Langflow Langflow vulnerabilities

IBM Langflow OSS 1.0.0 through 1.9.3 contains a Server-Side Request Forgery (SSRF) protection bypass vulnerability in the API Request component. An authenticated attacker with low-level privileges (flow author role) can bypass SSRF protections by enabling the follow_redirects parameter and supplying a public URL that redirects to internal/localhost addresses. The vulnerability exists because the application validates only the initial URL but does not re-validate redirect destinations. This allows attackers to access internal HTTP services, localhost endpoints, cloud metadata services, and private network resources that should be unreachable when SSRF protection is enabled. Successful exploitation can lead to disclosure of sensitive information including credentials, tokens, internal API responses, and administrative panel data.

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.0.19, an attacker can send a /api/v1/files/upload/ request without any authentication token/cookies and abuse a very long multipart form boundary to make the langflow app unusable for all users for an indefinite amount of time. This vulnerability is fixed in 1.0.19.

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.9.1, an Insecure Direct Object Reference (IDOR) vulnerability in /api/v1/responses endpoint allows an authenticated attacker to execute any flow belonging to another user by specifying the victim's flow ID in the request. This vulnerability is fixed in 1.9.1.

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.9.0, Langflow's /api/v1/monitor router exposes 7 endpoints that perform read, write, and delete operations on user-owned resources — messages, sessions, build artifacts, and LLM transaction logs — without verifying that the authenticated requester owns the targeted resource. Any authenticated user can read, modify, rename, or permanently delete another user's data by supplying the target's resource ID or flow_id. This is a classic IDOR/BOLA vulnerability. Notably, the same source file (monitor.py) contains one correctly-implemented endpoint that uses an ownership check, demonstrating the correct pattern was known but inconsistently applied. This vulnerability is fixed in 1.9.0.

A vulnerability was identified in langflow-ai langflow up to 1.9.3. This affects an unknown function of the component Bundle URL Loader. The manipulation leads to code injection. The attack needs to be performed locally. The vendor was contacted early about this disclosure but did not respond in any way.

IBM Langflow OSS 1.0.0 through 1.9.1 could allow an authenticated user to read or modify sensitive information by bypassing authentication using insecure direct object references.

IBM Langflow OSS 1.0.0 through 1.9.0 could allow a denial of service due to uncontrolled resource consumption.

IBM Langflow OSS 1.0.0 through 1.8.4 could allow any user to supply a flow_id to read transaction logs and vertex build data belonging to other users, and to delete persisted vertex build data for another user's flow.

IBM Langflow Desktop 1.6.0 through 1.8.2 Langflow could allow an authenticated user to execute arbitrary code on the system, caused by an insecure default setting which permits the deserialization of untrusted data in the FAISS component.

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.