Langflow versions prior to 1.9.0 contain a critical path traversal vulnerability in the Knowledge Bases API DELETE endpoint. This flaw allows an authenticated attacker to delete arbitrary directories on the server by supplying crafted knowledge base names that bypass path sanitization. The vulnerability can lead to significant data loss and service disruption. A fix for this issue is included in Langflow version 1.9.0.
A weakness has been identified in langflow-ai langflow up to 1.10.2. This affects the function eval of the file src/lfx/src/lfx/components/llm_operations/lambda_filter.py of the component LambdaFilterComponent. Executing a manipulation can lead to code injection. The attack may be performed from remote. The exploit has been made available to the public and could be used for attacks. The vendor was contacted early about this disclosure but did not respond in any way.
CVE-2026-7687 is a command injection vulnerability in langflow-ai langflow versions up to 1.8.4. It affects the function CodeParser.parse_callable_details in the Full Builtins Module Handler component. The vulnerability allows remote attackers to execute arbitrary commands by manipulating input to this function. The exploit has been publicly disclosed, but the vendor has not responded or provided a fix. The vulnerability has a medium severity with a CVSS score of 5.3.
A flaw has been found in langflow-ai langflow up to 1.8.3. This affects an unknown function of the file src/frontend/src/modals/IOModal/components/chatView/chatMessage/components/edit-message.tsx of the component Frontend React Component Rendering. Executing a manipulation can lead to cross site scripting. The attack may be launched remotely. The exploit has been published and may be used. The vendor was contacted early about this disclosure but did not respond in any way.
A vulnerability was detected in langflow-ai langflow up to 1.8.3. The impacted element is the function get_client_ip/install_mcp_config of the file src/backend/base/langflow/api/v1/mcp_projects.py of the component Model Context Protocol Configuration API. Performing a manipulation of the argument X-Forwarded-For results in injection. The attack may be initiated remotely. The exploit is now public and may be used. The vendor was contacted early about this disclosure but did not respond in any way.
A security vulnerability has been detected in langflow-ai langflow up to 1.8.3. The affected element is the function create_project/encrypt_auth_settings of the file src/backend/base/Langflow/api/v1/projects.py of the component Project Creation Endpoint. Such manipulation of the argument auth_settings leads to cleartext storage in a file or on disk. The attack can be launched remotely. The exploit has been disclosed publicly and may be used. The vendor was contacted early about this disclosure but did not respond in any way.
A weakness has been identified in langflow-ai langflow up to 1.8.3. Impacted is the function remove_api_keys/has_api_terms of the file src/backend/base/langflow/api/utils/core.py of the component Flow Using API. This manipulation causes unprotected storage of credentials. The attack can be initiated remotely. The exploit has been made available to the public and could be used for attacks. The vendor was contacted early about this disclosure but did not respond in any way.
A security flaw has been discovered in langflow-ai langflow up to 1.1.0. This issue affects the function create_upload_file of the file src/backend/base/Langflow/api/v1/endpoints.py of the component API Endpoint. The manipulation results in unrestricted upload. It is possible to launch the attack remotely. The exploit has been released to the public and may be used for attacks. The vendor was contacted early about this disclosure but did not respond in any way.
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.
Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to version 1.9.0, the Agentic Assistant feature in Langflow executes LLM-generated Python code during its validation phase. Although this phase appears intended to validate generated component code, the implementation reaches dynamic execution sinks and instantiates the generated class server-side. In deployments where an attacker can access the Agentic Assistant feature and influence the model output, this can result in arbitrary server-side Python execution. Version 1.9.0 fixes the issue.
The 'POST /api/v2/files' endpoint does not sanitize the 'filename' parameter from the multipart form data, allowing an attacker to write files to arbitrary locations on the filesystem using path traversal sequences ('../').
The '/api/v1/files/images/{flow_id}/{file_name}' endpoint serves SVG files with the 'image/svg+xml' content type without sanitizing their content.
