), neither branch enforced an ownership check — the query returned any flow matching the given UUID regardless of who owned it. This allowed any authenticated user to read any other user's flow, including embedded plaintext API keys; modify the logic of another user's AI agents, and/or delete flows belonging to other users. The vulnerability was introduced by the conditional logic that was meant to accommodate public/example flows (those with `user_id = NULL`) under auto-login mode, but inadvertently left the authenticated path without an ownership filter. The fix in version 1.5.1 removes the `AUTO_LOGIN` conditional entirely and unconditionally scopes the query to the requesting user.

An attacker registers or compromises any valid Langflow account in a multi-user deployment. They call GET /api/v1/flows/{uuid} iterating UUIDs (which are sequential or discoverable via timing), receiving full flow JSON including plaintext API keys for connected LLM providers. They exfiltrate the keys for unauthorized LLM API usage or lateral movement into connected services. They then issue a PATCH request to silently modify a victim's flow — injecting a malicious tool node or system prompt that persists across future agent executions — poisoning the AI agent's behavior without any visible indication to the legitimate owner.