Since SVG files can contain embedded JavaScript, an attacker can upload a malicious SVG that executes arbitrary JavaScript when viewed by other users, leading to stored cross-site scripting (XSS). This allows stealing authentication tokens stored in cookies, including JWT access and refresh tokens.
The '/logs' and '/logs-stream' endpoints in the log router allow any authenticated user to read the full application log buffer. These endpoints only require basic authentication ('get_current_active_user') without any privilege checks (e.g., 'is_superuser').
The '/api/v1/files/images/{flow_id}/{file_name}' endpoint does not enforce any authentication or authorization checks, allowing any unauthenticated user to download images belonging to any flow by knowing (or guessing) the flow ID and file name.
Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to version 1.7.1, in the download_profile_picture function of the /profile_pictures/{folder_name}/{file_name} endpoint, the folder_name and file_name parameters are not strictly filtered, which allows the secret_key to be read across directories. Version 1.7.1 contains a patch.
Langflow is a tool for building and deploying AI-powered agents and workflows. In versions 1.0.0 through 1.8.1, the `/api/v1/files/images/{flow_id}/{file_name}` endpoint serves image files without any authentication or ownership check. Any unauthenticated request with a known flow_id and file_name returns the image with HTTP 200. In a multi-tenant deployment, any attacker who can discover or guess a `flow_id` (UUIDs can be leaked through other API responses) can download any user's uploaded images without credentials. Version 1.9.0 contains a patch.
CVE-2026-33475 is a critical unauthenticated remote shell injection vulnerability in the langflow-ai Langflow project prior to version 1.9.0. It arises from improper neutralization of special elements in GitHub Actions workflows, where user-controlled GitHub context variables like branch names or pull request titles are directly interpolated into shell commands without sanitization. Attackers can exploit this by crafting malicious branch names or PR titles to inject arbitrary shell commands during CI/CD execution, leading to exfiltration of sensitive secrets such as GITHUB_TOKEN, manipulation of infrastructure, or supply chain compromise. The vulnerability affects multiple workflow files and actions within the Langflow repository. The fix involves refactoring workflows to use environment variables with proper quoting instead of direct interpolation. Given the high CVSS score of 9.1, this vulnerability poses a severe risk to any public Langflow forks with GitHub Actions enabled.
CVE-2026-33309 is a critical path traversal vulnerability in langflow versions 1.2.0 through 1.8.1. It arises from an architectural flaw in the LocalStorageService where boundary checks are missing, allowing an authenticated attacker to bypass filename validation on the POST /api/v2/files/ endpoint. This enables arbitrary file write anywhere on the host system, potentially leading to remote code execution without user interaction. The vulnerability stems from a failed patch for a previous related issue (CVE-2025-68478) and is fixed in version 1.9.0.
CVE-2026-33053 is an authorization bypass vulnerability in langflow versions prior to 1.9.0. The issue occurs because the delete_api_key_route() endpoint allows deletion of API keys based solely on a generic authentication check without verifying ownership of the API key. This flaw enables an authenticated user with limited privileges to delete API keys belonging to other users. The vulnerability is classified under CWE-639 (Authorization Bypass Through User-Controlled Key) and has a CVSS 4.0 score of 6.1 (medium severity). Exploitation requires authentication but no user interaction, and it can lead to denial of service for affected users by removing their API keys. No known exploits are currently reported in the wild.
Langflow is a tool for building and deploying AI-powered agents and workflows. In versions prior to 1.9.0, the POST /api/v1/build_public_tmp/{flow_id}/flow endpoint allows building public flows without requiring authentication. When the optional data parameter is supplied, the endpoint uses attacker-controlled flow data (containing arbitrary Python code in node definitions) instead of the stored flow data from the database. This code is passed to exec() with zero sandboxing, resulting in unauthenticated remote code execution. This is distinct from CVE-2025-3248, which fixed /api/v1/validate/code by adding authentication. The build_public_tmp endpoint is designed to be unauthenticated (for public flows) but incorrectly accepts attacker-supplied flow data containing arbitrary executable code. This issue has been fixed in version 1.9.0.
